AI/ML: The eyes of a machine: automation with vision APPLICATIONS: Reducing the impact of ecommerce with AI and ML
IOT: Securing the future of IoT with AI biometric technology TECHNOLOGY: A very human problem: the battle against bias in AI
The technology industry still strives for more gender equality. Here, we celebrate women in AI by looking at the top females innovating in the field
PRODUCTION
ARNETA MARIA GONZALEZ CHARLIE
CHIEF DESIGN OFFICER MATT JOHNSON
HATHAWAY SOPHIE-ANN PINNELL SAM HUBBARD MIMI JUSTIN SMITH REBEKAH BIRLESON JORDAN WOOD CARDOSO CALLUM HOODMARKETING
INDIA BERRY
MARTA EUGENIO ERNEST DE NEVE THOMAS EASTERFORD DREW HARDMAN
PROJECT DIRECTORS KRIS PALMER MIKE SADR BEN MALTBY TOM VENTURO CRAIG KILLINGBACK
People all over the world are impacted by inherent biases that are ingrained in society, and this issue permeates into the world of artificial intelligence. As more AI technologies continue to disrupt our daily lives, it's important that data scientists and technology professionals ensure they know how to detect and recognise bias so the tech doesn’t
limit its impact as the next great innovation.
To reduce bias, it is key to ensure there are people from all walks of life, of all genders, working in the industry to bring more diversity.
Ipsos’s latest Women in Tech Report found 58% of women said that visible role models are one of the things that attracts them to organisations. This is why we celebrate the top 10 women disrupting the AI industry in this issue – to highlight the allimportant role models and hopefully encourage more into the industry.
“To reduce bias, it is key to ensure there are people from all walks of life, of all genders, working in the industry to bring more diversity”
Showcase your values, products and services to your partners and customers at PROCUREMENT & SUPPLYCHAIN LIVE LONDON 2022.
Brought to you by BizClik, PROCUREMENT & SUPPLYCHAIN LIVE LONDON, the hybrid event held between 12th-13th October is broadcast live to the world and incorporates two zone areas of SupplyChain LIVE plus Procurement LIVE in to one event.
With a comprehensive content programme featuring senior industry leaders and expert analysts, this is an opportunity to put yourself and your brand in front of key industry decision makers.
From keynote addresses to lively roundtables, fireside discussions to topical presentations, Q&A sessions to 1-2-1 networking, the 2-day hybrid show is an essential deep dive into issues impacting the future of each industry today.
Global giants and innovative startups will all find the perfect platform with direct access to an engaged and active audience. You can’t afford to miss this opportunity.
Showcase your values, products and services to your partners and customers at FINTECH LIVE LONDON 2022.
Brought to you by BizClik, FINTECH LIVE LONDON, the hybrid event held between 1st-2nd November is broadcast live to the world.
With a comprehensive content programme featuring senior industry leaders and expert analysts, this is an opportunity to put yourself and your brand in front of key industry decision makers. From keynote addresses to lively roundtables, fireside discussions to topical
presentations, Q&A sessions to 1-2-1 networking, the 2-day hybrid show is an essential deep dive into issues impacting the future of each industry today.
Global giants and innovative startups will all find the perfect platform with direct access to an engaged and active audience. You can’t afford to miss this opportunity.
See you on:
November 2022
Massachusetts Institute of Technology
MIT researchers have developed a method for 3D printing materials with tunable mechanical properties that sense how they are moving and interacting with the environment. The researchers create these sensing structures using just one material and a single run on a 3D printer.
This technique could someday be used to create flexible, soft robots with embedded sensors that enable them to understand their posture and movements. It might also be used to produce wearable smart devices that provide feedback on how a person is moving or interacting with their environment.
Programmable materials from MIT could improve the future of robotics
MORE
MORE
“AI bias can be detected and mitigated, but, often, it cannot be completely eliminated, because of intersectionality issues”
A new Gartner survey has found that organisations are adopting AI to help with automation, but multiple challenges still remain
AI Magazine takes a look at enterprise AI translation services helping companies around the world engage with new clients in their own language
AI could contribute up to US$5.2tn to the global economy by the end of the decade, all in the name of sustainability
READ MOREREAD MORE
“Today’s industrial robotics are required to intelligently react and adjust to changes in the immediate surroundings, including safety functions when you have encroachment of the physical workspace”
Bjorn Andersson Senior Director, Global IoT, Hitachi Vantara
Francesca Rossi IBM Fellow and AI Ethics Global Leader, IBM
“Retailers and brands must align their offerings and capabilities with these new consumer expectations that have emerged from the crucible of COVID”
Camilla Freeman Strategic Analytics Consultant AI & Analytics, IBM Consulting
Gartner has recognised Microsoft as a Leader in the 2022 Gartner Magic Quadrant for Cloud AI Developer Services, with Microsoft placed furthest in “Completeness of Vision”.
