Synapse - Africa’s 4IR Trade & Innovation Magazine - 3rd Quarter 2022 Issue 17 (Show Edition)

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Africa’s 4IR Trade & Innovation Magazine SYNAPSE BLUEPRISM Employee Experience Boosted by AutomationAdvanced EMBASSYNETHERLANDS AI that Champions Inclusion SWITZERLAND Harvesting the Fruits of the AI Summer tinyML is the next wave of LearningMachine WELCOME TO THE AI TECH CAPITAL OF AFRICA 3rd QUARTER 2022 | ISSUE 17 AI AFRICAEXPO2022 5TH ANNIVERSARY EDITIONCELEBRATING THE RETURN TO IN-PERSON EVENTS

C o n n e c t ing Knowledge Innovation Education Support B u s i n e s s www.aiexpoafrica.com Join the largest B2B AI, RPA & Smart Tech Trade Event in Africa & explore the growing 4IR opportunity in the region 3 Day event 80+ Speaker Programme / 1,500+ Companies / Live Networking Speaker Lounge / Trade Expo / Country ePavilions 19-20 SEP2022 CONVENTIONSANDTON CENTRE SOUTHJOHANNESBURG,AFRICA Buy Tickets Now

13RD QUARTER 2022 | SYNAPSE 4 Nvidia Omniverse Ecosystem Expands 10x, Amid New Features and Services for Developers, Enterprises and Creators 6 SW7: To Scale your AI Business, your product has to be Built To Sell 8 Switzerland Harvesting the Fruits of the AI Summer 10 tinyML 13 The African Union Artificial Intelligence Continental Strategy For Africa 14 AI Expo Africa 2022: Join Us in Johannesburg in 2022 16 AI Expo Africa 2022: AI Expo Africa Show Stats 17 AI Expo Africa 2022: Testimonials & Vendors 19 Predictive Insights: Using AI and economics to plan for the future 22 State of AI in Africa 2022 Report 24 Enlabeler: SA Startup Aims To Grow Africa’s Footprint In AI And Data Labelling 26 Intel taps North West TVET college to spark AI appetite 28 AI start-up DataProphet raises R166m funding 31 Zindi raises US $1 million in a seed round to expand its network of data scientists 32 Arm Launches Cortex Lab in South Africa 34 Analytics Hive 36 Ashanti: The untapped power of artificial intelligence in the retail industry 38 BluePrism: ROI and Employee Experience Boosted by Advanced Automation 40 Accelerate your data science and automation journey with next generation AI 42 Data Sciences Corporation: How does AI fit into your business? 44 Dutch Embassy: AI that Champions Inclusion 46 EcosystemAI: Human-Centric Interactions 48 Cirrus: AI for Science in Africa 52 HyperCap: HyperAutomation360-Degree Cognitive DPA 54 IBM: How to create business value with AI 56 Saucecode: Business automation goes beyond RPA 58 Telkom Business brings AI-driven multilingual translation services to SMMEs Contents Data business?doesCorporation:SciencesHowAIfitintoyour p42 SYNAPSE | ISSUE 17 | 3rd QUARTER 2022 Saucecode: Business automation goes beyond RPA p56 SW7: To Scale your AI Business, your product has to be Built To Sell p6 InteractionsHuman-CentricEcosystemAI: p46Predictive Insights: Using AI economicsandto plan for the future p19

f data is the new oil, then Natasha is a veteran key to the fostering of its growth. She is a transformative and dynamic leader within the Data Science and Artificial Intelligence space who is well immersed across various industries. In that, she garnered a strong skill-set in data processes, business operations, start-up building and project management. In a bid to champion Artificial Intelligence in Africa, she co-founded the AI Centre of Excellence that aims to build sustainable value for AI in Africa by building capacity, building demand and building AI solutions through the Centre.

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Darlington Akogo (Ghana) CEO, minoHealth AI / KaraAgro AI & Member of United Nations ITU & WHO Focus Group on AI For Health darlingtonakogo W naomimolefe

Dr Nick Bradshaw Editor & CEO AI Media Group Welcome to Edition 17

Natasha Ochiel (Kenya) Co-Founder | CEO The AI Centre of natasha@aiceafrica.comExcellence natasha-ochiel

nickbradshaw aomi is a people strategist and business researcher with 10 years’ experience in using applied research methodologies to drive strategic decision making. Naomi has consulting experience across industries, financial services, media entertainment, telecommunications, and mining. She has developed capabilities in service management design, business process optimisation and strategic talent sourcing. She is the co-Founder and Chapter Director for women in Big Data SA; a registered NPO that is part of a global community of 17 000 women. The learning community works with strategic partners to cultivate tangible opportunities for women, unlock latent potential through accessible training and act as a catalyst for the advancement of women in Big Data fields.

ow - what a year its been !! The Post C19 unlocking brought the launch our our inaugural State of AI in Africa Report in partnership with WEF C4IR and the UN ITU. The feedback was amazing as we finally begin to map the entire African AI Ecosystem. We also offer a warm welcome to our new Guest Editor Naomi Molefe, MSc, Manager: Strategic Sourcing and Research at Discovery & Co-Founder & Chapter Director Women In Big Data, South Africa. Naomi will be focused on our Southern African news and stories. Finally, this is the 17th / 5th Show Edition of Synapse Magazine - the sister publication to the AI Expo Africa event. This is a big milestone for us for many reasons; Its the 5th Anniversary of the show and we are moving to Johannesburg - the new “AI Tech Capital” of Africa and certainly the main regional hub for AI / 4IR tech, start-ups and innovation in Southern Africa. Plus, we made it through C19 ! The last 2+ years have been no easy journey for any of us and we count ourselves lucky that we had the support of our community and sponsors to get us through this chapter. We look forward to charting a new course into our 5th year and beyond. We hope you will stay around for the journey and encourage others to join our community.

arlington Akogo is a global leader in Artificial Intelligence. He's the Founder and Director of Artificial Intelligence at GUDRA, and its subsidiaries; minoHealth; an AI Healthtech company, minoHealth AI Labs; an AI Healthcare, Biotech and Biomedical Research Lab, karaAgro AI; an AI-powered Plant & Pest Disease Detection and Precision Agriculture platform, Runmila AI Institute; an AI and Data Science training institute, and Gudra AI Studio; an organisation broadly exploring AI and Exponential Technologies applied various domains including Transportation, Sanitation and Energy.

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N Naomi Molefe MSc, Manager: Strategic Sourcing and Research at Discovery & Co-Founder & Chapter Director Women In Big Data, South Africa

Editor's Notes

Tshwane is the knowledge centre of South Africa. The City has a high concentration of academic, medical, social science, technology and scientific institutions which produces 90% of medical, science and technology research in the country and 60% of the country’s overall research output. The city has a student population of 60000 and high levels of literacy, giving investors access to a skilled workforce and continuous learning.

•••••• For more information Contact Us 012 358 www.facebook.com/CityOfTshwanewww.teda.org.zawww.tshwane.gov.za9999 Block B, 2nd Floor Tshwane House 320 MadibaPretoriaStreet0002 PO BoxPretoria4400001

Invest in Tshwane

The city is home to four universities and various research institutes and its knowledge and information industry is well-developed. Tshwane has a high literacy rate, a large concentration of financial and business services in the region, support of educational institutions and communication infrastructure, including broadband capacity.

Your investment is safe with us, we are governed by investment protection legislation, The Protection of Investment Act 22 of 2015 which specifically gives foreign investors similar rights and protections available to South Africans.

We have great investment incentives such as the duty drawback schemes that provide refunds for import duties paid on the materials used in the production of goods that are re-exported.

There are no restrictions for foreign investors to acquire property in the country. There are no restrictions on foreign investors to acquire companies or businesses in South Africa.

Why Tshwane?

South Africa’s Capital City, the City of Tshwane, is situated in the province of Gauteng, the economic centre of South Africa. As the seat of government, Tshwane is the country’s administrative hub and houses 134 embassies, 30 international organisations making it second only to Washington DC in terms of the concentration of the diplomatic and foreign missions. It is also home to over 30 Johannesburg Stock Exchange-listed companies as well as various multinational companies.

Tshwane has a well-developed infrastructure and road network and is centrally situated on the national road network with direct links to Mozambique, Botswana and Namibia along the east-west N4 route, and with Zimbabwe along the south-north N1 route.

DEVELOP WITH NVIDIA OMNIVERSE Start building custom tools and applications today. Watch this technical session here Explore developer resources, learn more

Raising the Bar on Industrial Digital Twin NVIDIA also offers NVIDIA OVX, a comput ing system architecture designed to power large-scale digital twins. NVIDIA OVX is built to operate complex simu lations that will run within Omniverse, enabling designers, engineers and planners to create physically accurate digital twins and massive, true-to-reality simulation environments.

At GTC 2022 in March, NVIDIA announced new releases and updates for Omniverse — including the latest Omniverse Con nectors and libraries — expanding the platform’s ecosystem by 10x, and making Omniverse even more accessible to creators, developers, designers, engineers and researchers worldwide

Omniverse Enterprise Features and Availability Broadens More updates are coming soon to Omniverse Enterprise, including the latest releases of Omniverse Kit 103, Omniverse Create and View 2022.1, Omniverse Farm, and DeepSearch.

VENDOR INSIGHT

Omniverse Replicator: a framework for generating physically accurate 3D synthetic data to accelerate training and accuracy of perception networks — now available within Omniverse Code so devel opers can build their own domain-specific synthetic data engines.

OmniGraph, ActionGraph and AnimGraph: major new releases controlling behavior and animation.

NVIDIA Omniverse Ecosystem Expands

10x, Amid New Features and Services for Developers, Enterprises and Creators

With New Connections and Libraries The Omniverse ecosystem is expanding beyond design and content creation. In one year, Omniverse connections, ways to connect or integrate with the Omniverse platform, have grown 10x — with 82 con nections through the extended Omniverse ecosystem. Some of the new features that were announced by NVIDIA include: Third-Party Connections for Adobe Substance 3D Material Extension and Painter Connector, Epic Games Unreal Engine Connector and Maxon Cinema 4D will enable live-sync workflows between third-party apps and Omniverse.

Enhancing Content Creation

More TechnologiesOmniverseand Features Developer Tools: Omniverse Code, an app that serves as an integrated development environment for developers and powers users to easily build their own Omniverse extensions, apps or microservices.

When it comes to creating and connecting virtual worlds, over 150,000 individuals have downloaded NVIDIA Omniverse to make huge leaps in transforming 3D design workflows and achieve new heights of real-time, physically accurate simulations.

New versions of Omniverse Kit, Create, View and Machinima.

DeepSearch: a new AI-based search ser vice that lets users quickly search through massive, untagged 3D asset libraries using natural language or images. DeepSearch is available for Omniverse Enterprise customers in early access.

CAD Importers: These convert 26 com mon CAD formats to Universal Scene Description (USD) to better enable man ufacturing and product design workflows within Omniverse. Asset Library Integrations: TurboSquid by Shutterstock, Sketchfab and Reallusion ActorCore assets are now directly available within Omniverse Apps asset browsers so users can simply search, drag and drop from close to 1 million Omniverse-ready 3D assets. New Omniverse-ready 3D assets, materials, textures, avatars and animations are also now available from A23D.

Omniverse Avatar: a platform that uses AI and simulation technology to enable developers to build custom, intelligent, realistic avatars.

To learn more about NVIDIA Omniverse, watch the GTC 2022 keynote from Jensen Huang.

Hydra Render Delegate Support: Users can integrate and toggle between their favorite Hydra delegate-supported ren derers and the Omniverse RTX Renderer directly within Omniverse Apps. Now available in beta for Chaos V-Ray, coming soon for Maxon Redshift, OTOY Octane, Blender Cycles, and Autodesk Arnold.

Omniverse Enterprise on NVIDIA LaunchPad is available across nine global regions. NVIDIA LaunchPad gives design practi tioners and project reviewers instant, free turnkey access to hands-on Omniverse Enterprise labs, helping them make quicker, more confident software and infrastructure decisions.

Omniverse XR App: a VR-optimized con figuration of Omniverse View that enables users to experience their full-fidelity 3D scenes with full RTX ray tracing, at 1:1 scale, coming soon.

Business AI solutions are in high demand as they offer the fulfilment of the high scale, fully automated, intelligent, digital future promised by the 4IR however, AI sales cycles can be long, complex, frustrating and educational. or your AI business to scale, your product has to move from hard to sell to easy to buy. This means shorter sales cycles, higher conversion rates and happy customers. Easy to buy happens when your product is built to serve the two customer buying cycles, investigation “Why would I consider you” and seeking value “Why would I choose you?”. We share some components of the Sw7 B2B Sales Acceleration Playbook that help shorten AI sales cycles.

Sell The Way The Customer Buys

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Customer Problem Statements are your North Star to make sure you don’t drink too much ‘cool tech’ Kool-Aid. The Customer Problem Statement is the Compelling Event inside your target business that indicates the appetite to act. What has changed inside their business that would make them act now? Why would your project make the top three items on their to-do list? These statements only surface after a problem has been identified, internal awareness levels have been raised and there is some consensus to act. They surface at the end of an internal change management journey that could have taken weeks, months F BUSINESS, YOUR PRODUCT HAS TO BE BUILT TO SELL or even years. Customer Problem Statements ensure we have a business sponsor, political support, appetite, awareness and budget and identify the Compelling Event that indicates the customer is likely to act. The ultimate goal of B2B sales is to connect with a need that already exists, not try to create it.

2. Choose a Sector Your Customer Understands When the customer experiences a problem, they will seek a solution in a particular Sector. The Sector invites competition so if your sale is not competitive the chances of closing a deal diminish considerably. No competition means your largest competitor is the status quo, ‘do nothing’ is the hardest competitor of all to beat. So, choose a Sector based on the customer buying journey you wish to serve. The customer will expect you to have base-level functionality of all products in your chosen Sector. If you choose a Sector the customer does not care about or understand they will not know how to buy your product. Confused customers don’t buy.

4. Ensure Your Customer receives value from your solution Value is measured by the benefits received by the customer, not the benefits offered. If a process or behaviour change is required to realise benefits, then the project has a high chance of stalling. The Coping Mechanism indicates the capacity and capability of the business to embrace and act on your insights. The Coping Mechanism provides you with the evidence that the customer is able to engage with what you do and receive value.

5. The Customer Buying Journey  We have to sell the way the customer buys, we can’t change it  When the Customer experiences {this problem} (the Compelling Event)  They will seek a solution that is in {this Sector} Competition).(Investigation/Invite  They will choose a product that leads {this Category} (Seek Value/Eliminate Competition) because it takes them to a future they are invested in (Customer Aspiration). Evidence of the ability of the customer to leverage your solution is indicated by the existing behaviours (Coping WhilstMechanisms).workingwith technology and data to build your product is exciting and creative, this is just part of the journey to scale your AI business. Success can only be measured by the value the customer receives. Scale will depend on the rate you are able to acquire new customers and show them which is driven more by how you sell than what you sell. How you sell is more important than what you sell. Sales does not fix all problems, but it does fix most problems!

1. Focus on Your Customer Problem Statements

The Coping Mechanism is the workaround in place to cope with not having the data and insights you are offering. If there is no Coping Mechanism, there is no evidence to show that the customer has a genuine appetite to solve the problem or is able to ingest or action the insights. The Coping Mechanism will lead to existing datasets, business rules and decision processes. Are you asking the business to do something new or are you helping them do something they are already doing faster with better insights? Often you will find that your customer wants innovation, as long as it’s not new.

“ Don’t try to sell what you can build, build what you can sell ”

ENTREPRENEURSHIP TO SCALE YOUR AI



3. Identify the Category you will lead The Category you lead is framed by the customer aspirations and supported by your domain expertise and how you leverage state-of-the-art technology. The Category will describe a future that the customer aspires to. Your Category will eliminate competition and will identify why the customer would choose your solution over the alternatives. If you have to explain the Category to the customer, it is not usually aspirational for them. Lead a Category the customer cares about so you need to name it, frame it and claim it.

Wonderful is yourtheunleashingpowerofdata.