SINGAPORE
Google employees will soon have access to robots to get chips and soda from company break rooms for them.
The ‘Ok Google’ feature has not been incorporated in the robots yet. In a media report, Google said that they are forming these robots with a sense of responsibility.
This is being done to avoid the robots turning into surveillance machines or answering back with offensive or foul language.
While Google says it is pursuing development responsibly, adoption could ultimately stall over ongoing concerns, which include robots being used as surveillance machines or being equipped with chat technology that can give offensive responses – as experienced in Meta tests amid other examples in recent years.
"It's going to take a while before we can really have a firm grasp on the direct commercial impact," said Vincent Vanhoucke, Senior Director for Google's robotics research.
Google has revealed a package of new investments for Singapore that include opening a new data centre, securing an AI partnership with the government, and expanding its training programme.
Following the second release of DALL·E, users began to report examples of bias. Phrases such as “a builder” only produced images featuring men, while the caption “a flight attendant” produced images only of women.
META
Meta released an AI chatbot, Blenderbot, that anyone in the US can talk with.
Immediately, users all over the country started posting the AI’s condemnations of Facebook, while pointing out that it’s really easy to get the AI to spread racist stereotypes and conspiracy theories.
2010
Understanding different aspects of intelligence
DeepMind was founded in 2010 by Demis Hassabis, Shane Legg and Mustafa Suleyman. Their goal was to create a general-purpose AI that would be useful and effective for almost anything. In 2014, the company joined forces with Google to accelerate its work, while continuing its own research agenda.
In March 2016, the strongest Go player in the world, Lee Sedol, sat down for a game against Google DeepMind’s AI program, AlphaGo. The program defeated him and demonstrated that DeepMind’s AI techniques were potentially advanced enough to be applied to scientific challenges including the “protein-folding problem”. Shortly after, DeepMind established a small team to begin work on protein structure prediction.
The first public test of AlphaFold
2018 saw DeepMind’s AlphaFold win the 13th Critical Assessment of Techniques for Protein Structure Predictions (CASP), successfully predicting the most accurate structure for 25 out of 43 proteins. The methods were then published in the scientific journal Nature, the team was expanded, and work began on an innovative new system.
We take a look at the development that accurately predicts the shape scientists understand the biological
2020 Providing a solution AlphaFold2 won CASP14 by a considerable margin and was recognised as a solution to the 50-year-old “protein-folding problem” by the organisers of CASP. It predicted structures down to atomic accuracy with a median error (RMSD_95) of less than 1 Angstrom.
development of AlphaFold, an AI program shape of proteins, and will help biological processes of every living thing.
In 2021, DeepMind – in partnership with The European Bioinformatics Institute – launched its AlphaFold Protein Structure Database.This gave the scientific community free and open access to the human proteome, along with another 20 model organisms – over 350,000 structures in total.
In the latest development, DeepMind has expanded the AlphaFold Protein Structure Database from nearly 1 million to over 200 million structures, including predictions for most proteins in UniProt. Over 300,000 researchers worldwide have made use of the database to date.
Microsoft’s Director of Growth Innovation and Strategy, Strategic Missions and Technologies, Nick McQuire, is a globally recognised thought leader, former technology analyst and AI-enthusiast with over 20 years of experience.
“I’ve always been interested in how businesses apply new technologies to innovate, change how they work and succeed in their industries. This dates back to writing my Master’s thesis at university and crystallised when I landed my first job working in a tech start-up incubator and early-stage VC in London,” explains McQuire.
Months at Microsoft
Named among the top technology analysts in the world in 2019 and 2020 by the Institute of Industry Analyst Relations
and Technologies division – or SMT–which is its business incubation and scale-up arm.
“What interests me the most about AI is how it will increasingly intersect with many advanced technologies in the future, shaping the future of the cloud in the process,” he adds.
In his current role at technology giant Microsoft, McQuire works in the company’s Strategic Missions
“At the moment, we are focused on four areas collectively shaping the future of the cloud: telecommunications and 5G, Space, Quantum Computing and solutions for the Federal Government. There really isn’t a typical day for me, considering how fast things move. What I really enjoy about working here is the opportunity to work with such an amazing and diverse array of people in advanced tech and innovation. At times, I feel like a kid in a candy store; there are so many things we are working on shaping the future of technology, business and society, it’s really exciting,” says the exec.
Like anyone else, McQuire has had to battle career challenges and personal obstacles to get where he is today, and one of his biggest achievements is adapting to his type 1 diabetes diagnosis in early adulthood.
Keen technologist Nick McQuire shares his passion for AI, the work he does for Microsoft, and how the technology has the potential to transform his own quality of life
“I am looking forward to the arrival of an autonomous system powered by AI for diabetics in the future – a closedloop robotic pancreas, if you like”
McQuire
Now, McQuire takes a keen interest in how AI and other disruptive technologies could transform his own life as the healthcare industry continues to improve with the introduction of automation.
“I am looking forward to the arrival of an autonomous system powered by AI for diabetics in the future – a closed-loop robotic pancreas, if you like. It will span real-time glucose monitoring to insulin injection and will be a system that has learned my patterns of living, has the ability to predict and alert me to future states, and, above all, can co-reason with me on decision making. At the moment, we have elements of this picture, but the technology and suppliers are not there in connecting all the dots. But we are heading in this direction quickly – can’t wait,” notes McQuire.
For his work in technology and AI, McQuire has been named among the top technology analysts in the world and, as a leader in the field, he draws inspiration from his own mentors to support others.
“The biggest thing that I have reacted to in a great leader is the ability to inspire and create conditions for me to produce my best work. I remember someone mentioning to me a while ago, ‘There are many companies grossly over-managed and severely under-led’, which I think sums it up nicely. Whilst I am by no means an expert in this area, I have always kept these elements in my mind over the years from some of my great leaders, managers, and mentors in the past,” explains McQuire.
Equally, McQuire knows the importance of sharing his own lessons learned: “One thing I have learned throughout my career is that change is positive, even though I myself have been fearful of it. At Microsoft, we are encouraged to become comfortable with change. If I were to start again, I would advise to step outside of my comfort zone more, not to fear rejection and do so elevating learning or being a ‘learn it all’, above everything.”
Keen to support others in all aspects of life, McQuire works as a mentor for aspiring early career individuals
and early stage startups, as well as being a judge for the CIO 100, which recognises the most transformational CIOs in the UK each year.
On top of this, McQuire works closely with his own community to encourage sport in younger generations, as he concludes: “I am fairly active around sport in my area, volunteering as a junior rugby coach for our local rugby club. It also gets me active in the community beyond rugby, as well as fundraising each year by volunteering at local running events acting as marshals for several marathons each year.”
“What interests me the most about AI is how it will increasingly intersect with many advanced technologies in the future, shaping the future of the cloud in the process”
» My work at Accenture as a senior leader is to help our clients reach their business outcomes through the use of Data and Applied Intelligence (which includes Artificial Intelligence). This sounds far-fetching and very high level since data at a minimum involves data assessment, management and/or governance (management is actually part of governance), while AI ranges from the application of machine learning to neural networks, deep learning, metaverse etc. At the core of what I do is to involve technology with process and people, the basic trifecta, to understand, evolve, design, build, solve and apply tools, technical solutions, and go-tomarket assets that enable our existing and potential clients to make the best decisions for themselves.
I have been fortunate to be a global leader – as a speaker and panellist – and what I enjoy most is the human interaction, conversations internally and externally, thinking big and inventing, putting the pieces together of a jigsaw puzzle,
ACCENTURE’S SUE TRIPATHI SHARES HER JOURNEY WITH AI OVER HER CAREER AND OFFERS A NUGGET OF ADVICE TO THOSE STARTING OUT IN THE INDUSTRY
collaborating with internal teams, be it strategy and consulting, industry X, operations, song or technology. I think, in this day and age, the confluence of humans and technology, when applied appropriately and without bias, may yet yield the best insights. Saying hello to human connections and gleaning valuable knowledge through those conversations enables when, what and how to apply data and AI.
»
When I began my journey 27 years ago, AI was not part of our lingo in the workplace. I began with data, having led and built data, evaluation, quality, performance, compliance, and audit departments while managing multimillion dollar contracts and learning how to build budgets, pre-sales, and go-to-market assets. During this quarter-century journey, I got certified in organisational change management, lean management, evaluation (programme, developmental, empowerment, quantitative, qualitative) and applied various statistical methods, quality management and project management methods along with AI.
So the transition was very natural, because, by nature, if you are curious, eager, want to be ‘right’ and not afraid
“THE BEAUTY OF LIVING IN THE AGE OF HIGH CONNECTIVITY IS THAT INFORMATION CAN BE SIFTED AT LIGHTNING SPEED”
to confess what you don’t know, you will learn. And in the workplace, it is at times learning by trial and error. There is no playbook that determines continued and sustained success every time. But the core of why I chose to get into the field is to take all these skills and apply it to all communities; that is, apply AI in the socio-technical context – a term coined by the National Institutes of Science and Technology (NIST) in the US. While NIST applies this sociotechnical approach in the context of reducing bias in AI, the practical application of AI, is a universal platform that promotes publicprivate partnerships, enabling people and organisations across the globe to reach their goals.