Built-in

Learn More Intel.com/Xeonat For more complete information about performance and benchmark results, visit www.intel.com/benchmarks. Intel, the Intel logo, and Xeon are trademarks of Intel Corporation or its subsidiaries. © Intel Corporation 2020

Xeon®

Intel® Scalable processors deliver industry leading, workload optimized performance through built-in AI acceleration, providing a seamless foundation to help speed data’s transformative impact, from the multi-cloud to the intelligent edge and back. AI acceleration is how wonderful gets done.

References:  Pabst, S., Sigrist, S. & Suter, D, (2022) Swiss AI Report Beyond the Hype on the use of Artificial Intelligence in Swiss Companies. WIRE & Mindfie. Available from:

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he Swiss approach around strategy, policy, and reports lies in the philosophy of a bottom-up approach facilitated through supportive framework conditions created by the Confederation. However, it was noted that the scope of artificial intelligence and its impact call for interventions from the Federal Council. The Digital Switzerland Strategy was adopted by the Federal Council on 11 September 2020, followed by AI guidelines, working groups, and guiding reports.

 Swiss Cognitive, (2021) Artificial Intelligence Industry in Switzerland Landscape Overview 2021 Q4. Available from: https://analytics.dkv. global/AI-in-Switzerland-2021-Q4/Report.pdf (Accessed: February 2022) T

The Swiss AI Report is looking at "Beyond the Hype" on the Use of Artificial Intelligence in Swiss Companies was released at the AI Conference held in Switzerland on 7 June 2022. For the first time, a report offers a systematic approach for assessing the use of AI technology by companies in Switzerland. The report demonstrates how established companies, start-ups, and research institutions are dealing with the new technology and illustrates the areas in which AI is already beingLetused.ussee how Switzerland is sunbathing in the AI Summer. For the Swiss AI Report, 92 companies were surveyed on their current and future use of Artificial Intelligence. The report includes systematic analyses in the critical areas for dealing with AI: technology & data, workforce, business, strategy, and governance. AI has climbed to strategic relevance backed by action and funding. The companies are willing to invest in AI, expecting to increase their AI budget by more than 100% in the next three years. Swiss companies are also acting as learning institutions focusing on the in-house capacity for AI development. AI is deployed for data management and analysis with humans still in the driver's seat. True to the Swiss reputation for innovation and precision is the outlook at the start-up level to increase the efficiency of processes through AI Companies are concerned about data integrity directly impacting value creation. A premium is placed on developing AI skills through a wide range of training, access, and exposure to AI. AI is a vehicle for job creation with data scientists, machine learning engineers, and data engineers in demand. Another interesting element of the survey is that AI must earn the trust of Swiss companies for full deployment in the coming years.

Key Findings of the Swiss AI Report of June 2022 (Pabst, 2022) Swiss AI companies are attracting more and more investments today. Switzerland is a country that has all the necessary infrastructure for market players to perform. Thanks to its traditional strength in innovation, Switzerland has 34.6 AI patents per 1 million inhabitants, 500 AI companies in 2021, and 37% of Swiss AI patents are world-class. The uptake of AI by Swiss companies is fueling the existing collaboration between industry and academia, with 71% of companies already in exchange or cooperation with research institutions. The reason for the Swiss academia-industry partnership is apparent. Switzerland has world-renowned universities and research institutes in the field of AI, demonstrated by the presence of tech giants running their AI research in Switzerland. Did you know that Switzerland is first in the Global The history of Artificial Intelligence (AI) certainly had its fair share of technology and investment roller costing from the coining of the technology in 1956 to the 'winter' period starting in 1974 to a renewed interest in 1987. And now, the 21st century brings us the 'AI Summer,' with Switzerland embracing the social, technological, and economic fruits of the AI Summer.

com/5e71f505e224b656715c1753/629f91e3ac23483a7102968https://uploads-ssl.webflow.5_Swiss_AI_Report_19052022.pdf(Accessed:July2022)

SWISS EMBASSY

SUMMERFRUITSHARVESTINGSWITZERLANDTHEOFTHEAI

Innovation Index, the Global Talent Competitiveness Index, the Impact of AI publication per country, and has the highest number of AI companies per capita in the European Union? Indeed we are not only enjoying the profits of the AI summer but also sharing these profits through our collaboration with South Africa in artificial intelligence.

COMMUNITY

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Popular applications include detecting and classifying objects in front of tiny low powered cameras, keyword spotting and figuring what sounds mean in real time from microphones. It doesn’t stop there and its possible to work with any kind of sensor to find interesting applications such building a low cost highly accurate artificial nose that runs on batteries as an interesting example of the kinds of new use cases made possible by tinyML.Thegrowing use cases span all industries and allow for businesses to implement predictive maintenance and demand optimisation in real time directly on the ground. In a quick response driven world, the agility provided by tinyML not only helps the T

Popular applications include detecting and classifying objects in front of tiny low powered cameras, keyword spotting and figuring what sounds mean in real time from microphones. It doesn’t stop there and its possible to work with any kind of sensor to find interesting applications such building a low cost highly accurate artificial nose that runs on batteries as an interesting example of the kinds of new use cases made possible by tinyML ”

tinyML is the next wave of Machine Learning that is enabling low power embedded systems to do what was once only possible in the domain of high performance cloud computing. Its fuelling the emerging field of Edge Machine Learning which makes it possible to run deep learning models directly at the edge on 32bit micro controllers. This has been made possible by breakthrough research into the optimization and deployment of convolutional neural networks pioneered by the TensorFlow Lite Team at Google. he focus of tinyML is to not just deploying deep learning neural network models on micro controllers but to also keeping the power consumption as low as possible. Newer systems and embedded AI accelerators are coming to the market at an unprecedented pace, bringing support for ever increasing model complexity at reducing levels of power consumption. This has brought the worlds of embedded systems and Artificial Intelligence together in turn activating new use cases and opportunities that were previously not feasible.Internet of Things or IoT evolved from adding connectivity to embedded systems to facilitate the capturing and forwarding of raw data about processes to the cloud, where machine learning would usually be used to derive insights. This consumes power and bandwidth and introduces a latency in the processing of the data into results. By leveraging unused computing capacity in these IoT devices to deploy tinyML models to derive insights directly from the data on NEWS the device itself, IoT becomes the Artificial Intelligence of Things or AIoT. The instant benefits are lower bandwidth and privacy as the raw data doesn't need to leave the device and its possible to send just the insights to the cloud via low cost, low bandwidth and of course low power data connections. The added benefits are longer periods between replacing batteries and immediate intelligent responses to the environment.

TinyML embodies this approach as more than just a technology but a philosophy and a movement with the goal of also uplifting the world through initiatives like TinyML for Good to drive sustainability and empower communities and democratize this disrupting technology. This is achieved through Meetup Groups, TinyML Talks, open access to information and resources all driven by the TinyML Foundations Strategic Partners forming a vibrant, diverse and thriving global community who all support each other with the shared goal. The pandemic has brought the world closer together and never before has it been more apparent that everyone is a global citizen with a part to play. The developing world is no exception as technology will only help solve problems if its affordable and accessible.

TinyML supports this through TinyML4D run out of Harvard that is making the technology open and accessible to all through the creation and dissemination of courseware tailored to support the developing world. In Africa the ecosystem is growing steadily having started in Northern Africa through the efforts of early inspirational pioneers who saw the need to develop skills as way to provide economic sustainability for theirWecommunities.haveonlyjust begun in Africa and there is a still a lot more work to do to spread it to all parts of Africa. In South Africa there are many challenges that need to be overcome which can be solved through job creation and entrepreneurship which in turn will be possible through skills development. This is driven by initiatives such ARM E3NGAGE and Coretex Hub where skills are being nurtured at grassroots levels in STEM and Robotics and the ARM E3NGAGE Embedded Learning Challenge to equip the next generation of embedded engineers and incubate entrepreneurship. Most importantly TinyML is open to all regardless of background whether you are a developer, academic, maker, AI expert or just someone who is curious and wants to find a way into AI as a career path don’t know where to start all are welcome all to join the movement and the Meetup Group in your area or the ARM E3NGAGE Embedded Learning Challenge. We hope to see you there

To learn more thecortexhub.africa/arm-http://www.tinyml.org/visit:orhttps://www.learning-challenge

113RD QUARTER 2022 | SYNAPSE COMMUNITY NEWS bottom line but helps identify and reduce and prevent process bottlenecks proactively in a sustainable way that also protects energy resources.Itdoesn’t stop with the technology itself, tinyML is driven and supported by the TinyML Foundation and its partner hardware and software vendors who are all working together with a common purpose of changing the world of AI and bringing true intelligence to every kind of device around you while also empowering you to be able to do it yourself. For the first time in history big tech and industry are working together with the community and end users from school learners and hobbyists to professionals alike to create and nurture new opportunities.

Tiny machine learning (tinyML) is broadly defined as a fast growing field of machine devices.targetingalways-onenablingandtypicallyextremelyetc.)audio,on-devicecapablealgorithmsintegratedhardwareapplicationstechnologieslearningandincluding(dedicatedcircuits),andsoftwareofperformingsensor(vision,IMU,biomedical,dataanalyticsatlowpower,inthemWrangebelow,andhenceavarietyofuse-casesandbatteryoperated ntelligent edge devices with rich sensors (e.g., billions of mobile phones and IoT devices) have been ubiquitous in our daily lives. Combining artificial intelligence (AI) and these edge devices, there are vast real-world applications such as smart home, smart retail, autonomous driving, and so on. However, the state-of-the-art deep learning AI systems typically require tremendous resources (e.g., large labeled dataset, many computational resources, many AI experts), both for training and inference. This hinders the application of these powerful deep learning AI systems on edge devices. The TinyML project aims to improve the efficiency of deep learning AI systems by requiring less computation, fewer engineers, and less data, to facilitate the giant market of edge AI and AIoT.

Learn more The tinyML community continues to grow through the multiple high quality events – in-person and online – throughout the year including tinyML Summit, tinyML EMEA, tinyML Asia, tinyML Talks, and tinyML Meetups.

COMMUNITY NEWS

tinyML Foundation The inaugural tinyML Summit in March 2019 showed very strong interest from the community with active participation of senior experts from 90 companies. It revealed that: (i) tiny machine learning capable hardware is becoming “good enough” for many commercial applications and new architectures (e.g. in-memory compute) are on the horizon; (ii) significant progress on algorithms, networks and models down to 100kB and below; and (iii) initial low power applications in the vision and audio space. There is growing momentum demonstrated by technical progress and ecosystem development. About tinyML for Good Technological advancements are transforming the way we live, work, and connect with the world around us. Tiny machine learning and artificial intelligence are enabling on-device sensor data analytics at extremely low power and with privacy built in by design, already showing great potential to make positive contributions to the United Nations Sustainable Development Goals, particularly in low-resource settings.

tinyML at AI Expo Africa 2022 Peter Ing is the Co-Organizer & Lead for TinyML South Africa and ambassador at Edge Impulse will be speaking at AI Expo Africa 2022 about the tinyML movement. He will be hosting a tinyML Foundation booth in the expo hall showcasing the work by the tinyML Foundation. So drop by and get involved in this exciting field of engineering and applications.

AI EXPO AFRICA WELCOMES TINYML FOUNDATION AS COMMUNITY PARTNER / Read original article here / I

Read more here: www.tinyml.org/about/https://

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akar, Senegal – An experts consultative meeting on developing a continental strategy for Artificial Intelligence (AI) in Africa has been successfully held in Dakar, Senegal, from the 10th – 13th of May 2022. This was held on the margins of the 6th Calestous Juma Executive Dialogue (CJED), organised by the African Union High-Level Panel on Emerging Technologies (APET).

The strategy can help African countries comprehensively develop AI-related technology products and services within various economic sectors and also model how African countries could improve data security and safeguard the technology through enabling regulatory frameworks.

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THE STRATEGYCONTINENTALINTELLIGENCEUNIONAFRICANARTIFICIALFORAFRICA

The strategy can enable stakeholder engagements, enhance capacity building, and strengthen the regulatory environment in AI technology and data management. Such enabling policies can address the existing and systematic implementation challenges faced by African AI innovators. ACCS would also guide the generation of knowledge products towards addressing myths and misconceptions around AI adoption in Africa, as well as enhance provision of technical advice on the technology in AU Member States. The strategy should be developed in consultation with continental AI experts and stakeholders. Its development process would include integrating existing National AI strategies and consolidating their best practices for continental benefit.

A key activity during the meeting was for the experts to engage with policy and decision-makers, including Permanent Secretaries and Director Generals of the Ministries of Science and Technology and Education in the 15 Member States in West Africa, meeting for the 6th Calestous Juma Executive Dialogue (CJED). The experts made a presentation on "addressing the myths, challenges, and benefits of Artificial Intelligence (AI) in Africa", after which there was a Q&A session with the policy and decision-makers.Theexpertsaddressed myths about AI, emphasising that due to the influence of movies, AI is often misconstrued as "the rising of robots" to take over the world. Experts discussed use cases for the technology on the continent, speaking to their personal experiences in utilising AI for health, agriculture, and education, among others. During deliberation, African countries were encouraged to invest in human capital, which should be undertaken early enough in the curriculum to improve AI literacy across all youth and economic sectors. In addition, African countries were challenged to establish continental, regional, and national institutes and innovation ecosystems on AI that will be responsible for coordinating AI-related technology development. African countries can also improve and secure data protection and increase awareness of the importance of data management. To this end, African countries can build innovation infrastructure and review policy implementation frameworks governing AI. The experts also encouraged African countries to consolidate outputs of stakeholder engagements and address country-specific barriers to AI technology to enable youth to innovate. For example, African countries can deliberately support and promote African AI innovation companies to be global players. This can be accomplished by supporting local companies instead of importing AI technologies. Furthermore, African countries can set milestones to fast track the harnessing efforts of AI technology in Africa. For example, countries can target 50% of their youth to be familiar with AI technology by 2030. This can be accomplished through deliberate investments in research, development, and innovation and by establishing continental, regional, and national AI institutes across the African continent.Theexperts developed a draft outline for the strategy, outlining 5 key pillars. Following this consultation, an extended group of experts will be meeting to kickstart the drafting of the strategy with the support of APET. It is anticipated that stakeholder engagements to support the drafting, reviewing, and finalisation of the strategy will be held till the end of 2022, after which it shall be launched in the first quarter of 2023.

AFRICAN UNION NEWS D

For more pleaseinformation,contact: Justina Dugbazah Senior Programme Officer for Education and Social Development Coordinator, APET-CJED African Union Development Agency Email:(AUDA-NEPAD)justinad@nepad.org

AI experts at the meeting recommended that APET establishes a continental repository and networking platform for AI experts. The experts further challenged African countries to create an enabling environment for market-based AI policies and allow compliance with regulatory processes of the technologies. They encouraged the consumption and utilisation of locally generated African AI products instead of the continued reliance on imported AI products.

The CJED convenes policy and decision makers, executives, youth, and relevant stakeholders to deliberate on harnessing appropriate innovations and emerging technologies for Africa’s socio-economic development.

The meeting further stated that development of Policies and regulatory frameworks to improve data transparency, data sharing, and collaboration in AI-related economic activities should be encouraged and formulated in Africa.

APET has prioritised and recommended AI as an emerging technology worth harnessing for Africa's socio-economic development. In the APET "AI for Africa" report to be launched in December 2022, the panel provides guidelines for African countries on how best to exploit AI-based technologies for the continent’s advancement. The high-level panel further recommended developing a continental Artificial Intelligence strategy for Africa, necessitating this expert consultative meeting.Inhis opening remarks, a member of APET and lead on Artificial Intelligence, Dr William Wasswa, noted that AI is a pathfinder technology and valuable tool for economic development that cuts across economic sectors. As a continental expert who is revolutionising health service delivery using AI, Dr Wasswa noted that a comprehensive AU-AI Continental Strategy (AACS) would enable African countries to enhance policymaking and implementation and improve stakeholder engagements on AI-related challenges and opportunities.