» As I scour market trend reports, review competitive intelligence and disruptors in the field, some key emerging trends in AI have been around for a while and are in the second iteration of exploring further capabilities. These include: language models, where machine learning determines how phrases, sentences and paragraphs are related, ingesting large amounts of texts and building a statistical model; bias removal in machine learning; natural language processing (NLP), which has already revolutionised how humans interact with machines through understanding the meaning of text
or speech (e.g. Siri, Alexa) and is now in the throes of helping in scaling business operations; reinforcement learning, mimicking how we learn, widely used in robotics, financial trading, games and data science; multimodal learning – that is, learning from sensory input like images, text, speech, sound and video.
» My advice is to know yourself and don’t spend too much time being a perfectionist in everything. Go deep in an area that speaks to you, learn it, practise and eventually become a coach or mentor to others –especially those not in the field. The beauty of living in the age of high connectivity is that information can be sifted at lightning speed.
Ask for help, from senior leaders, your peers and family members.
I have worked and learned new methodologies from experts because I asked, read, stumbled, clarified and applied my learning.
Those starting in the field of AI should ask why they want to be in this field and spend a good part of their life in it. For me, one key driver is promoting the use of AI that benefits humanity, part of corporate social responsibility. Ask yourself what drives you and how you can contribute to this field.
»
I think with COVID-19, we may have fundamentally shifted in our collective thought processes regarding what we want to learn in our careers.
For me, personally and professionally, it is what I want to learn in the time I have while I give due diligence to the task at hand. I am interested in far too many things to learn – the use of AI in music; diversity, equity and inclusion that have implications in hiring practices; access to vaccines and identification of behavioural health conditions; psychographic segmentation of consumers (not easy to do) etc.
At the end of the day, my hope is that in my career, I am contributing to and aligning with key core values, with clients at the centre to improve their experience. Learning is continuous; it is not limited to one’s career. My “hope” is that AI has the potential to help humans make more “equitable” decisions.
“I HAVE BEEN FORTUNATE TO BE A GLOBAL LEADER, AS A SPEAKER AND PANELLIST, AND WHAT I ENJOY MOST IS THE HUMAN INTERACTION”
PRODUCED BY: LEWIS VAUGHAN WRITTEN BY: GEORGIA WILSON
Acelebrated pioneer in the sustainable development of ICT services, CSC is committed to promoting climate targets across its entire operations.
As such, through supporting the green transition, reducing its carbon footprint, and achieving positive green growth, CSC aims to minimise the environmental impact caused by its activities.
The company is working in collaboration with UPM and AMD enhancing its data centre in Kajaani/Finland to offer worldclass energy efficiency. “The key to energy efficiency is for all the energy consumed by data centres to be spent on meaningful activities i.e. computing power with low PUE. And the waste heat generated by the DC operator is used sustainably. This also lowers the energy cost significantly,”
Jukka-Pekka Partanen, Hannu Havanka, and Andrew Dieckmann discuss their collaboration in Kajaani to create a safe, secure, and energy-efficient ecosystem
explains Jukka-Pekka Partanen, Data Center Ecosystem Director in CSC - IT Center for Science.
A modern business park in Kajaani, based on an old UPM paper mill, hosts more than 40 customers including data centres. Kajaani Data Center Program has ambitions to further grow its customer base with both national and international clients.
“We want to create a synergy of benefits within the ecosystem for the data centres and the companies related to them. We also want to expand and deepen the knowledge on invocation of data, machine learning, and artificial intelligence (AI), as well as support Kajaani and the wider Kainuu region’s visibility, reputation work, internationalisation and business,” explains Partanen.
Founded in 1971, CSC - IT Center for Science is a Finnish centre of expertise in information technology. It is owned by the Finnish state and higher education institutions. CSC’s mission is to provide high-quality ICT expert services – internationally – for higher education institutions, research institutes, culture, public administration, and enterprises.
CSC’s Kajaani Data Center Program was created to attract new national and/or international data centre customers to Kajaani, as well as create synergy benefits as part of its ecosystem for the data centres; expand and deepen its knowledge on invocation of data, machine learning and artificial intelligence; and support Kainuu’s visibility, reputation work, internationalisation and business.
Founded in 1996, UPM is a large Finnish forest industry company. UPM provides a variety of products made from wood. Due to the structural changes in paper making, many of the organisation’s paper mill facilities are
empty. UPM aims to implement new ways of operating on these premises. UPM Is dedicated to creating a future beyond fossils.
While its core business isn’t real estate, after closing its paper mill activities, UPM has grown dedicated to developing its real estate into locations suitable for other usages.