14 SYNAPSE | 3RD QUARTER 2022 After two years of digital events, the 5th edition of AI Expo Africa will be returning in 2022 to a brand new home, that of Johannesburg, South Africa. The Gauteng and Tshwane Regions of South Africa are home to the largest concentration of new and emerging 4IR tech companies dubbed the “AI Tech Capital of Africa” allied to a strong demand for vendor solutions, jobs and skills in this category. Its also a great opportunity to explore “The City of Gold” and the Administrative Capital of South Africa. The AI Expo Africa community is excited about the much awaited return to face to face events in 2022 and we hope you can join us for our largest event so far. 2022 Delegate Tickets Sign up TODAY before March 2022 to secure your super early bird ticket and a 50% discount off full access tickets for the show. Click here to register 2022 Exhibitor Consultations Want to reach the largest buyer and partner community focused on acquiring AI, RPA & Smart Technology solutions? Discuss your needs & find a package to suit your sales & marketing goals TODAY Click here to request a 1-2-1 meeting JOIN US IN JOHANNESBURG IN 2022 AI EXPO AFRICA 2022

You

There are 9 core value propositions for sponsors & exhibitors, namely;

153RD QUARTER 2022 | SYNAPSE Pre-show Build early brand momentum, awareness & press coverage months before show day Leads Generate new business opportunities with qualified buyers seeking solutions Learn Gain valuable insights about the regional trends, needs & wider African 4IR landscape Promote Promote products, services & programmes to a curated audience of buyer centric delegates Network Network with thought leaders, buyers, Governments, trade missions & start-ups Coverage Reach 30K+ practitioners via our regional mailer, magazine, social & video ecosystem Analytics Obtain detailed insights via our buyer survey plus opt-in delegate list & show analytics Build Develop your African channel, deployment & distribution partner network with local ISVs Post show Leverage our network, with newsletter, trade magazine & bespoke services 365 all year We connect you to decision makers, innovators & thought leaders via the largest event of its kind in Africa After the amazing success of 4 editions of AI Expo Africa, we are proud to announce our 2022 event will be staged in Johannesburg on the 19th and 20th September with a VIP opening event on the evening of 18th September.

AI Expo Africa welcomes sponsors and vendors from all corners of the 4IR smart technology community and we have a range of sponsorship packages to suit all budgets for vendors, platform providers, service providers, deployment partners, start ups and niche community / skills partners alike. will enjoy a packed two-day programme allied to a unique exhibition area affording delegates, exhibitors and sponsors learning and networking opportunities.

AI EXPO AFRICA 2022

16 SYNAPSE | 3RD QUARTER 2022 Ratings & Reviews* % of respondents rating the show as EXCELLENT or GOOD Event Admin TICKETING PAYMENTS& 94% QUALITY PROGRAMMEOF 91% INFORMATIONWEBSITE 91% AI MEDIA STAFF 91% Event Content EXPERIENCEOVERALL 83% QUALITY & MIX OF VENDORS 87% PROGRAMME QUALITY & MIX OF TALKS 92% QUALITY & MIX OF SPEAKERS 95% WILL YOU ENJOY US AT AI EXPO AFRICA 2022? 92% DID WE MEET EXPECTATIONS?YOUR Event Value DELEGATE / SPEAKER 83% DID YOU ENJOY YOURSELF AND LEARN SOMETHING NEW? 94% 93% Event Site Traffic per year Practitioner Mailer Reach Expo Hall Space (Sq Feet) Registered Delegates LinkedIn Trade Group SpeakersCompanies& Sponsors Countries Represented Key Numbers at a Glance* Delegate diversity 34%66% 3,000,000+ 20,000 10,000 5,410 9,594 1,420 133 91 *from AI Expo Africa 2021 Customer Reviews AI Expo Africa Energy Ln, Century City, Cape Town 4,9 73 reviews Decision Maker & Buyer Community Seniority & Status Decision Maker / Budget Holder / Purchasing Analyst / Influencer End User / Employee Other 31% 30% 17% 22% CxO, VP, Director, Manager ContractorEngineerFounder / Employee OtherStudent 31% 13%11% 25% 13% 7% AI EXPO AFRICA 2022 AI EXPO AFRICA SHOW STATS 2021 TM

173RD QUARTER 2022 | SYNAPSE AI EXPO AFRICA 2022 TESTIMONIALS & VENDORS VENDOR SNAPSHOT FROM 2021 “Enjoying this talk great content and like the advocating for Africa” ZINDI UK “Incredible talk thanks for the amazing experience you and your team have done a great Job” INSPIRED TESTING, SA “Love the Intel initiatives” CAPITEC BANK, SA “Congratulations on the success of the AI Expo Africa! The work you and your team put in was quite evident” UNPACK AI, CHINA “I am inspired by how the Kenyan government is embracing tech specifically Artificial Intelligence” AMATHUBA AI, SA “Am glad I attended the AI Expo Africa and NVIDIA really delivered  a well insightful presentation which was of profound assistance to me” BIMO TECH, SA “Great Telkom presentation” DELEGATE “Congratulations on another great show for 2021” DEPT OF COMMERCE, INTERNATIONAL TRADE ADMINISTRATION, USA 2021 TM

193RD QUARTER 2022 | SYNAPSE PREDICTIVE INSIGHTS

Usually when we think about predictions we think about ‘big calls’, like flying cars, rather than the myriad of small predictions that businesses need to make on a day-today basis. These small predictions can be for things like “How many people will visit a specific outlet at a specific?”, “What will they consider buying?”, and “How many of the scheduled staff will be absent for a specific shift?”. Improving predictions of these ‘smaller’, but essential, processes can lead to more certainty and better consistency in decision making, adding up to a more effective and profitable business. Currently, most glances into the future are based on ‘rules of thumb’, backward looking calculations and extrapolations of current trends, or gut feel. Using these types of approaches to make forecasts introduce a set of avoidable errors. Humans are plagued by behavioural biases, including a recency bias where we overvalue things that have happened recently, and a tendency to see patterns where there are none. People struggle to process large amounts of information, and to identify vague but consistent patterns. Predictions and extrapolations which only look backwards can also miss changing economic and social conditions, particularly in cases like the past three years with the Covid-pandemic. These forecast errors filter through to the whole business. Having a bad forecast for your business is like having a bad map – you’ll

Making forecasts for things like revenue, more than three months into the future, can be difficult, but forecasts at this time horizon are often essential for things like budgeting, stock ordering and strategic planning.

Long-term forecast accuracy

USING AI AND ECONOMICS TO PLAN FOR THE FUTURE

Niels Bohr, the Nobel Prize-winning physicist, allegedly said, “Prediction is very difficult, especially about the future.” What makes forecasting the future particularly difficult is that outcomes are a combination of a number of factors that may combine in complex ways. These include economic trends, consumer behaviour, and random chance; how these impact a specific business, product, customer, or location; but also the beliefs and prejudices of, and the information available to, the person making the predictions.

Longer-term forecast methodologies have been developed and used by institutions like Central Banks to make forecasts for inflation and GDP but these approaches are underutilised by businesses. Over the past year, Predictive Insights has worked on adapting these long-term forecasting approaches to business and budget forecasting. Combining curated real-time data on the economy, with machine learning and behavioural insights can enable restaurants and retailers to more accurately predict demand up to 18 months ahead.Neil Rankin, CEO at Predictive Insights, said: “Businesses often base forecasts on activity from the same week or period of the previous year. Due to Covid, behavioural changes and other disruptions, this historic data is dirty. Forecasts based only on this data are even more inaccurate now.”

The team of economists and data scientists at Predictive Insights use a combination of data points to improve the accuracy of forecasting including real-time data, transactional data and relevant external data. Through the Predictive Insights machine learning platform, customers are provided with actionable insights for strategic planning, budgeting, demand forecasts, staffing, stock optimisation, lead scoring, promotions, pricing and behavioural nudges.

Over the last year Predictive Insights has implemented this medium-to-long term Demand Forecasting solution at multipleoutlet stores, which often sell through multiple channels, in the United Kingdom, South Africa, Botswana, United Arab Emirates, and Australia. This approach has led to an improvement in branch managers’ predictions by up to 30 percent for forecasts up to 18 months ahead. These longer-term forecasts can be combined with Predictive Insights shortterm Demand Forecasting solution (providing hourly, daily and weekly forecasts up to eight weeks in advance) which can be used to drive operational aspects like staff scheduling or stock ordering, which also dramatically increase operational efficiency.

end up getting lost and wasting time and energy going the wrong way. There is thus a large opportunity for ‘machine-assisted’ approaches to forecasting the future.

Allow the machines to do the heavy lifting Neil commented on the added benefits: “In addition to improving accuracy, a big bonus for our customers is that machines are doing the heavy lifting. Where data gathering and analysis can be a full-time job, machine learning can help to provide analysts with a baseline for review. This takes the tedious work away, allowing people to add additional insights and do so much more with their data.”

The use of Artificial Intelligence forms a core part of Telkom’s commitment to technological advancement and digital transformation.

Visit www.izwe.ai for more information.

ADVANCING YOUR WORLD PRODUCT LAUNCH

Our technologies can help close the inequality gaps in South Africa, including the education system.

In September izwe.ai was launched. It is an AI platform developed by Telkom, in collaboration with Enlabeler, which transcribes and translates speech into text from English and local languages. izwe.ai aims to deliver local-language transcription and translation that gives all learners equal access to learning material. This will also have a far-reaching impact on the health and business sectors, allowing for academic and legal transcription; contact centre transcription and analysis; and media production services.

213RD QUARTER 2022 | SYNAPSE DIGITAL TRANSFORMATION IS COMPLEX, IT DOESN’T HAVE TO BE COMPLICATED. FROM THE INNOVATORS BEHIND BCX WE BRING YOU OUR NEW DIGITAL WING SIMPLY NAVIGATING THE COMPLEX Our most important customer is yours. Scan the QR code for information.more

22 SYNAPSE | 3RD QUARTER 2022 LAUNCHING MAY 2022 State of AI in Africa 2022 REPORT Analysis of the 4IR in Africa –A Foundation for Growth Report Commissioned by the AI Media Group CLICK HERE to grab your FREE copy TODAY with promo 'SOAIR100'code

A key finding was just how cross cutting this technology is. South Africa, Nigeria, Egypt & Kenya dominate this sector with AI impacting at least 120+ separate market segments across Africa,” said Dr. Bradshaw ”

INDUSTRY ANALYSIS

segment  Company size Vs Year founded STATE OF AI IN AFRICA REPORT –GLOBAL LAUNCH WITH WEF GLOBAL SHAPERS & UN ITU  Investment landscape 

 Africa by numbers  Notable communities  Company type Vs

As the report findings show, a “positive sign that this technology and its attendant start-up ecosystems can win big across Africa if these trends continue.”

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“A key finding was just how cross cutting this technology is. South Africa, Nigeria, Egypt & Kenya dominate this sector with AI impacting at least 120+ separate market segments across Africa,” said Dr. Bradshaw report author and CEO of the AI Media Group.

AI’s development in Africa is attracting huge amounts of resources and funds, with Tunisian AI start-up InstaDeep “receiving $100m USD funding earlier in 2022. The global market is also projected to grow from $387 Bn USD in 2022 to $1,394 Bn by 2029, exhibiting a CAGR of 20%.”

 Foreward  Introduction  At a glance summary  The

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According to the report there are now over 30 AI / Deep Tech communities in the Africa region providing a range of services and attracting “wannabe learners, entrepreneurs and job seekers allied to a growing range of vendor based programmes supporting the creation of AI / Deep Tech solutions.”

The new State of AI in Africa Report created by the AI Media Group from South Africa, offers an analytical insight into the growing Artificial Intelligence (AI) sector in Africa, a topic that has not been fully explored up until now. The unique report contains statistics and trends, offering an in-depth look at key factors and communities driving the ecosystem across the continent. It will be launched globally online by AI Media in partnership with WEF Global Shapers & UN ITU. Africa is currently at a massive turning point and supporting AI makes the region ripe with opportunity for a better future. Launched June 14th 2022 at the Council for Scientific and Industrial Research (CSIR) and WEF C4IR in Pretoria, South Africa, this 32-page report is crucial for anyone who is looking for a richer understanding about the dynamics of this rapidly growing frontier tech market. & headings included in the report are as follows; global view Industry Who is trading in Africa “TheConclusionsStateofAI in Africa Report, provides the driver, catalyst, and inspiration for “Africa Now” as the hub for global opportunity” said Stephen Ibaraki (Canada), Chair & Managing General Partner REDDS Capital, Founder & Chair Outreach UN ITU #AI4Good, in the report’s foreward.

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tarted in 2019, Enlabeler is a data labeling provider that offers highquality data services, including data classification, annotation and data labeling for businesses globally. Enlabeler is taking aim at the local youth unemployment crisis by providing contract-based employment and growth opportunities for young unemployed people in South Africa and Kenya.

START-UP HIGHLIGHT

Kingson Capital’s Gladwyn Leeuw says, “With Enlabeler, we see the beginning of a future where technology creates widespread employment opportunities on the African continent. We hope to shatter the perception of technology as a force that adversely affects job creation or ‘replaces’ human elements. Rather, technology has the potential to create a whole new generation of African tech professionals, leveraging innovation to grow the continent’s economic footprint and boost every individual’s earning potential in the long-term.”

The spark of inspiration behind Enlabeler was ignited when Founder and CEO (Chief Executive Officer) Esther Hoogstad wrote a research paper on how the SA tech sector could help create digitally enabled micro-jobs for the underutilised youth demographic. In the process, Hoogstad met two enthusiastic entrepreneurs, Pieter Boon and Koen Bonenkamp, in the AI and Data Science industry, which led to the official birth of Enlabeler.Thecurrent leadership team with Ridha Moosa and Pieter van der Merwe – among others – has grown to become a team of domain experts in this field, with both data science and DevOps experience. They are accelerating their innovative footprint to support the labelers with strong tech and operationalHoogstadprocesses.expandson the company’s inception: “The global market for AI applications has grown by a CAGR of 38% and is projected to surpass around 1,59 USD billion by 2030. The global data labelling market alone is expected to increase to USD 8.2 billion by 2028. We noticed that worldwide, data scientists and machine learning engineers need high-quality datasets to train and inform their working models. This trend is only recently gaining momentum in South“AcceleratedAfrica. by COVID-19 and the corresponding lockdown, many companies have been digitising and automating their business processes using ML (Machine Learning). As Enlabeler started working completely remotely during lockdown, we had to develop a robust tech foundation to service clients globally. At the same time, the team had to be inventive in recruiting, selecting and training labellers using online tools. This is now being supported by our permanent team of reviewers and project managers based all over South Africa and Kenya.” For the layperson, Enlabeler’s services incorporate image and video annotation – or labelling video frames and images to inform ML models and algorithms. ML is a crucial component in AI applications and requires large volumes of trained and untrained datasets that need to be “labelled” by humans to “teach” the machines. The company’s other services include speech and audio transcriptions; translations of video and audio content to local languages to increase market reach; text classification, and sentiment analysis. All of which give Enlabeler a distinct advantage over global competitors.KingsonCapital’s Ross Jenvey says, “We see many pitch decks from various tech start-ups, but Enlabeler stood out for its multi-pronged potential. That is, the company has a selection of highly-innovative services with vast commercial possibilities; plus, it offers immense scope for employment growth in the most underserviced local population group – young, often unskilled or unqualified job seekers.”

South African tech startup Enlabeler has closed its funding round with venture capital firms Kingson Capital and E4E Africa, as well as the Michael & Susan Dell Foundation.

“To create earning opportunities that South Africans from low-income households need to support themselves and their families, the Michael & Susan Dell Foundation invests in organizations that provide training for placement in in-demand jobs or connections to livelihood earning opportunities at scale. This new funding partnership allows Enlabeler to expand on its ability to provide training and enabling infrastructure to more labellers throughout the country, removing the barriers to earning faced by many,” says Ona Meyer, program manager, youth employment, the Michael & Susan Dell Foundation.

STARTUP AIMS TO GROW

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DATAFOOTPRINTAFRICA’SINAIANDLABELLING original article

PROUDLY SPONSORING AI EXPO AFRICA 2022 INSTADEEP IS COMMITTED TO ENSURE AFRICA SHAPES THE FUTURE OF AI. INSTADEEP.COM

“It is therefore important to understand that our emphasis as a department is in the highpriority skills areas. Critical skills and skills in high-demand are important to us.”