Founded in 1969, AMD has driven innovation over 50 years in high-performance computing, graphics and visualisation
technologies–the building blocks for gaming, immersive platforms and data centres.
AMD employees are focused on building leadership high-performance and adaptive products that push the boundaries of what is possible. Billions of people, leading Fortune 500 businesses, and cutting-edge scientific research institutions around the world rely on AMD technology daily to improve how they live, work, and play. For more information about how AMD is enabling today and inspiring tomorrow, visit the AMD (NASDAQ: AMD) website, blog, Facebook and Twitter pages.
Creating a safe, secure, and energy-efficient ecosystem
Working collaboratively, CSC has developed a strong partnership with UPM and AMD to develop a safe, secure and energy-efficient data centre ecosystem to Kajaani.
“AMD believes strongly in environmental sustainability and energy efficiency improvement efforts. We have announced an ambitious goal to achieve a 30 times increase in energy efficiency for AMD processors and accelerators from 2020-2025,” says Andrew Dieckmann, Corporate VP & GM for the Data Center GPU Business Unit at AMD. “We are also dedicated to creating a future beyond
COMPANY: CSC
LOCATION: KAJAANI, KAINUU, FINLAND
Jukka-Pekka Partanen works
at CSC - IT Center Ecosystems and is based in Kajaani. He has been at CSC over 10 years and, before that, spent almost 20 years at Nokia Mobile Phones.
Partanen has been involved in the Finnish data centre industry for the past 10 years, being one of the founds of the Finnish Data Center Forum association and an active board member until recently. In that role, Partanen has worked with a range of colleagues on the global research infrastructure scene, as well as with major international data centre operators and investors.
Most recently, Partanen has been focusing on growing the Kajaani Data Center Ecosystem, where LUMI - one of the most powerful supercomputers in the world - is leading the way. The Ecosystem programme is supported by the city of Kajaani, the Kainuu Region, and local partners.
“The waste heat generated by the DC operator is used sustainably. This also lowers the energy cost significantly”
CORPORATE VP & GM FOR THE DATA CENTER GPU BUSINESS UNIT, AMD.
TITLE: CORPORATE VP & GM FOR THE DATA CENTER GPU BUSINESS UNIT
COMPANY: AMD
LOCATION: GREATER SACRAMENTO
As general manager of the Data Center GPU team, Andrew is responsible for the overall business management, Product Management and Strategy, Product Marketing, Business Development and Business Operations teams. Andrew has spent his 20+ year professional career defining and building products for the data centre market, including compute, memory and storage solutions that help to power many of the leading cloud services and data centre technology platforms. The data centre GPU team at AMD is focused on providing the world’s leading accelerator solutions, powering the world’s biggest AI clusters and HPC supercomputers enabling new scientific discovery and AI advancements that will provide tools, capabilities and innovation previously not thought possible.
“AMD believes strongly in environmental sustainability and energy efficiency improvement efforts”
fossil fuels. Sustainability is at the core of our company,” adds Hannu Havanka, Vice President of Real Estate in UPM Kymmene Oyj.
As part of their joint efforts on this front, the three are supporting the EuroHPC Joint Undertaking, which harnesses and develops top-of-the-range supercomputers to boost Europe's scientific excellence and industrial strength, and to support the digital transformation of the EU's economy.
One such supercomputer is located at Kajaani. “LUMI was ranked third on the Green500 list, published on 30 May 2022. The supercomputer was built on world-class environmental sustainability and costefficiency criteria. It helps the European ICT sector to drive the greener, more costefficient operations necessary to reach the EU’s ambitious climate targets and pave the way for the green transition. With the smallest possible environmental burden and lowest cost for European taxpayers, LUMI is beyond compare,” says Partanen.
The LUMI system leverages a coherent CPU and GPU interconnect using AMD Infinity Fabric™ technology, which offers high-speed, low-latency interconnect, a unified memory for applications and boosts efficiency.
“Applications using HPL code leverage this coherent interconnect to run the serial portions of the code in the CPU, with the parallel portions of the code on GPUs ensuring an efficient use of both the high performance of the AMD EPYC™ CPU cores and AMD Instinct™ GPU compute units. This also helps intelligently manage the data movement, thus simplifying programmability and easing the adoption of GPUs for HPC applications,” explains Dieckmann.
He continues: “The LUMI system also has a downstream NIC directly attached to each
of the Instinct MI250X GPUs that operates at 25Gbps, permitting low-latency messaging from GPUs to off-node, helping to overlap computation and communication, thus efficiently using the system and improving overall performance. These innovations are critical to deliver a system that can deliver 152PF of peak and 62.7 GFlop/W, achieving the #3 spots in both the Top500 and Green500.”