“Technology has never been more important for humanity and is driving the need for more computing and uspkilling.”

“The rest of those students are registered in courses and programmes that – even after they graduate – they’re going to join the long queue of unemployment.

“The Intel TVET AI programme has been rolled out across the entire globe – it is also in the US, the UK and India, but it is the first initiative in Africa, at a South African TVET college.“Itsstate-of-the art AI training centre was also set up and this was completely funded by Intel.“Already, Intel has trained 12 trainers (at an international standard), trained by Intel officials and facilitators from all over the world. From the 12, two have already been poached by industry.”Todate, more than 300 students – those in their final-year of their TVET programmes –have already been trained, Balkrishen revealed.

26 SYNAPSE | 3RD QUARTER 2022

“Participants will gain practical skills – we are talking about programming and coding, algorithm and computational thinking, social skills, AI ethics, critical thinking, problemsolving, systems mapping and solution building.”Higher education and training directorgeneral Dr Nkosinathi Sishi commented that 1.1 million students are in the country’s postschoolHowever,sector.the department is concerned that only 126 000 are registered in areas or courses that are of scarce skills, he stated.

From left: Higher education DG Dr Nkosinathi Sishi; Intel VP Maurits Tichelman; and Dika Mokoena, principal at Orbit. (Photo by Lesley Moyo) The Intel AI laboratory opened at Orbit TVET College. (Photo by Lesley Moyo)

Campus.Thelaunch

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Dr Nkosinathi Sishi, higher education and training DG, and Maurits Tichelman, Intel VP sales and marketing and GM for EMEA territories. (Photo by Lesley Moyo)

esterday, the global chipmaker officially launched its AI for Future Workforce programme at Orbit TVET College, Brits event, which was a collaborative effort between Intel, Orbit and the Department of Higher Education and Training (DHET), also saw the opening of a new AI laboratory at the institution.Speaking at the launch event, Maurits Tichelman, Intel VP of sales and marketing and GM for EMEA territories, stated Intel is honoured to contribute to the development of AI skills at Orbit TVET College. “The launch of this programme is the first one in South Africa, and also the first one on the continent, and we look forward to extending the AI for Future Workforce programme to all other colleges.“Starting here [at Orbit] presents great potential to go to all colleges in South Africa and spread across the continent.”

“It’s an appetiser AI course, providing a broad overview of what artificial intelligence is. Obviously, there are various other steps of the training programme and we feel this will empower them [students] greatly. If they are interested in AI and have an eye for AI, then they will take all the other steps in the training programme that are being offered.

“As a region, we want to extend this programme to the six TVET colleges in the region. It’s starting out at Orbit, but we want to extend it to the other five – we want all of our colleges and all of our students to benefit.”

INTEL TAPS NORTH WEST TVET COLLEGE TO SPARK AI APPETITE / Read original article here /

North West technical and vocational education and training (TVET) institution Orbit TVET College is the first on African soil to roll out Intel’s artificial intelligence (AI) training programme.

Detailing the programme’s origins, Dr Nick Balkrishen, regional manager for TVET and CET colleges in North West and Mpumalanga, said he had two colleges in mind that would kickstart it, but it was Orbit TVET College that was eager to run with it.

SOUTH AFRICA NEWS

The AI for Future Workforce initiative has already been rolled out in other parts of the world and forms part of the Intel Digital ReadinessTargetedprogrammesatvocational college students, it aims to empower them with critically-needed job skills in the field of AI, with courses on data collection, computer vision, AI model training, coding, societal impacts, ethics of AI technology and more. Students who successfully finish the courses will get a certificate of completion, according to TichelmanIntel.said through the programme, South Africa can start training the next generation of future technologists and innovators, who will contribute to president Cyril Ramaphosa's fourth industrial revolution mandate.

Tichelman added: “We want to make sure we equip the future workforce with the technical confidence to learn and apply these AI skills.

enture capital firm Knife Capital led the round, joined by South Africa’s International Development Corporation (IDC) and Norican – a metal surface preparation and finishing equipment provider. The funding provides DataProphet with the capital to invest in its industrial AI product set, while facilitating targeted growth in selected geographies and manufacturing verticals.KnifeCapital initially invested in DataProphet in early 2018 via its KNF Ventures Section 12J funding vehicle. This latest round is the first investment made by Knife Fund III, the newly-launched fund supporting the international ambitions of African Foundedscale-ups.in2014in Cape Town, DataProphet enables manufacturers to step towards autonomous manufacturing through its AI-as-a-service offerings, which include the DataProphet Prescribe platform, which helps manufacturers to continuously optimise production without the human analysis typically required. In 2020, the start-up company also received $6 million funding from Knife Capital, IDC and Norican. This, after the company had established a partnership with Norican aimed at accelerating the adoption of AI in the foundry industry“Accelerating the international expansion of DataProphet, given the leading nature of its technology, is exactly the mandate of our new fund – and it couldn’t be more fitting for our first investment to be a follow-on investment from our existing cohort,” comments Keet van Zyl, co-founder and partner at Knife Capital. Andrea Böhmert, partner at Knife Capital and executive chairperson of DataProphet, and Frans Cronje, CEO of DataProphet.

“I am excited about the continued support DataProphet has received from Knife Capital,” says Frans Cronje, CEO of DataProphet.“Goingforward, we will use this additional funding to continue to accelerate and expand into new markets, build new relationships that are aligned with our machine builder strategy, and further our global expansion.

Andrea Böhmert, partner at Knife Capital and executive chairperson of DataProphet, says: “It is fantastic that the launch of Knife Capital’s Fund III allows us to continue supporting DataProphet in its journey to become the leading provider of impactful AI solutions for the manufacturing industry

“The optimisation of manufacturing performance in the context of smart manufacturing is still in the early adoption cycle. The DataProphet team is world-class, as validated by the third-party recognition it receives, and as such, it is perfectly positioned to further entrench its leadership position in this fast-growing sector.”

INVESTMENT NEWS

28 SYNAPSE | 3RD QUARTER 2022 AI DATAPROPHETSTART-UP RAISES R166M FUNDING / Read original article here /

DataProphet says it has tripled its team since Knife Capital’s initial investment, and has successfully built a recognised brand in the advanced manufacturing analytics market.Itscustomer base has now expanded to the Americas, Europe and Asia. With this funding behind it, the company says growth will be further accelerated.

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Another important pillar is bringing in top talent to build on this momentum.”

Knife Capital’s Fund III is still open for investment and is backed by the International Finance Corporation, Mineworkers Investment Company, SA SME Fund and select family offices, and other credible financial institutions, says the companyItexplains that DataProphet positions industrials to evolve towards autonomous, energy-efficient production, optimising manufacturing performance.

SeriesmillioncompletedDataProphet(AI)artificialTown-foundedintelligencestart-uphasits$10(R166million)Afundinground.

Justin Larsen, CFO of DataProphet, elaborates: “Leading up to the finalising of this funding round, we’ve made great strides in our product development and gained additional momentum with our existing and new clients. We’ve also won several industry awards, acknowledging the progress that we’re making. These are strong indicators that the business is headed in the right direction.”

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Our quick turnaround means you keep improving with the smartest minds in data science on your team. Partner with Africa's leading data science platform to access the power of 45 000 data scientists for your business. Through our partnership program, organisations can tap into this pool of talent, access machine learning and AI solutions, and stay at the forefront of innovation. C o n t a c t u s n o w f o r a f r e e c o n s u l t a t i o n w w w z i n d i a f r i c a t a m @ z i n d i . a f r i c a + 4 4 7 5 2 2 1 2 0 0 7 7 GET IN TOUCH R e a c h o u t n o w f o r a 2 0 % d i s c o u n t f o r a l l A I E x p o d e l e g a t e s

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Zindi, a South African startup that operates as a

Read original article here / he funding round was led by the San Francisco-based Shakti VC, with participation from other investors including Launch Africa Ventures, Founders Factory Africa, and five35 Capital Partners. With the belief that data science should be accessible to everyone, Zindi was founded in 2018 by Celina Lee, Megan Yates, and Ekow Duker. Today, the company hosts a community of over 34,000 data scientists

earlyrapidafteritfundingascientists,networkprofessionalofdatahasraisedUS$1millionseedroundtohelpcontinuetogrowexperiencinggrowthinitsstages.

“We are an African platform with a global reach that has African roots.” So far, our primary focus has been on expanding our presence in the African market. For every data scientist and aspiring data scientist on the continent, we will be the go-to platform to which they can turn. According to Lee, “If we can get it right in Africa at scale, if we can create a world where companies, data sets, and talent are seamlessly connecting on the Zindi platform to create new exciting value, it is entirely possible that we will be able to replicate this model in other emerging market contexts where many of the opportunities and challenges are similar,”

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“ We are an African platform with a global reach that has African roots.” So far, our primary focus has been on expanding our presence in the African market. ”

who are tackling some of the world’s most pressing business and social challenges with machine learning and artificial intelligence.

“This means that all companies will be able to unlock the power of their data; people will be able to pursue careers in data science regardless of race, gender, or geography; and artificial intelligence solutions will be designed in a way that will positively impact the everyday lives of people all over the world,” Lee explained.

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While Zindi charges companies to post challenges, it crowdsources machine learning solutions for those challenges. Here, Zindi steps in to fill the void by making data science and artificial intelligence (AI) more widely available.

ZINDI RAISES US$1 MILLION IN A SEED ROUN D to expand its network of data scientists

INVESTMENT NEWS

E ARM LAUNCHES

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CORTEX LAB IN SOUTH AFRICA

technologies.andcomputing,intelligence,emphasisRevolutionintowardsregionsstrategiesForward-lookingandeconomiestakingfar-reachingdecadeweimpactwillDigitaldeveloperstartupsecosystems,technologycatalyzeandengagecommunities.technologieshaveaprofoundonthewayliveinthecomingwiththemostchangesintheemerginginAfricaLatinAmerica.acrossthesearegearedparticipationtheFourthIndustrialwithanonartificialcloudrobotics,advancedwireless

Arm is launching the Arm (E3) NGAGE lab To support digitization initiatives across emerging economies, Arm is launching the Arm (E3)NGAGE lab focused on engaging, educating, and cultivating local technology ecosystems while making Arm a central pillar of the computing ecosystems across these regions. Programs and initiatives will also seek to catalyze startups and developer communities in the region. The pilot (E3)NGAGE lab is being launched in partnership with the Cortex Hub, a regional technology incubator located in East London, Eastern Cape, South Africa, Africa’s automotive capital. Other participants include the National Integrated, Cyberinfrastructure System of South Africa, the Council for Scientific and Industrial Research, and numerous Arm hardware and software partners. The lessons learned here will then serve as a blueprint for opening centers elsewhere in Latin America and Africa.

The (E3)NGAGE Lab will bring people in emerging economies together to cultivate local

Read original article here / stablishing a thriving digital ecosystem, however, remains a work in progress: existing grids and communication networks are often stressed. Rural communities often remain digitally isolated. Even in established business corridors, adoption of the latest technology can lag: Africa accounts for less than 1 percent of the cloud services markets, according to Xalam Analytics. Just as importantly, we need to close the knowledge gap.

PARTNERSHIP NEWS

 Bare Metal as a Service Lab. Arm will leverage the infrastructure support activities of the Cortex Hub Bare Metal as a Service Lab to demonstrate and promote proof-of-concept set ups for our Infrastructure line of business and support local versions of innovative projects like the Mini Nodes project.

 Electronics Hardware Lab. Arm will support the current activities of the Cortex Hub Electronics Hardware lab by providing workshops, demos, and ecosystem training events that leverage Arm based tools and resources. The Electronics Hardware Lab will also provide opportunities for ecosystem partners like Arduino, Edge Impulse and Spark Fun to interact with developers and startups.

 Automotive Lab. Arm-led initiatives like Autoware and research-focused development activities will seek to catalyze regional automotive/IoT led innovations built on Arm. The lab is also equipped to support projects and demos to highlight local V2X, telematics and location-based services.

Within the Cortex Hub, some of the targeted projects and services include:

The long-term impact of the (E3)NGAGE lab model across targeted ecosystems includes an increase in the awareness and prominence of Arm’s technologies, capacity, and ecosystem capabilities.

 The (E3)NGAGE Learning Challenge, the lab will expand ecosystem awareness of Arm based MCUs and encourage the development of local solutions. We will also encourage startups and prepare training platforms to familiarize developers with Arm tools, resources, and libraries such as Keil MDK Community Edition and Mobile Studio.

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 Sustainability. The lab will also spotlight Arm led sustainability programs and partnerships, while building local stakeholder networks that are developing needed solutions that address regional problems.

 Robotics Lab. Leveraging our relationship with Microbit and the first African Arduino Inspiration Lab, the Build With Arm program will focus on K-12 Learners in South Africa using the training and curriculum resources of the Arm School Program and Arm Education.

Cost, Culture and Channel Strategy

Channel strategy can be another differentiator. Just as cellular carriers used “free” phones to gain traction in the U.S., innovative channel ideas such as bundling solar and smartphone subscriptions or no-interest layaway plans have become vehicles for reducing transactionMeanwhile,costs.others are building products to better navigate existing circumstances. Cape Town’s MediaBox is developing an inexpensive portable set-top box that lets consumers take and view content wherever. In countries where bandwidth is often constrained, it changes the TV experience.

The pilot (E3)NGAGE lab is being launched in partnership with the Cortex Hub, a regional technology incubator located in East London, Eastern Cape, South Africa, Africa’s automotive capital. ”

An export opportunity Creating a path from concept to commercial deployment for digital technologies in these regions is one of the largest economic opportunities of our time. GSMA estimates that mobile technologies alone could generate $155 billion in economic value by 2025. East London’s expertise in auto technology, combined with the chronic traffic problems of cities like Lagos, makes it a potential hub for the development of V2X technologies for improving safety and traffic management. One could also imagine Latin America and Africa becoming test beds for using mid-band 5G for fixed wireless access as existing incumbent technologies aren’t as pervasive or edge technologies.Forgingthis path is also a moral imperative. In these regions, technology can make a difference for the better. For both reasons, Arm will be there.

What makes a product for Africa or Latin America different than those developed for North America or Japan? Cost is, of course, an inescapable factor. Manufacturers such as Celkon, Karbonn, and Transsion have succeeded by inventing ways to include higher-end features while lowering the price. Some have also shifted manufacturing to Ethiopia and Kenya. UltraLow-Cost smartphones based on our Total Compute processor design philosophies will further help expand the market by lowering the bill of Localizingmaterials.features, however, is equally as important. Take Transsion, the number one smartphone company in Africa through its brands Techno, Itel and Infinix. Some Techno phones support up to four SIM cards, allowing customers to save money and capitalize on variations in coverage strength over different networks. It also leads in offering keyboards in Hausa and other African languages. The company also notes it beat Google in leveraging artificial intelligence (AI) for better photo quality and facial recognition for AfricanSimilarly,faces.carriers are working on ways to upgrade their infrastructures for greater efficiency and greater amounts of traffic. MTN, the South African carrier that provides service across the continent, has already added 1,100 sites built with Open RAN technology to its networks. It is also experimenting with AI to reduce power consumption at its 20,000 plus substations across the continent.

PARTNERSHIP NEWS

DataAnalytics-basedProducts (Solutions) RetentionCustomer SolutionEnterpriseSolutionHiveOpportunities&(CROH)Check ServicesProfessional (Consulting) Data Salesforce&TrainingAnalyticsITResourcing:&DevelopmentApplicationAuditsInformationCybersecurityEnterpriseAdvancedManagementAnalyticsArchitecture&SystemSoftwareEngineering&AdvancedDomainExpertsDevelopmentCRM OfUniverseCrystallizedOfferings South Africa: 1st Floor, Midlands O ce Park West Mount Quray Road Midstream, Johannesburg, RSA, 1692 Tel:info@analyticshive.com+27100210239 United Kingdom: 50 Sheephouse Road SL6Maidenhead8HH,London, United Kingdom Tel:www.analyticshive.com+447903950647 Zimbabwe: Suite 104 Club Chambers Building Corner Nelson Mandela Avenue/3rd Street Harare, Tel:www.analyticshive.comZimbabwe+263717960810 CustomerChurnCombat Customer AnalysisContact-abilityCross-SellOpportunitiesUp-SellOpportunitiesCustomerSentimentDataScienceArtificialIntelligenceGeospatialAnalyticsAuditSupportAnalytics

MICTSETAACCREDITEDSTANDARDOFFERINGS BUSINESSSCHOOL&CORPORATEDIRECTCUSTOMOFFERINGS Deliveringqualityauditsatafractionofthecostbyleveraging dataanalyticsforcontinuouscontrolsmonitoring(CCM) SolutionModules BusinessAnalytics ITEnd-UserComputing, NQFLevel3 Artificial 5Development,Development,IntelligenceCybersecurityITSystemsNQFLevel4ITSystemsNQFLevel5BusinessAnalysisSupportPractice,Level

HowaboutimprovedpersonalizationofservicestoyourB2Bcustomers?

DoyouwanttodevelopinsightsintoanenterprisebeforeadmittingitasaSupplier,Customer,orPartnerto better-assessandmitigatetheriskofdoingbusinesswiththem?

Doyouwanttoknowwhenandthroughwhatchannelstocontactyourcustomers tomaximizereach?

Doyouwantinsightsbeforebuyingstockinalistedentity?

Thecostofacquiringanewcustomerismuchhigherthanthecostofretainingan existingone. Areyouconcernedaboutlosingyourexistingcustomerstoyourcompetitors?

Themulti-moduleCROHSolutionhasgotyoucovered.Ourclientshavereported: upto33%boostinrevenuefromtheirexistingcustomerbase, upto30%reductionincustomerattrition,and upto38%increaseincustomerreach.

Thereiscostattachedtoattemptingtoreachyourcustomersandfailingtoget throughtothemwhenyouwant.

Abirdinhandisworthtwointheforest. Areyouseekingwaystogeneratemorerevenuefromyourexistingcustomer base?

Doyouwanttoknowwhichofyourexistingcustomersarelikelytoleave,and when,tocraftanddriveproactiveretentionstrategies?

TheEnterpriseCheckSolutionempowersandcapacitatesyouwithallthis;andmuchmore. advancedanalyticscraftanddeploy solutions

Leveraging

Areyouseekingdeeperinsightintoyourcompetitors?

intelligentlyautomatedanddigitizedbusiness

to

Are you concerned about losing your existing customers to your competitors?

much more. Leveraging advanced analytics to craft and deploy intelligently automated and digitized business solutions MICT SETA ACCREDITED STANDARD OFFERINGS BUSINESS SCHOOL & CORPORATE DIRECT CUSTOM OFFERINGS Delivering quality audits at a fraction of the cost by leveraging data analytics for continuous controls monitoring (CCM) Solution Modules Business Analytics IT End-User Computing, NQF Level 3 Artificial SupportBusinessNQFITNQFITCybersecurityIntelligenceSystemsDevelopment,Level4SystemsDevelopment,Level5AnalysisPractice,Level5 Analytics-basedDataProducts (Solutions) CustomerRetention CheckOpportunities&Hive(CROH)SolutionEnterpriseSolution ProfessionalServices (Consulting) Data EngineeringArchitectureAnalyticsManagementAdvancedEnterpriseCybersecurity&InformationSystemAuditsApplicationDevelopment&SoftwareResourcing:IT&AdvancedAnalyticsDomainExpertsTraining&DevelopmentSalesforceCRM OfferingsCrystallizedUniverseOf SouthAfrica: 1stFloor,MidlandsOceParkWest MountQurayRoad Midstream,Johannesburg,RSA,1692 info@analyticshive.comTel:+27100210239 UnitedKingdom: 50SheephouseRoad London,MaidenheadSL68HH,UnitedKingdom www.analyticshive.comTel:+447903950647 Zimbabwe: Suite104ClubChambersBuilding CornerNelsonMandelaAvenue/3rdStreet Harare, www.analyticshive.comZimbabweTel:+263717960810

The cost of acquiring a new customer is much higher than the cost of retaining an existing one.

Are you seeking deeper insight into your competitors?

Do you want insights before buying stock in a listed entity?

Do you want to know which of your existing customers are likely to leave, and when, to craft and drive proactive retention strategies?

CustomerUp-SellCross-SellContact-abilityOpportunitiesOpportunitiesSentimentAnalysis DevelopmentManagementAnalyticsArchitecture&SystemEngineeringDomainExpertsCRM Data AuditGeospatialArtificialScienceIntelligenceAnalyticsSupportAnalytics

Do you want to develop insights into an enterprise before admitting it as a Supplier, Customer, or Partner to better-assess and mitigate the risk of doing business with them?

The multi-module CROH Solution has got you covered. Our clients have reported: up to 33% boost in revenue from their existing customer base, up to 30% reduction in customer attrition, and up to 38% increase in customer reach.

How about improved personalization of services to your B2B customers?

There is cost attached to attempting to reach your customers and failing to get through to them when you want.

A bird in hand is worth two in the forest. Are you seeking ways to generate more revenue from your existing customer base?

The Enterprise Check Solution empowers and capacitates you with all this; and

OpportunitiesCheck

Do you want to know when and through what channels to contact your customers to maximize reach?

Customer Churn Combat Customer

UNTAPPED POWER OF ARTIFICIAL INTELLIGENCE IN THE RETAIL INDUSTRY

Ashanti ai, we believe that a lot of money is at stake and agile players can even tap into more investment opportunities. Strategic planning will require the power of big data and artificial intelligence. As a retailer, you are faced with a network of decisions that are often ambiguous and volatile. And it’s upon this background that most decisions are made. The implications are vast and will determine the winners and losers in the market.

INDUSTRY INSIGHT THE

The global retail industry is undergoing tremendous disruption as a result of the Covid-19 pandemic. The Omicron variant adds new problems in the global supply chain industry. It is certainly isn’t a Black Friday but a dark Friday. Consumers have veered online as a result of the coronavirus and this has led to massive wealth gains for e-commerce startups and technology giants. Rand Merchant Bank calculates that the value of the e-commerce industry will be R225 Billion in 5 years.

KPMG emphasized on this year’s quarterly reflection on the retail sector that, “ The recent crisis has drawn a stark line under any indecision: the choices retailers make in the coming months will influence their success over the next 5 years or more.”

Think about this real-life scenario, it seems strategic for many executives to minimize store chains, and downscale investment on the physical property because consumer behavior has shifted. At the same time, a study by Pargo reveals that online purchases only account for 1% of total retail sales. This statistic may seem insignificant and might steer other executives to invest more in physical property because 99 % of the total sales come from offline services. Both of these extreme choices are not winning choices.Thereason for this is simple; consumers have multiple options and they are exercising all of them. They are not necessarily offline or exclusively online. They are considering many factors such as price, delivery, shopping experience, security, and more. They may be using the physical stores to browse products but purchase them online instead. For a retail chain, these permutations involve multiple stores.Let us complicate these retail strategic decisions by factoring in macro and international forces that are beyond our control. Take, for example, the July economic riots that were unforeseen, and no plans were devised to deal with such a retail disruption at such a scale. Many business owners whose shops were looted are faced with tough choices. Is it better to rebuild a smaller store in a shopping center or reconstruct the same one again or reduce the number of stores in your retail chain?

It is not about algorithms but competitive insights Data alone is not enough but excellent machine learning models are necessary for converting big data into insights. Retail competition is at an all-time high . Entrepreneurs need to make inventory management decisions, demand forecasting, track and respond to consumer behavior, monitor the competition, and create marketing activities with quantifiable returns on investment. All these choices happen in different departments but at the same time, they are choices that influence each other. Predictive analytics empowers you to order the right amount of stock so that stores won’t end up with too much or too little. However, artificial intelligence is more than just algorithms, it is about creating the perfect shopping experience. One example is heat mapping in the store. The hybrid of cameras and computer vision reveals which products are available picked up, which are returned, and where the customer goes after departing the shelf. You can utilize this intelligence to create experiences that expand engagement with products and encourage shoppers to learn more. More and more creative technology products will continue to come out, retailers who don’t adapt might not survive.

Takalani Madzhadzhi ( FASSA) is the Chief Executive Officer of Ashanti AI

Retailers need to change strategy

t

A

All of these considerations require making sense of qualitative and quantitative data to make intuitive business decisions that are customer-centric. Intelligence can also reveal new opportunities that aren't obvious to see. Did you know that it is possible for a physical store to have weak sales and profit but is a strong contributor to the overall retail performance? This is what we call the halo effect.The retail industry is evolving and technology is an enabler for innovative business strategies and execution. Big data, predictive analytics, and artificial intelligence empower businesses to build solutions and products that smash their everyday costs. They further provide a journey map of the customer that informs executives of profitable and sustainable management decisions they can explore.

36 SYNAPSE | 3RD QUARTER 2022

scheduled drugs in

and found the following improvements: results over a 4 week period in a live hospital environment

linen,

3RD QUARTER 2022 | ctrl easily integrates to multiple robots for dynamic automation needs find out more ctrlrobotics.com/better-hospitals@

Hospitals around the world face huge internal logistic a result of the labor intensive environment, many small packages need to be delivered on time from various depots to wards where patients need their medication, medical supplies, and delivery module on a custom configured robot to deliver a live hospital environment

problems as

meals. We piloted our

Automation has become imperative for businesses to maintain the competitiveness and agility required in today’s ever-changing economy. The latest Pinnacle Model study shows that enterprises prioritizing developing their intelligent automation (IA)

T AUTOMATION NEWS ROI AND EXPERIENCEEMPLOYEEBOOSTED BY ADVANCED AUTOMATION

The study defined businesses that achieved these superior outcomes thanks to their advanced IA capabilities as “Pinnacle Enterprises.” These businesses were found to:  Generate 2.3x the return on investment and 3.7x the cost savings from IA initiatives compared to enterprises with lower levels of automation  Benefit from a 62% overall improvement in operational metrics when compared to pre-automation figures. These include higher employee productivity, operational efficiency and quality, turnaround time, process governance and regulatory compliance – all key to overall business performance  Almost double their revenue over 2.5 years, highlighting IA’s boosting effect on business operations  Improve customer experience by 55% and employee experience by 52%

This latest study highlights that RPA alone lacks the ability to deliver the full potential of automation. While all companies that invested in automation saw some improvements, Pinnacle Enterprises differentiated themselves by choosing to integrate advanced IA technologies with the highest level of capabilities, including IDP, process mining and conversational AI – leading to substantial outcome gaps. Download the full study here. We look forward meeting you at the AI Expo Africa on September 19-20, 2022. Visit SS&C Blue Prism at our stand to find out more.

38 SYNAPSE | 3RD QUARTER 2022

he market for hyperautomationenabling technologies is rapidly growing and expected to reach nearly $600 billion this year.

A new Everest Group Pinnacle Model® study, supported by SS&C Blue Prism, has unveiled the financial, operational, and strategic benefits that enterprises realize by investing in advanced automation capabilities.

Advanced experienceimprovingbusinessestwofoldcapabilitiesautomationleadtoROIincreaseforwhilealsoemployeeby52%

IA is about much more than making businesses operate faster and at reduced error rates. It’s about utilizing the full potential of human talent. It’s about enabling businesses to reach further and achieve outcomes and goals they never realized possible while building organizational agility and resilience.

capabilities see the most improvements in operational efficiency, employee productivity and customer experience, which are the key drivers for intelligent automation adoption.

393RD QUARTER 2022 | SYNAPSE

 iTuring MLOps for automating the deployment of ML models;  iTuring MRM for automating model lifecycle management, model control, process and technology risk management, and risk classification and governance; and

M

 iTuring Decision AI to enable frontline workers to augment ML predictions with feedback based on the business realities and combine predictions of several AI models.

/

performance.enablercover,pricingcreditworthinesscompetition,intocustomerfraud,claimsmodellingworld.theyurgentsome(AI)artificialtowardsintelligenceasasolutiontoofthemostchallengesfaceinavolatileWhetherit’sinsuranceorcreditcardimprovingtheexperienceremainrelevantthefaceofdigitalassessingorinsuranceAIisanforbetter

“ This trend is changing fast with our nextgeneration approach to AI, which offers a one-stop, zero-code solution for rapidly developing, deploying and operationalising AI applications at scale. This approach slices the time to deploying AI projects from between two to six weeks, while helping to reduce risks and enhance ROI ”

40 SYNAPSE | 3RD QUARTER 2022

ost FIs struggle to achieve the full ROI they were hoping for and that it is significantly more difficult than anticipated. Across industries, AI initiatives are expensive and complex projects that take three to six months to complete, with an 85% failure rate. Lack of talent and time are perhaps two reasons FIs find AI success more elusive than expected. Building a team that spans the data science/machine learning (DSML) lifecycle is expensive and difficult. The time generally taken in developing, deploying and operationalising machine learning (ML) models often mean the data that an AI system was trained on is out of date before it’s ready for deployment. Since FIs operate in a highly regulated sector, issues of risk, trust and governance are high on the agenda. FIs need to be able to explain how an algorithm decides someone is a fraud risk or why a loan application was refused. They need to be able to assess and mitigate the risk of AI failure, plus have a governance framework to regulate development, deployment, monitoring, and managing of models. Somewhat ironically, the common factor behind so many of these challenges is that so little of the work that goes into building an AI system is automated. From data selection and modelling, operationalising AI to managing risk and governance, AI projects still depend heavily on slow, repetitive, manual work done by scarce talent. This trend is changing fast with our next-generation approach to AI, which offers a one-stop, zero-code solution for rapidly developing, deploying and operationalising AI applications at scale. This approach slices the time to deploying AI projects from between two to six weeks, while helping to reduce risks and enhance ROI. Our solution reduces the time required to develop accurate, production-ready models to a few hours without writing any code. The scalable AI platform can address a variety of use cases for every enterprise in various industries. Furthermore, it enables FIs to interpret, explain, and trust ML models. It understands, mitigates bias, and continuously improves performance, ensuring AI adoption.

 iTuring AutoML+, a fully automated ML platform to build and test best-in-class machine learning models;

By Bryan McLachlan, Managing Director: Africa at CyborgIntell / Financial institutions (FIs) in Africa are turning

AUTOMATION NEWS ACCELERATE YOUR DATA SCIENCE AND AUT OMATION J OURNEY WITH NEXT GENERATION AI

The components of our solution include:

 iTuring Open Data Accelerator (ODA), which processes, collates and cleans data from diverse datasets, leveraging more than 7000 pre-configured data features and feature store;

413RD QUARTER 2022 | SYNAPSE Build and deploy AI projects, with zero code, in 2-4 weeks. : cyborgintell.com : support@cyborgintell.com : @CyborgIntell : CyborgIntell Our disruptive “iTuring” platform is an innovative ZERO CODE AI driven Data Science and Machine Learning software that enables enterprises with CI’s ZERO CODE plug-and play platform is designed to start providing results instantly.

The SuperCluster, dubbed by Meta as the RSC (AI Research SuperCluster), is a behemoth: 760 NVIDIA DGX A100 systems representing a total of 6,080 GPUs and over 200 petabytes of caching/storage capacity AI FIT INTO YOUR BUSINESS?

Making sense of AI Few technology topics can cause as much confusion and anxiety as AI does. Highly technical and broadly mythologised by Hollywood movies and sci-fi novels, AI sits outside the enterprise's comfort zone. Yet you don't need to wade into the AI undergrowth - a handful of concepts illustrate fundamental AI use cases and how they can fit into your plans. Below is a primer on AI concepts that enterprises should know about: Computer Vision Computer vision is about 'seeing' objects. For example, many estates use AI via cameras to register car licence plates. Insurance apps can register a policy or claim, using computer vision to analyse photos of the insured items. Manufacturers deploy computer vision to spot defects on product lines. One of the current focus points is identifying complex visual elements, such as objects moving in 3D space and creating virtual duplicates of physical systems, often called Digital Twins.