Partanen adds: “The LUMI supercomputer is a really unique data centre investment in Kajaani. It is a top modern and efficient project that was completed in the agreed timeframe and budget. Kajaani is a proven location suitable for data centres and data centre ecosystems. As a proof, LUMI data centre has already won three international competitions in the most innovative project category.”
Hannu Havanka is the Vice President Real Estate of UPM Kymmene Oyj, a Finnish-based listed forest company acting globally. Mr. Havanka is an experienced realestate professional and has, through his career, worked as a developer, investor and corporate real estate in global perspective including investments and workplace development projects.
HANNU HAVANKA
TITLE: VICE PRESIDENT REAL ESTATE
LOCATION: VANTAA, UUSIMAA, FINLAND
“We are also dedicated to creating a future beyond fossil fuels. Sustainability is at the core of our company”
HANNU HAVANKA VICE PRESIDENT REAL ESTATE, UPM KYMMENE OYJ
A unique data centre ecosystem with world-class solutions and services, CSC, AMD and UPM strongly believe in the capabilities of the Kajaani site and the opportunities it can provide to drive business growth.
“We have a proven data centre ecosystem at Kajaani. There is plenty of room for those in the data centre business sector to grow in our park facilities, where we offer world-leading speed-to-market delivery – thanks to the brownfield site – and a smooth permitting and planning process,” says Havanka.
As both interest and visibility grow in the Kajaani area, CSC is dedicated to growing businesses related to its programme, finding new operators that can benefit from hosting a part of their footprint in the Kainuu region, Finland.
Such benefits and opportunities of operating in the Kainuu region include:
• Cost efficiency - inexpensive electricity and reimbursement from waste heat utilisation.
• World-class references - such as the LUMI EuroHPC project.
• One of the most eco-effective data centres in the world - small carbon footprints and surplus amounts of renewable energy are in increasing demand.
• Data - extremely effective connection.
• Supply of HPC environments - CSC has strong knowledge alongside a track record of reliability and excellence in this area.
• Unique ecosystem - offering professional partner expertise, dedicated education, and RDI.
“We want everyone to understand the opportunities and benefits that can be gained from housing their data centres at our base in Kajaani. Our data centre ecosystem with the LUMI EuroHPC supercomputer as its public reference significantly strengthens Finland's – and especially Kainuu’s – role in the European and global high-performance computing ecosystem,” says Partanen.
He concludes: “At the same time, it will strengthen the national and international status of Kainuu’s ICT and Data Center services. Kainuu now has the opportunity to take advantage of the new prospects and build its data centre ecosystem to a new improved level. Now is the perfect time to attract new operators, to establish their presence as the world’s best data centre location.”
CSC:
AMD:
As automation tech continuously improves to meet the changing needs of manufacturers, we look at the impact machine vision will have on the industry
WRITTEN BY: CATHERINE GRAYOpening the door to automation, the use of artificial intelligence (AI) has enabled industrial robotic applications to process large amounts of images and data in volumes that were previously not possible. Now, with the introduction of machine vision, robotics and automation within manufacturing are set to transform the industry yet again and its increasing affordability means it will be making a huge impact on a number of companies, regardless of size.
Historically, data acquisition within computer vision has been limited by the manual interpretation of captured image data. However, the introduction of deep learning –a type of machine learning based on artificial neural networks – has generated data-driven models that could replace handcrafted preprocessing and feature extraction.
The evolution of computer vision started with basic neural networks being able to recognise handwritten numbers from zero to nine. Today, with the advancement of GPUs and large datasets, we can accurately identify just about anything from people to dogs to household objects in video.
“Vision is essential for an organism to understand the world around it beyond touch. However, it's not a simple process. More than 50% of the cortex – the surface of the human brain – is devoted to processing visual information. This demonstrates the volume of processing resources that need to be devoted to it, and it’s the same in robots and other artificial intelligence. Vision is very challenging but adds enormous capability,” notes Eleanor Watson, IEEE AI Ethics engineer and AI Faculty at Singularity University.
The technology, when applied to robotics, enables machines to perceive their surroundings, recognise individuals and objects, understand context, discern the attributes of things, and freely navigate environments.
With these abilities, machine vision can enable the contextual awareness required for robots to work closely alongside humans and adapt to changes in the environment by applying AI to learning new work patterns.
“Apart from the most common use cases – using visual information to check on the status of quality, position or inspection of tasks – machine vision’s value is flexibility and contextual awareness. Today’s industrial robotics are required to intelligently react
PRASHANT NATARAJAN VICE PRESIDENT OF STRATEGY AND PRODUCTS, H2O.AI.“AI cloud solutions can bring state-ofthe-art deep learning to solve industrial computer vision problems, utilising the innovative AI methods built on top of the modern cloud technology stack”
and adjust to changes in the immediate surroundings, including safety functions when you have encroachment of the physical workspace,” explains Bjorn Andersson, Senior Director, Global IoT at Hitachi Vantara.