/

OP ED

Meta's metaverse plans. Real-time emotional speech translation in online meetings and highquality computer vision are just a few applications that will emerge from this AI training complex. It's a strategic business investment - a sign that the future of digital enterprises will align closely with their AI investments. Of course, Meta's investment doesn't mean every business should start budgeting for a SuperCluster. But it suggests that AI be part of strategic conversations, says Werner Coetzee, Data Sciences Corporation's Business Development Executive: "Until recently, companies could look at AI as something other than a central business enabler. That narrative is changing - the SuperCluster proves that AI infrastructure has become more commoditised and affordable. For example, Nvidia is one of the highest-valued chip manufacturers because it in part supplies chips for AI. We're entering the enterprise high-performance computing era. Whether businesses rent AI services from the cloud or start building their own mini clusters, they must think about how AI impacts their strategy and future business models."

42 SYNAPSE | 3RD QUARTER 2022 n January, Meta (formerly Facebook) revealed its AI Research SuperCluster One might think: so what? You can log onto AWS or Azure and pick your AI service flavour. Why does it matter that Meta is doing the same? Only, it's not quite the same and, in retrospect, we'll mark the SuperCluster as a significant milestone. For people in the commercial AI and high-performance computing (HPC) sectors, the SuperCluster is huge news, explains Adrian Wood, Business Operations Director at Data Sciences Corporation:"Ithinktwo things stand out about the SuperCluster. Firstly, it's a massive, massive investment in AI infrastructure by a Fortune 500 company, not an academic institution or nation state. Second, Meta is not building this to sell services to users, as the hyperscale cloud providers do. The SuperCluster is an inward-facing strategic project. It's there to help drive Meta's business future."

HOW DOES

By James Francis / I that can provide 16 terabytes a second of training data (with plans to scale to 1 exabyte a SuperClustersecond).underpins

What does any of the above mean for your business? That is a question only you and your peers can answer. But Meta's big investment indicates that AI is inseparable from a maturing digital business world. Whether you use a few AI services or strategically adopt high-performance computing, start having conversations about AI and what it means for the future of your enterprise. “ This trend is changing fast with our nextgeneration approach to AI, which offers a one-stop, zero-code solution for rapidly developing, deploying and operationalising AI applications at scale. This approach slices the time to deploying AI projects from between two to six weeks, while helping to reduce risks and enhance ROI ”

Siri, OK Google and Alexa use speech recognition models trained by AI. If a service chatbot understands typed responses, that is natural language processing at work. You may have already encountered online presentations translated in real-time to another language. And if you use AI-powered transcriptions from audio files such as Otter.ai, you benefit from this branch of AI. Researchers are currently focused on analysing emotions in language that will translate real-time conversations with the nuances of human speech.

Self-supervised learning & Transformer-based models Self-supervised learning and more advanced transformed-based models enable AIs to adjust their training parameters. But they don't stray from their objectives - an AI improving computer vision won't go rogue. Despite the name, such systems are highly supervised. They just don't need human intervention to adjust their parameters, thus significantly speeding up AI model innovation. The ability of Google to translate web pages is a predecessor of these concepts.

Robotics & Embodied AI

When a robotic vacuum cleaner figures out its way around your home, that's an example of robotics and embodied AI. Embodied AI happens at the edge, detecting the physical world and making decisions based on that input. We're inclined to think of self-driving cars, but an embodied AI could be a search & rescue robot navigating an unknown space as it looks for survivo rs. Amazon Echo devices are a current example: they can dynamically lower or raise their volume in response to ambient noise. Robotics puts embodied AI in action around us, operating safely and effectively with the information detected by its sensors.

Augmented Reality & Virtual Reality Augmented reality (AR) - which overlays digital information over what we see in front of us - is used for training, design and repairs. AR is also active in surgery and across the windscreens of high-end luxury cars. Mining, manufacturing and engineering firms have found numerous uses for AR. Likewise, virtual reality (VR) has become instrumental for designing cars, aircraft engines, and architecture. AI training helps create and manage the visual data that both technologies use, such as digital twins and virtual collaboration rooms.

Adrian Wood, Business Operations Director, Data Sciences Corporation / Werner Coetzee, Business Development Executive, Data Sciences Corporation

Multimodal AI As the name suggests, multimodal AI incorporates two or more different AI concepts. Several above examples already illustrate the concept, such as robotics or virtual reality interactions.

433RD QUARTER 2022 | SYNAPSE OP ED

Natural Language Processing (NLP) & Speech Recognition

AI is not just a means to an end, we live and do business differently because of its far reaching impact. It offers us new opportunities to address societal and economic issues, from social inclusion to workplace participation, to security and environmental protection. Therefore, as an engine of productivity and economic growth, any developments in AI must also contribute to the general welfare and prosperity of a country and its citizens.

44 SYNAPSE | 3RD QUARTER 2022 AI THAT INCLUSIONCHAMPIONS DUTCH EMBASSY

The Netherlands excels at innovation, because of its ability to bring knowledgegovernmentbusiness,andinstitutestogether demandcollaborationstrategicandplacingatthecoreofourconversations,weaimtofosternewpartnershipsinaddressinglocalchallenges

DUTCH EMBASSY

Our focus lies in smart solutions for resilient cities, including smart logistics, agri tech, health tech and water tech; where we support mutually beneficial trade, investment, and knowledge cooperation.

Let’s get the conversation going!

453RD QUARTER 2022 | SYNAPSE

Follow us on

COCREATION Through

owever, when it comes to AI and data science, there is a troubling and persistent absence of women. Only 22 percent of those in this field are women. But despite low participation rates and barriers to entry, women in AI are breaking silos and bringing game-changing innovations to the industry. Technological innovation cannot flourish without social innovation, and social innovation cannot happen in the absence of inclusion. It has been proven that diverse teams are more productive and creative leading to new and inventive ideas. The Kingdom of the Netherlands in South Africa, under the #cocreateSANL brand, strives to improve the participation of women and youth through its support of women in STEM, and working more meaningfully with youth-led organisations. One such initiative is #InspiringFiftySA, which is a national campaign that showcases inspiring women role models in the STEM industry in Europe, Canada and South Africa. We continue to work together with the South African ecosystem to develop solutions that will empower both countries. We will be hosting a hackathon (#hackMYCITY) in November 2022, in collaboration with one of the leading digitalisation institutes in the country, Tshimogolong Digital Innovation Precinct. Through the hackathon, we aim to demonstrate the opportunities and benefits of digital twins in policy making for the city for Johannesburg. Therefore, the hackathon will be centred on real challenges the city is facing, facilitate surfacing of local youth-led innovations as well as kickstart the implementation of said innovations. The Netherlands believes digital transformation must be built on trust and focus on serving societies worldwide. Through cooperation, we aim to further unlock the social and economic potential of digital technology, such as lowering healthcare costs, improving mobility H and accelerating sustainable food production. We also aim to be a pioneer and testing ground for responsible digital innovation. To this end, the Netherlands has positioned itself as a key player in a number of sectors in regard to technological development and AI such as smart mobility, healthcare, agriculture, data sharing and cyber security. The Netherlands is rising strong in AI readiness, and leaped from 14th to 9th place in the 2020 Oxford Insights Index. We are proud to host the headquarters of the largest international AI network, the CLAIRE Research Network, as well as the first AI-only Rockstart Accelerator.Wearelooking forward to growing the relationships with our existing partners in South Africa, and we are always open to forming new strategic partnerships. Make sure to visit our women in AI pavilion at this year’s expo, and look out for our #hackMYCITY hackathon in November! “ We continue to work together with the South African ecosystem to develop solutions that will empower both countries. We will be hosting a hackathon (#hackMYCITY) in November 2022, in collaboration with one of the leading digitalisation institutes in the country, Tshimogolong Digital Innovation Precinct

The Kingdom of the Netherlands believes that we can #cocreate pioneering digital solutions to solve local challenges by facilitating innovative partnerships Reach us at KAA@minbuza.nl our website www.cocreatesa.nl social

| Visit

media SUSTAINABLESOLUTIONS

INNOVATION

The human in the system is seldom accounted for. Even though machine processes are largely designed to target, speak to, and engage with humans; most of the patterns and correlations it identifies don’t tell you much about their behaviours. Using machine learning to understand the impact of shared rituals is poorly lacking in most deployments.

By 2025, 90% of customer interactions will be supported by AI.

HUMAN-CENTRIC

INTERACTIONS

A recent report by Gartner found that 85% of AI projects fail to deliver.

Engage with people more authentically with pre-configured behavioural models

Clearly, companies are investing hugely in Ai to get to know their customers better, build loyalty and make more sales.

EnvironmentLow-CodeBehaviouralAnalysis

platform is built on 3 foundational pillars:

There are myriad reasons for this, but we believe that there are 3 fundamental issues that can lead to such high failure rates:

Generic data science answers the “how” through analysis of data points and trends. But ecosystem.

The

How much can you tell about your customers? PredictionsReal-time

46 SYNAPSE | 3RD QUARTER 2022

Can a deployment based on historical data really predict what customers are going to do in the future? Consider the data from the last 3 years when the Covid pandemic influenced an un-referenceable series of data points. Can we reliably use this data to predict what customers want this year, or the next? This is ecosystem.Ai’s area of expertise. Our revolutionary platform integrates Computational Social Science to bridge the gap between machine and human intelligence. Providing analytics from a human and behavioural context, we help companies build behvaioral models in their own environment and get their real-time predictions into market faster. Our low-code platform increases your speed to market by reducing complexity costs The platform has a no-code environment Workbench, as well as low-code environment Notebooks. Designed to be accessible to everyone in a business - from the Businessperson who needs to drive success. To the Data Scientists who require uncomplicated tools to untangle machine learning complexities. As well as Technologists who require flexibility in the form of code-based customizations that are easy to implement and integrate.

The extra layer of meaning this adds to the data allows companies to communicate more effectively. As well as offer more relevant recommendations, and understand what customers truly want.

ecosystem.Ai’s multi-faceted technology provides a single platform that works within your own environment, or in the cloud. It facilitates open collaboration for all team members to work on the same project, and keep track of all deployments.

OP ED

Ai needs to advance and factor in human behaviour and context.

But are they seeing a return on their investment?

1. Deployment Complexity can skyrocket costs Putting accurate and successful machine-learning projects into production is complex. The tools to create predictions, build recommenders and configure experiments are costly, complicated and require expertise.

Moving to a low-code, specialised deployment environment reduces these costs immediately, and gives business users more involvement throughout the lifecycle of the project.

2. Current predictions don’t account for ever-changing human behaviour

3. Reliance on historical data doesn’t provide real-time insight 58% of successful machine learning projects take more than several months to deploy. Delays happen, which means that at the point of deployment, the data being analysed and predicted on is from the past. As stated, this can’t account for a customers changing behaviour, and crucially, it doesn’t factor in their most recent transactions.

Ai use Computational Social Science to take this a step further by asking the “why” and “what next”. Uncovering this deeper level of understanding reveals a multitude of untapped data patterns to identify real human behavioral nuances. One way to achieve this is by applying a digital personality*. Segmenting by personality provides a better way to know an individual’s wants and needs, in a more personalized way than traditional segmentation.Everydigital interaction leaves a transactional trail that gives insight into the behaviours of a human. Analysing this trail as it plays out in realtime, helps you make better predictions about that individual. Companies can structure offers and engagements based on the rhythm and actions of a customer, while continuously testing and experimenting with novel offers to spark interest. Capitalize on emerging trends and ritualistic patterns with real-time analysis Companies need to evolve. There must be frequent continuous cycles of experimentation to keep pace with changing behaviors. Our real-time engine makes this possible by giving your machine-learning models more accuracy and relevance, right now. Allowing you to change configurations, tweak engagements,

Ai Platform. Companies should always be experimenting. When you increase the frequency of experiments and deployments, you stay more current and more competitive. Every digital transaction is a missed opportunity to understand and serve your customers, partners, and employees better. However, this involves more than analysis of historical data and technical expertise. We have integrated Ai with real-time, behavioural constructs, to bring a new level of human intelligence and contextual understanding. In order to enhance how you engage and interact with your customers. and tailor offers and messages as customers interact with you. Real-time means no more waiting for batch processes to analyze performance.You can let your customers reactions guide decisions as you view their real-time interactions. This is a game-changer as it takes the element of guesswork out. With predictions there is benefit to using historical data. But in real-time you don’t necessarily need data to get started. Our experimentation process means you can start building relevant predictions with no data. Experiment to get faster, more reliable insights into production According to Gartner, only 53% of projects make it from prototype to production. But what if you could run live experiments with your predictions? Having no data does not mean you cannot make good predictions Whether your data is tied up, behind red tape, unusable or nonexistent, experimentation is the key. Our Data Science Experimentation Module helps you detect real-time changes in human behaviour without data. It uses an experimentation-based methodology, built with sophisticated functionality that takes time dependence, seasonal effects, and human rituals into account. Using our experimentation modules, you can start testing while the traditional data science process is being completed. Furthermore, you can run multiple experiments in production to amplify the success of your predictions. Dynamic Experimentation is a framework that goes far beyond general AB testing. While the one focuses on testing few options in the hopes of finding the OP ED ‘one-size-fits-all’ solution. Our Dynamic Experimentation means you can find the right fit for all of your customers, by giving them exactly what they want, and not just the most popular opinion. With Dynamic Experimentation, you can identify tangible evidence of offer takeup in a personalized customer basis. Learning from each customer which option suits them best, and which one they are most likely to engage with. This allows you to lower the costs associated with failed deployments and unpopularContinuousoffers.behavioral tracking and interventions through experimentation will catapult your business to success. The experimentation’s powerful real-time feedback system continuously learns from user interactions to enhance both system knowledge and actionable outputs. Therefore, you no longer have to decide on a single option to test. Recommend the right things at the right time to the right people Recommenders are commonly used by all major companies like Amazon, Spotify and Instagram, to provide offers, filter content and make suggestions. These have already moved on from the early days of ‘people who like this, also like these’, to now incorporate more personalization. But are they getting it right yet, and what’s ecosystem.Aimissing?are advocates for appealing to the human as a changing being. We have structured our recommenders to always remember the human, by offering fresh, new options to customers to introduce an element of novelty. Our recommenders offer further enrichment to businesses by providing accurate and timely view of customer takeup. Real-time

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*a digital personality is derived from digital interactions and provides a view of a human’s behaviour with your company, not their human personality. information combined with human behavioural analysis, allows for more personalized, targeted offers at pivotal times in the customer journey. Engagements are enhanced, as the customers behavior determines the design, structure, amount of information, and wording that can be used. The recommender can then offer the best options depending on feedback from the customer in real-time. Multiple recommenders and experiments can be run at the same time, all easily managed from one central location - the ecosystem.

ECOSYSTEM NEWS

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By Gregg Barrett /

Cirrus and the AI Africa Consortium are a major response to the AI deficit in African science. The aim is to broaden researcher access to compute, data, and engineering, training students, ensuring that AI for science is feasible in numerous academic institutions across the African continent - not just elite academic institutions and large technology firms - and facilitating the commercialisation of research findings. With human capital central to AI, on-line learning and related pedagogies can play an important role in knowledge transfer to Africa.

AI FOR SCIENCE IN AFRICA

Prioritising AI for science in Africa AI enabled scientific research is not yet happening in Africa. Most of the leading corporate research operations are not located in Africa, but operate in Asia, Europe and North America. This is an important barrier to collaborative research and commercialisation efforts at African institutions. The five major technology platform companies spent US $127 billion in R&D in 2021 [Bajpai, 2021]. Data from the QS World University Rankings, since 2012, show that Fortune 500 companies collaborated six times more with the top 50 universities than with those ranked between places 301 and 500, where most African universities are situated [Ahmed, et al. 2020]. This imbalance in collaboration exacerbates the disparities between academic institutions in Africa and top tier academic institutions in the rest of the world. Furthermore, Fortune 500 technology companies and the top 50 universities publish five times as many papers annually per AI conference than universities ranked between the 200th and 500th places. Africa’s highest ranked university in 2021 was the University of Cape Town, in the 220th place.i And while the research budgets of premier academic research institutions like Carnegie Mellon University’s Robotics Institute - at US $90 million in 2019 [Carnegie Mellon University, 2019] - is a fraction of that of the major industrial companies, it is orders of magnitude greater than that of any academic institution in Africa.While world class research does take place at African institutions, African researchers lack the data, compute infrastructure, and engineering resources to develop and apply the more powerful and

Introduction There is much fundamental and applied scientific research being carried out at academic and other research institutions in Africa, but little as yet utilises AI. African science needs to take up AI methods, because absent such methods an increasing number of scientific disciplines at African institutions will border on irrelevance. A greater use of AI in scientific research in Africa will bring numerous benefits, deepening African science, broadening global research agendas, and incentivising the location of corporate R&D labs. Ultimately, the use of AI in science will have spillover effects, helping upgrade the capabilities civil society more broadly.