Without machine vision technology, machines could not know where to find objects to pick them off a conveyor or out of a box, could not perform quality control on stock to check for damage or missing pieces, and couldn’t recognise a catastrophic error to notify a human colleague.
“Advanced machine vision allows for greatly improved mobility and independence. Traditional industrial robots live in a literal cage and cannot easily be repositioned, let alone reposition themselves. Modern robots take themselves wherever they anticipate the greatest need, with minimal oversight or correction necessary from a human guide,” comments Watson.
with affordable machine vision
Affordability has always been a problem within the robotics industry. Those who have historically been able to afford the technology have been leaps and bounds ahead of their competitors, whereas those who haven’t been able to afford it lag significantly behind.
“We’ve passed an inflexion point where machine vision is now available, affordable and fast enough to be used in practice. Data, computing power and affordability are the three main ingredients for a step function improvement,” explains Andersson.
“Today’s industrial robotics are required to intelligently react and adjust to changes in the immediate surroundings, including safety functions when you have encroachment of the physical workspace”
BJORN ANDERSSON SENIOR DIRECTOR, GLOBAL IOT, HITACHI VANTARA
The global machine vision market size was valued at US$13.23bn in 2021 and is expected to expand at a compound annual growth rate of 7.7% from 2022 to 2030. The increasing demand for quality inspection and automation in different industrial verticals is likely to continue driving the market. Additionally, the need for vision-guided robotic systems across the automotive, food and beverage, pharmaceutical and chemical, and packaging segments is expected to fuel the market growth.
“IoT brought us the data and the continuous improvement of computing hardware, while algorithms gave us computing power. Add to that the affordability to deploy it essentially everywhere, then it’s enabling fundamental changes in how we work,” he adds.
On top of this improved affordability, machine vision often utilises deep learning technology to elevate it further. The pair go hand in hand: when you add deep learning algorithms, it gives robotics intelligent vision, bestowing them with the ability to recognise objects, thus taking robotics to a new level of efficiency.
“Machine vision is one of several areas where deep learning models not only outperform other machine learning approaches, but are able to achieve accuracy comparable to humans,” notes Prashant Natarajan, Vice President of Strategy and Products at H2O.ai.
“Moreover, using modern hardware, deep learning models can produce the predictions within milliseconds, allowing real-time applications for machine visions. Such applications include recognising the surrounding environment and making decisions accordingly. That enables a wide range of tasks to be automated in industrial robotics,” he continues.
Looking to the future, the opportunities for machine vision within robotics are closely linked with the private cloud, which, according to TCS, is expected to continue maturing.
“Computer vision’s preference for the private cloud is all about latency and physics. In most applications that interact with humans, latency is noticeable when you go beyond a few milliseconds. You will start to
notice if the time to gather the image data, send it somewhere to do the processing and then deliver the result back takes longer than that,” comments Andersson.
However, Natarajan outlines the importance of a private cloud as it enables all the benefits of cloud technologies without privacy and security concerns: “It is crucial for computational-heavy tasks like computer vision, where availability of the appropriate hardware to train and
execute the models fast is crucial. Together with resource scalability, private clouds enable the fast adoption of cloud-based AI technologies that are already tailored for computer vision applications.”
He concludes: “AI cloud solutions can bring state-of-the-art deep learning to solve industrial computer vision problems, utilising the innovative AI methods built on top of the modern cloud technology stack.”
WRITTEN BY: JOSEPHINE WALBANK
PRODUCED BY: LEWIS VAUGHAN
The drive towards net-zero CO2 has ignited innovation across every industry sector, but none more so than the world’s data centres.
Today, the dual demands of high performance and improved sustainability standards mean the risks for data centres are higher than ever, as those that do not match the pace of the rest risk being left behind.
In conversation with David Craig, the CEO of Iceotope, we discussed how Iceotope’s cooling technologies offer a long-term, seamless aid to sustainability targets.
Readily scalable, holistic solutionswhat Iceotope brings to the cooling market Iceotope’s precision immersion cooling solutions are a prime example of data centre technologies aligning with the ever-expanding and ever-changing nature of the industry.
“I would describe our difference as: we definitely set out to understand the customer’s problem and create a solution that fits,” says Craig.
“If you look at the liquid cooling space today, there are two very dominant technologies in cold plates and tank immersion. Our approach was to say, ‘This cannot just be a technology; this must be a solution that is scalable and serviceable’.
“So, by being in racks and chassis, we fit customers’ integrator models, and we're incredibly serviceable – actually achieving slightly better serviceability than air cooling.”