Full implementation of all the components of Cirrus and the AI Africa Consortium will

For African academic and research institutions, moving forward on AI also requires efforts to significantly increase the scientific throughput that feeds AI systems.

493RD QUARTER 2022 | SYNAPSE ECOSYSTEM NEWS critical AI methods. Even for the world’s elite academic institutions and researchers, it is increasingly difficult to work at the frontier of AI research [Sample, 2017]. For example, OpenAI analysed the relationship between the availability of computational resources and 15 relatively well-known breakthroughs in AI between 2012 and 2018 [Amodei, et al. 2019]. Of the 15 developments examined, 11 were achieved by private companies while only four came from academic institutions. When that paper was published, the most recent of the major compute-intensive breakthroughs originating from academia was Oxford’s 2014 release of its VGG image recognition system. According to OpenAI, of the eight breakthroughs that occurred between 2015 and 2018, all came out of private companies.

iii A high priority must be to identify and leverage existing and potential scientific data-generating programmes to produce AI-ready data repositories. The liberating of data in a privacy-preserving manner must extend across science, from earth observation to healthcare. Doing so will not only support science but will also aid in the use of AI for a more diverse set of pressing social problems. Also needed are research infrastructures and resources that can provide continuous data collection where AI is eventually integrated to allow for active learning, where the AI system itself decides what data to collect next, and supports dynamic control and decision making (an example is the case of automated experiments.

Cirrus and the AI Africa Consortium Cirrus was initiated in 2017 out of a need to use AI in scientific research taking place between the synchrotrons and Wits University. The Wits University leadership then decided that Cirrus should benefit not only Wits, but all academic and research institutions in Africa.

An important step in developing AI in Africa is to prioritise the capabilities needed by scientists and researchers in academic and research institutions and industry. Governments in Africa already struggle to provide a range of basic infrastructure and other public services. Any discussion of AI must be had in a context of these broader priorities. In this broader context, there is also an urgent need to recognise the AI needs of civil society - given its role as promoter of good governance [Mlambo, et al., 2019] - and related efforts on social justice and human rights. Africa lacks the calibre of governance institutions found in more developed regions of the world, making the role of civil society even more critical [World Bank, 2020]. Strengthening the African AI workforce and infrastructure requires integrating the needs of civil society organisations with academia. In terms of training and human capital development, universities are fortunate in that the field of AI involves many feasible options to rapidly upskill researchers. This is resulting in a paradigm shift for many in academia who are accustomed to building courseware (an example of what it takes to build and maintain high quality courseware for machine learning is given in Reddi (2021)). Forward thinking universities have steadily been moving towards what is called a ‘flipped classroom’. A flipped classroom format means that learners watch videos and complete in-depth assignments and online quizzes at home, then come to class for discussion sessions. The classes generally culminate in an open-ended final project, which the teaching team usually assists with. The university often uses previously developed high-quality Massive Open Online Courses as the core course material, and then focus on supplementary domainspecific materials, projects and assignments. With this approach, students in developing countries can access courseware used at elite universities, at a fraction of the cost to the student and the university than the previous alternatives.

The implementation of Findable, Accessible, Interoperable, and Reusable data principles, and the participation in a centralised set of standards for benchmark datasets in scientific domains are needed to govern data storage formats, access and metadata to reduce engineering overhead and lower the barriers to training and comparing model performance.

Over the course of 5 years the legal groundwork has been laid to operationalise Cirrus and the AI Africa Consortium. Cirrus and the AI Africa Consortium are ambitious by African standards. The resources involved, plans and modus operandi of Cirrus and the AI Africa Consortium are described in the rest of this section. Some activities have already begun including the rollout of machine learning for embedded devices.

“ While world class research does take place at African institutions, African researchers lack the data, compute infrastructure, and engineering resources to develop and apply the more powerful and critical AI methods ”

To deploy AI for science requires a range of new capabilities and leadership New capabilities and leadership are needed if African research institutions are to harness new AI methods. Such capabilities do not exist in the absence of engineering personnel to prepare data, configure hardware, software and machine learning algorithms, as is the case in most of Africa. In addition, the ad hoc mix of campus computers, and commercial clouds that Africa’s educators and researchers rely on today are inadequate.iiSimplyproviding underserved academic and research organisations’ with the data, hardware, software and engineering resources is insufficient. To truly reduce the barriers to AI-enhanced research, underserved institutions need access to experts able to implement best practices in such areas as approaches to problems, methods of teaming, selection of tools for tasks, and optimisation of workflows.

Governments, academic and research institutions in the region must redouble their efforts to generate more and betterquality data, and to make data accessible.

An example is the development of AIready datasets. Although data in science is abundant, in many scientific areas sufficiently large datasets either do not exist and/or are not accessible in forms that permit the application of AI methods.

Substantial effort is required to create new datasets, for instance in locating the data, cleaning it, aligning the schemas of disparate data, ensuring machine readability, and providing relevant metadata pertaining to issues such as data provenance, quality, and completeness. This expensive and error prone process, which must be repeated for each analysis, not only becomes a barrier to using data, it also leads to problems of research reproducibility. Furthermore, privacy and security issues need to be addressed from the beginning, rather than after the fact, with integrated assurances and audit capabilities to advance research in the public interest. Most tool development for datasets happens without public or an interexperiment collaboration in mind, which can lead to duplication of effort. Providing a data management platform to enable efficient AI development and sharing is a priority for Cirrus. Such a platform will enable users to store, manage, share and find data used to develop AI systems. This includes tracking of the data, versioning support for various data formats, and complete metadata, to allow for retraining and understanding models built from the data. Such a platform will drive advances in AI by enabling AI researchers to experiment with existing and new methods in new contexts, and benefit the disciplines in which the datasets are created.

3. Wits is situated geographically in the highest concentration of economic, academic and research activity in Africa.

Third, the Cirrus FOUNDRY Fund is the in-house fund to support start-ups in the Cirrus FOUNDRY to reduce dependence on outside capital. The Cirrus FOUNDRY Fund has a target capitalization of 35 million dollars and will undertake preseed and seed stage investments.

overview of why consortia can catalyse open science see Cutcher-Gershenfeld (2017)).

 Accelerate discovery and improve reproducibility through sharing of data sets, metadata, models, software, hardware and other resources.

Source: Cirrus AI, 2022.vi

Thesolutions.organisational structure of the Consortium is set out in figure 1. At the time of writing the outstanding component of the schema is the appointment of the lead investment bank for the solicitation of the SFP’s. Following the placement of the SFP’s the Partner, Affiliate and Co-development programmes will be rolled out.

Allocation of Cirrus resources to the AI Africa Consortium will occur through a mix of peerreview, lottery and equitable distribution criteria. As a private-sector entity, Cirrus is also not encumbered by the intellectual property constraints that ensnare research commercialisation efforts at publicly funded universities.iv This provides Cirrus with the flexibility to support a range of commercialisation options.

4. Wits has the land available to house the necessary infrastructure, including for necessary energy generation and storage (construction of the physical infrastructure, like the energy generation, and high-performance computing centre is yet to start).

 Foster a co-design culture where teams of scientific users, engineers, and instrument providers can help to develop new and broadly applicable capabilities and tools.

ECOSYSTEM NEWS

Figure 1: The organisational layout of Cirrus and the AI Africa Consortium commence following the placement of the Strategic Founding Partners (SFP’s).

Cirrus has three components. First, Cirrus will house the cooperation programmes, the state-of-the-art computing and data infrastructure, engineering personnel and the open learning programmes. Second, the Cirrus FOUNDRY is equipped with everything needed to address the challenge of turning insights from scientific research into start-ups and eventually larger commercial applications.

 Reduce the cost for individual research programmes involved in integrating capabilities and/or comparing their work with others’.

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The AI Africa Consortium

Cirrus Cirrus is designed to provide data, dedicated compute infrastructure, and engineering resources at no cost to academic and research institutions, through the AI Africa Consortium.Providing dedicated compute infrastructure will be an enormous contribution. Based solely on hardware costs, it is more cost-effective to own infrastructure when computing demand is close to continuous. Estimates comparing commercial cloud services to a dedicated high-performance computing cluster show that commercial cloud services are more expensive per compute cycle [Villa et al. 2020]. While the initial costs of subsidizing cloud credits might be less than building public infrastructure, studies show that relying on commercial cloud services would likely be much more expensive in the long term [Wang et al. 2021].

 Reduce redundancy of effort and cost as new research projects will not have to build capabilities or collect new data from scratch each time.

The physical infrastructure and operations for Cirrus are to be housed at Wits University in Johannesburg, South Africa. Wits University was selected as the host institution for four primary reasons:

2. Wits is one of Africa’s leading academic research institutions.v

The Africa AI Consortium is currently establishing collaboration agreements with numerous parties in the African R&D ecosystem to help identify research priorities, to spread AI research resources, and to engage African research talent (for an

 Help and encourage researchers to interact and collaborate beyond disciplinary or institutional silos.

Cirrus will help to attract corporate research (and associated venture capital activity) to Africa. For the private sector, participation will provide:  Returns as Limited Partners in the Cirrus FOUNDRY Fund.  Returns from equity ownership in startups within the Cirrus FOUNDRY  Admission to the Cirrus Partner Programme, which is geared to support collaborative R&D as well as technology transfer and sharing. The goal is that Cirrus will ultimately be owned, through equity, by around 15 to 25 multinational corporations, termed Strategic Founding Partners. The financial contribution from these corporations will be in the region of 7 to 20 million dollars each. The diversity in ownership should bring with it a diversity of research interests and help avoid AI research focused only on a narrow set of ideas and methods biased to the interests of a particular private sector participant. The research mission of Cirrus is also isolated from political influence, from changes in political administrations, and from politically appointed administrators.

 Supporting a research ecosystem that understands the full context for AI

The Consortium aims to create a leading AI research capability by developing skills and recruiting researchers across Africa and other skilled personnel, and pairing these with the capabilities provided through Cirrus.

The Consortium will:

1. South Africa is the most scientifically advanced country on the African continent [Mouton, et al. 2019].







The strengthening of science in Africa by AI methods will broaden global research agendas and elevate African research. To accomplish this Africa must also act collectively and collaborate to grow the scientific output needed to exploit the opportunities presented by AI. The goals described in this essay are challenging and the proposed solutions will require significant investment. However, the potential return on that investment is enormous: new types of data analysis, improved and even autonomous operations and performance of scientific instruments, innovative commercial products emerging from science, with even the potential for new industries, and an opportunity for Africa to become a producer of AI for science and not merely a consumer of the resulting breakthroughs.

 Sample, I. (2017). ‘We Can’t Compete’: Why Universities Are Losing Their Best AI Scientists, The Guardian Website, November 1. Retrieved from losing-best-ai-scientistsnov/01/cant-compete-universities-www.theguardian.com/science/2017/https://  South African Government. (2010). Intellectual Property Rights from Publicly Financed Research and Development Act: Regulations. Retrieved from documents/intellectual-property-https://www.gov.za/ rights-publicly-financed-research-anddevelopment-act-regulations-1  The Times. (2022). The Times Higher Education Emerging Economies University Rankings Website. Retrieved from economies-university-rankingsuniversity-rankings/2022/emerging-timeshighereducation.com/world-https://www.  World Bank. (2020). Worldwide Governance Indicators Website. Retrieved from org/governance/wgi/https://info.worldbank. Villa, J and D. Troiano (2020), “Choosing Your Deep Learning Infrastructure; The Cloud vs. On-Prem Debate”, Determined AI Blog, July 30. Retrieved from blog/cloud-v-onprem/https://determined.ai/  Wang, S and M. Casado (2021), “The Cost of Cloud, a Trillion Dollar Paradox”, Andreessen Horowitz Website, May 27. Retrieved optimization/lifecycle-scale-growth-repatriation-of-cloud-paradox-market-cap-cloud-https://a16z.com/2021/05/27/cost-from i For the full list of rankings, see: QS World University Rankings. (2021). ii For commentary on the engineering skills that went into developing AlphaFold 2, see: Rubiera. (2021). iii For recommendations concerning access to research data from public funding, see: OECD. (2021). iv For the regulations governing intellectual property rights from publicly financed research in South Africa, see: South African Government. (2010). v See The Times Higher Education Emerging Economies University Rankings. (2022). vi Schematic view of the organisational layout of Cirrus and the AI Africa Consortium, see https://aiafrica.ac.za/ vii For information on TinyML4D, http://tinyml.seas.harvard.edu/4D/see viii For information on the MLCommons Science Working Group, see science/mlcommons.org/en/groups/research-https://

Conclusion

Fundamental and applied research and development at academic and research institutions in Africa are at risk of marginalisation because resources essential to AI - compute, hardware, software, accessible data, and machine learning engineering - are out of reach. The growing imbalance in AI resources and innovation between Africa and the rest of the world requires an unprecedented response. The establishment of Cirrus and the AI Africa Consortium is one of Africa’s responses, aiming to help spread opportunity more widely, supporting students and researchers at universities and research institutions across Africa, activating the talent of researchers once they have access to AI infrastructure and other resources, and creating fertile ground for commercialisation through entrepreneurship. For science in Africa, Cirrus and the AI Africa Consortium afford a major opportunity to develop and exploit AI techniques and methods. This will improve not only the efficacy and efficiency of science but also the operation and optimisation of scientific infrastructure (because system scale and complexity demand AI-assisted design, operation and optimisation).





ECOSYSTEM NEWS

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References  Ahmed, N. and M.Wahed (2020), “The De-Democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research”. Retrieved https://arxiv.org/pdf/2010.15581.pdf.from  Amodei, D and D.Hernandez (2019), “AI and compute”, OpenAI Blog, May 16. Retrieved from





Efforts already underway within the AI Africa Consortium include: TinyML4D: The rollout machine learning on embedded devices targeted at developing countries. It includes the provision of free hardware kits, workshops, courseware and a network of research and collaboration opportunities. vii  MLCommons: Fostering African participation in the development of science benchmarks, particularly those of relevance to African researchers.viii  Remote Excellence Fellowships: A remote internship system for talented Masters students to allow students to connect with leading researchers in Europe.

sciencemellons-top-ranked-school-computer-edu/news/hebert-named-dean-carnegie-AugustCarnegieTop-RankedHebertCarnegieand-development-rd-2021-06-21companies-spend-the-most-in-research-https://www.nasdaq.com/articles/which-NasdaqResearchWhichblog/ai-and-computehttps://openai.com/Bajpai,P.(2021).CompaniesSpendtheMostinandDevelopment(R&D)?,Website,June21.RetrievedfromMellonUniversity.(2019).NamedDeanofCarnegieMellon'sSchoolofComputerScience,MellonUniversityWebsite,8.Retrievedfromhttps://csd.cmu.  Cirrus AI. (2022). Schematic view of the organisational layout of Cirrus and the AI Africa Consortium.  Cutcher-Gershenfeld, J. et al (2017), “Five ways consortia can catalyse open science”, Nature 543, 615–617. Retrieved from https://doi.org/10.1038/543615a  Mlambo, V. et al. (2019). Promoting good governance in Africa: The role of the civil society as a watchdog, Journal of Public Affairs, March 16. Retrieved from https:// doi.org/10.1002/pa.1989  Mouton, J et al. (2019). The state of the South African research enterprise. Retrieved from enterprise.pdfstate-of-the-South-African-research-crest/wp-content/uploads/2019/08/http://www0.sun.ac.za/  OECD (2021), “Recommendation of the OECD Council concerning Access to Research Data from Public Funding”, OECD Website. Retrieved from funding.htaccess-to-research-data-from-public-www.oecd.org/sti/recommendation-https://  QS World University Rankings. (2021). QS World University Rankings Website. Retrieved from world-university-rankings/2021topuniversities.com/university-rankings/https://www.  Reddi, J.V. et al. (2021), “Widening Access to Applied Machine Learning with TinyML”. Retrieved from https://arxiv.org/ pdf/2106.04008.pdf  Rubiera, C. (2021). AlphaFold 2 is here: what’s behind the structure prediction miracle, Oxford Protein Informatics Group Blog, July 19. Retrieved from prediction-miracle/2-is-here-whats-behind-the-structure-blopig.com/blog/2021/07/alphafold-https://www.





Endnotes 

/ By Chayan Bhattacharyay, Founder and CEO, HyperCAP / Language Processing (NLP), to simplify the automation of business workflows and seamless integration of hetero genius systems.Hyper Automation augment your staff's ability to reduce operating costs and errors and improve efficiency, productivity and help you scale faster.

52 SYNAPSE | 3RD QUARTER 2022 The idea of isfortheGartneraroundmanager'swouldtheseGartner,(DPA).processphenomenonForresterintroducedautomationhyperwasfirstbyGartner.identifiesthisasdigitalautomationAccordingtoimplementingtechnologiescuttheworkloadby69%by2024.estimatethattotalmarketsizeHyperAutomation$860BN. imply put, Hyper Automation is the technique of combining several technologies to carry out 360-degree automation of a company's business functions within the need of a single, unified, and intelligent system. It involves the use of technologies such as - Robotic process automation (RPA), Machine Learning (ML), Artificial intelligence (AI), and Natural AUTOMATION NEWS S HYPERAUTOMATION-360-DEGREECOGNITIVEDPA

in

HyperCAPAbout

At HyperCAP we work with companies like yours to augment their staff's ability to reduce operating costs and errors by 10x with intelligent digital workers that would improve efficiency, productivity and help you scale faster.

Video and Image Analytics

533RD QUARTER 2022 | SYNAPSE AUTOMATION NEWS

Conversational AI Powered by AI, ML, NLP and NLU, Speech To Text (STT) and Text to Speech (TTS), it provides intelligent contextual personalized round-the-clock automated service to your internal or external stake holders. It allows you to engage your customer over chat or voice on the web, mobile, Facebook, WhatsApp, telegram, Viber, Slack and with voice assistance like Google Home or Alexa and many more Process Mining and Discovery It’s a tool that allows us to analyse your process log data and visualize the business processes and highlight any bottleneck deficiencies or repetition and recognize areas of improvements in the processes by bottleneck process it means activities which are taking too much time to complete or require significant amounts of rework

It’s a computer vision technology that uses ai and machine learning to help you understand, analyse and classify your images and videos with a very high degree of accuracy.

Benefits of HyperAutomation

HyperCAP is a one stop shop for Hyper Automation. We enable organizations to adopt the most comprehensive Hyper Automation platform on the planet that we have built in-house. We complement the existing enterprise applications like ERP or CRMs – and make the process execution 100x faster in every business function like HR, Finance, Procurement and Supply Chain, IT, Any Core business process, and Customer Service. We are industry, business functions and business application agnostic and can work with any business applications. Here is a brief demo of the platform.

Intelligent Document Processing (IDP) Consider a situation in which hundreds of invoices need to be processed and the entries need to be made in the accounts payable system. Traditional data extraction of these documents is based on predefined templates. With the help of Machine learning and AI, IDP can help to extract data from thousands of these documents without any need of writing template-based data extraction logic.

Key Market

TechnologiesDriversinvolved

HyperAutomation

RPA Robotic process automation (RPA) Help you automate the routine and tedious tasks and let you focus on innovation. It offers automation solutions to the common problems in running repetitive work such as data entry, payment reconciliation, and data sharing, letting you focus on the problem that matters most.

bepotentialdecisionsforwhatbasedofon—bigexecutivescreatesbusinessButintelligenceartificial(AI)hype.whenindustriesorleadersdo,itAImythsthatsomebasedecisionsdecisions.Insteadmakingwise,data-movesbasedonAIcanactuallydobusiness,theymakebasedontheymightnotsetuptoreach—yet.

To help separate myth from reality, the IBM Institute for Business Value (IBV), in collaboration with the MIT-IBM Watson AI Lab, interviewed individuals involved in deep-learning projects from more than 35 real-life artificial intelligence (AI) implementations around the globe. We talked to business and technology experts from more than a dozen industries about their AI goals, challenges, and learnings.

Separating AI myths from business reality isn’t always easy. Explore 12 examples of how organizations are creating very real business value with artificial intelligence. It’s easy to get caught up in the

HOW TO CREATE BUSINESS VALUE WITH AI

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VENDOR INSIGHTS

etting it right—now—matters because business and society are rapidly adopting AI. Early in the pandemic, 84% of all organizations expected to maintain or increase the level of organizational focus on AI, with nearly a third boosting their AI investments as a direct result of the pandemic. For some innovative AI adopters, AI helps create entirely new business models. Few enterprises, however, are using it for such broad transformation yet.

A peek behind the AI curtain

Transformation depends on reality, not perception The transformative value of AI—through its financial, economic, and societal impacts— can only become reality if leaders of more traditional enterprises fully grasp the opportunities for innovation strategically, thoughtfully, and concretely. A critical starting point is to separate perception from the emerging reality of AI. To distinguish AI realities versus the myths, download our report. You’ll learn how a consumer goods company used AI to supplement the experience of junior food scientists to help them perform at the level of a senior scientist with 20 years of expertise. You’ll discover how AI is being used to battle malaria, and how an insurance company dropped settlement costs by 40% using artificial intelligence. And that’s just the beginning.

What did we learn about AI business value? AI uptake continues to increase, but most organizations are not yet using it fully for broad transformation. Instead, many are just addressing discrete business challenges. By the end of 2022, we estimate that just one out of four large companies will have moved beyond pilots to operational AI. Some companies are still basing AI decisions on a few myths, rather than AI reality. “AI shortcuts don’t work.” Oh, but they do. “If it isn’t deep learning, it isn’t AI.” Not so. Part of AI’s power lies in its many variations. Fit for purpose matters.

G

In this piece, we pull back the curtain on five artificial intelligence myths, revealing through data and real-world examples the truth about how companies are using AI, so business leaders and teams can learn from their peers. Five common AI myths

553RD QUARTER 2022 | SYNAPSE IBM Global AI IndexAdoption2022 New research commissioned by IBM in partnership with Morning Consult CLICK HERE to read

Roboteur Saucecode’s Roboteur RPA solution has turned the market on its head through its low cost and ease of Typicaluse.RPA implementations are long, complex and costly, but Roboteur combines sophisticated features with a user-friendly interface and simple process design. Roboteur has a low cost of entry and doesn’t attract huge consulting, development and maintenance fees, says explains Brian Little, chief operating officer of Saucecode. This means that organisations can automate more processes without incurring the massive costs often associated with RPA.

Saucecode’s professional services are available for customers or partners who don’t have their own skills in-house.

“There is a low-code stack with Z-One, which gives commonality and ability to pull data from wherever it is, and connect all the way up the software pillar to the StarBridge, where you can convert and manipulate data, add in RPA with Roboteur where it’s needed and feed the data back in whatever form is required.”

With StarBridge, Saucecode believes it can deliver reduced development effort while saving money and increasing quality.

The StarBridge brings together all the disciplines associated with software development into one platform. “This makes it very easy to create high-quality software that could include complex features – and it’s 1 000-times faster than normal development.,” Buck explains.

What Saucecode offers Saucecode offers a wealth of solutions based on its Z-One low-code development platform, including Roboteur RPA and StarBridge hyperautomation.Butitgoesfurther, giving customers and partners a viable and profitable business model, professional services and a software as a service (SaaS) offering. The SaaS model works well for service G

Visit Saucecode at the AI Expo, on 19 and 20 September, at the Sandton Convention Centre. For more information on Saucecode and its solutions, go to www.spacepencil.co.uk or email brian@spacepencil.co.uk

artner predicts that RPA software sales will hit $2,9-billion this year, up from $2,4-billion in 2021, at a growth rate of 19,5%. And 2023 is tipped to have 17% growth.

56 SYNAPSE | 3RD QUARTER 2022 providers who supply their own specialty solutions or services.

Z-One is backward-compatible so existing code would never be affected by updates to the platform or to any of the code blocks used to create applications. And, because Z-One is based on open source standards it will work across any platform, with any interface.

But the growth won’t be RPA as we know it: hyperautomation is the name of the game, says Gartner. Organisations will expand their automation technologies to include low-code application platforms, process mining, task mining, decision modeling, computer vision and integrated development planning (IDP).

The robotic process automation (RPA) market is booming – but it is not the entire story by any means, with hyperautomation rapidly becoming a vital part of every IT and business process.

Gartner defines hyperautomation as a business-driven, disciplined approach that organisations use to rapidly identify, vet and automate as many business and IT processes as possible.Saucecode helps organisations quickly move to hyperautomation with Roboteur, Z-One and“RPAStarBridge.hasbecome the entry point for hyperautomation, and forms part of the overall solution,” explains Brian Little, chief operating officer of Saucecode. “What organisations need is a layer that enables things like computer vision, integration with legacy system and the other services required for hyperautomation.

StarBridge Buck has a simple and succinct description of StarBridge: “It is the singularity,” he says. “It is the layer that bridges all the systems and can connect down to everything else in the organisation. It brings everything to the singularity and then RPA or any other tools can be used to do what is needed with the data.

Hyperautomation

Scheduling and management are simplified and reliable, so human intervention is kept to a minimum.

“It gives customers a much better view of their data, enabling them to manage, manipulate and create intelligence out of it.”

The company has also pioneered the concept of swarming – or running several bots in parallel – so customers can employ more bots during demand peaks.

OP ED

“It is a true low-code solution that developers can use to accelerate their application building,” says Barry Buck, chief technology officer of Saucecode.

AUTOMATIONBUSINESS GOE S BEYON D RPA

Bots are developed through a drag-anddrop interface, with a library of preconfigured commands available, so command configuration is repetitive and the modular building blocks used to create bots are reusable.

“Essentially, they can build something once and use it many times; learn once and write anywhere. With a small set of standards, they can now achieve a huge amount of productivity.”

Z-One The Z-One platform gives developers access to blocks of services which can be linked together to produce an implementable file that can be ported between different systems.

58 SYNAPSE | 3RD QUARTER 2022

TELKOM BUSINESS BRINGS

“ The translation service is supported by a network of linguists. In that way, we can find linguists that can cater to each customer’s needs. For now, the translation service is included within the

Enlabeler has a network of digital linguists who are connected to the platform to help provide customers with accurate translations and transcriptions. If a business wants higher accuracy than what the machine transcription service can provide, they can select the Humans-in-the Loop service on the izwe.ai website. Businesses simply need to upload data on the platform, and it is distributed to the digital workforce that will then provide human transcription to get the required accuracy levels.

“The translation service is supported by a network of linguists. In that way, we can find linguists that can cater to each customer’s needs. For now, the translation service is included within the Humans-in-the-Loop component. Businesses can simply upload their documents on the platform that are then translated to the preferred language including the mentioned South African languages as well as Portuguese, Kiswahili, and Dutch.”

elkom Business has partnered data labelling start-up Enlabeler, to introduce izwe.ai, an artificial intelligence-driven multilingual transcription and translation platform that provides businesses with speech-to-text services to create a cost-effective and convenient communication experience for SMMEs. Through izwe.ai businesses can engage directly with multilingual transcription and translation services, said a statement. The platform allows SMMEs to eliminate the manual work by automatically transcribing and translating important information into text with a high level of accuracy.“Every business needs digital tools to remain competitive and you cannot think about digital without mentioning AI. Through this platform, the aim is to enable several different speech-related services. Currently, we are making available transcription and translation services, but we are also developing more refined services that are more technical as it relates to entity extraction, sentiment analysis and other value-added services,” said Stefan Steffen, Telkom Executive, Data Science.

T

As part of the collaboration, izwe.ai provides Humans-in-the-Loop, a service that allows customers to access translation and multilingual transcription services in the various South African languages at increased levels of accuracy, explained the statement.

Telkom said, in a multilingual country such as South Africa, businesses must be able to communicate their offerings in multiple languages. Through the izwe. ai translation component, businesses can expand their reach beyond the Englishspeaking consumers.

Adds Steffen, “The blend of the machine learning and the Humans-in-the-Loop allows us to deliver highly accurate output in a customisable way. The first machine transcription model that we are deploying is our English model. This focuses on transcribing the various South African accents. Telkom Business plans to introduce isiZulu, Afrikaans, Tshivenda, Xitsonga and Sesotho transcription models in the future.”

Humans-in-the-Loop

AI-DRIVEN SMMESTRANSLATIONMULTILINGUALSERVICESTO

” SERVICE NEWS / Read original article here /

Telkom Business said by making services such as izwe.ai accessible, SMMEs can operate efficiently while using affordable services.

thatdocumentscomponent.Humans-in-the-LoopBusinessescansimplyuploadtheirontheplatformarethentranslatedtothepreferredlanguageincludingthementionedSouthAfricanlanguagesaswellasPortuguese,Kiswahili,andDutch

593RD QUARTER 2022 | SYNAPSEPOWERED BY & Our teams also specialise in speech analytics, speaker diarization, sentiment labeling and deliver performance dashboards per project. ENTERPRISE SOLUTIONS FOR END TO END TRANSCRIPTION SERVICES An AI powered transcription & translation platform using ML and humans in the loop to deliver highly accurate outputs. Expert knowledge of contact center, medical & debt collection domains. Expert knowledge of contact center, medical & debt collection domains

INAIGOOGLELAWYERAFRICA

SYNAPSE

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TELKOM BUSINESS BRINGS AI-DRIVEN MULTILINGUAL TRANSLATION SERVICES TO SMMES

3min
page 60

BUSINESS AUTOMATION GOES BEYOND RPA

4min
page 58

HOW TO CREATE BUSINESS VALUE WITH AI

3min
page 56

HYPERAUTOMATION - 360-DEGREE COGNITIVE DPA

3min
pages 54-55

AI FOR SCIENCE IN AFRICA

17min
pages 50-53

HUMAN-CENTRIC INTERACTIONS

7min
pages 48-49

AI THAT CHAMPIONS INCLUSION

4min
pages 46-47

HOW DOES AI FIT INTO YOUR BUSINESS?

5min
pages 44-45

ACCELERATE YOUR DATA SCIENCE AND AUTOMATION JOURNEY WITH NEXT GENERATION AI

3min
page 42

ROI AND EMPLOYEE EXPERIENCE BOOSTED BY ADVANCED AUTOMATION

2min
page 40

THE UNTAPPED POWER OF ARTIFICIAL INTELLIGENCE IN THE RETAIL INDUSTRY

4min
page 38

ARM LAUNCHES CORTEX LAB IN SOUTH AFRICA

6min
pages 34-35

ZINDI RAISES US$1 MILLION IN A SEED ROUND to expand its network of data scientists

2min
page 33

AI START-UP DATAPROPHET RAISES R166M FUNDING

3min
page 30

INTEL TAPS NORTH WEST TVET COLLEGE TO SPARK AI APPETITE

4min
page 28

SA STARTUP AIMS TO GROW AFRICA’S FOOTPRINT IN AI AND DATA LABELLING

4min
page 26

STATE OF AI IN AFRICA REPORT – GLOBAL LAUNCH WITH WEF GLOBAL SHAPERS & UN ITU

3min
page 25

USING AI AND ECONOMICS TO PLAN FOR THE FUTURE

4min
page 21

THE AFRICAN UNION ARTIFICIAL INTELLIGENCE CONTINENTAL STRATEGY FOR AFRICA

5min
page 15

AI EXPO AFRICA WELCOMES TINYML FOUNDATION AS COMMUNITY PARTNER

3min
page 14

Tiny ML

5min
pages 12-13

SWITZERLAND HARVESTING THE FRUITS OF THE AI SUMMER

4min
page 10

TO SCALE YOUR AI BUSINESS, YOUR PRODUCT HAS TO BE BUILT TO SELL

5min
page 8
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