Iceotope’s high-performance cooling solutions are precisely engineered to help data centres achieve the dual demand of rapid growth done sustainably
Alongside this, the technology also offers a simple, efficient way for data centres to improve their sustainability standards.
“We use a fraction of the raw materials, and we use a fraction of the amount of dielectric coolants – it's cheaper, it's simpler, it's lighter. We don't need to worry about spills, we have superior thermal performance, and we’re able to deliver a better holistic performance to the customer overall.”
Craig explains how Iceotope’s technology makes heat management infinitely easier.
“Today, everything to do with heat in computers is a problem to manage. And actually, adopting our technology removes that altogether, because you're not really cooling anymore. What you're actually doing is capturing heat. So, computers run better, they run in more places, they run more inexpensively, but also, you can do useful things with heat, depending on where you are.
“Fundamentally, what we have done is deliver a scalable, serviceable, deployable
“ I think this is one of those times that occurs once in a generation, where incrementalism becomes potentially quite dangerous”
DAVID CRAIG ICEOTOPE TECHNOLOGIES
solution which – by being able to retrofit and scale down to one, as well as up to many –means that the customer doesn't have to go for this ‘all or nothing’ type of approach.”
For Craig, we are only at the cusp of the change that the data centre industry will witness. He asserts that, in the very near future, the usual quick-fix air cooling methods will not be able to keep pace with the technology being deployed.
“I genuinely think that, in five years’ time, we will be in the midst of an avalanche of change. People will be accelerating towards those more holistic understandings and solutions – and customers will be driving that demand much more significantly.
“The young generation, who really care about sustainability, will be budget holders.”
TITLE: CEO
LOCATION: ILKLEY, ENGLAND
David Craig is CEO of Iceotope.
Having worked his way up through Unisys and IBM in global procurement roles, he moved on to lead the commercial integration of Prudential Assurance and Scottish Amicable. Moving on from the merger to turnaround a leading British refrigeration company and start a consultancy, which he sold three later to Amey. He was then invited to join a late 1990s tech boom disaster, which then became Scotland’s third
As the younger generations rise to positions of higher influence, ESG as an industry priority will only increase. By this point, as Craig asserts, the companies that have not successfully met these standards will struggle to survive, simply because they waited too long to innovate.
Sustainability and high performance - the competitive edge of immersion cooling
As you can imagine, an instrumental factor driving Iceotope’s technological innovation is sustainability. Iceotope’s step away from air cooling has allowed it to achieve green standards that knock its competitors out of the water.
“Everything in data centres, today, has been designed to be cooled by air.
“As a result, it's pretty low density and horrifically inefficient – servers typically run at pretty low utilisation rates to prevent them from throttling. So, they use up large amounts of land, as well as huge amounts of electricity and water resources.”
In comparison, Iceotope’s technology can improve environmental performance across a number of key areas.
“If you just think about data centres, if our technology was deployed across the majority of the industry, we would reduce the usage of billions of litres of water. The industry consumes enough water to hydrate 10% of the world's population today – that could be returned to people who could drink it.
“However, the impact becomes broader when you step right outside it. If the whole industry got about 30% more energy efficient, you're dealing with the levels of 50MT-of-carbon-a-year reduction.”
To that end, Iceotope’s technologies deliver sustainable cooling in adaptable, bespoke and highly practical solutions. They offer cooling solutions that can be tailored to meet each site’s specific needs, balancing sustainability with optimal performance.
“We have a whole set of benefits that the technology itself delivers: less space, less cost, less energy, and less water – and people get that.
“The key thing that we do to help is actually engage with, listen to and deliver the solutions that they need, as opposed to saying, ‘This is what we've got, here's your fridge, where would you like it? It’s white’. Instead of trying to bend them to us, we are bending us to them.”
“When you do that, you are much more aligned with the customer. It means that we listen to them, and we adopt their thinking into what we develop.”
The global potential, ready to be unlocked Improving cooling solutions may sound like a small step, but alleviating the restrictions imposed by air cooling can reap huge rewards. It promises to not only help data centres achieve a more efficient way of
I really think there is a moral case for growth, but we have to conduct growth in a moral way”
operating, but to drive higher performance across countless global industries.
“As businesses start to understand how much cheaper and more effective life can be in a chassis-based liquid cooling world, they will accelerate towards it. You paint a picture of a world in which you are using a quarter of the physical space to do your processing, plus half of the energy and virtually no water.”
Beyond the immediate benefits that this will bring in terms of sustainability and business costs, adopting advanced cooling solutions also has the power to transform the way that data centres are run, modelled and implemented, in an increasingly technologically-advanced world.
“If your processes are completely silent or you're not deafening your staff, you can run data centres in city centres. You can run them on the 33rd floor of an office block. You can transform the type of land that you use – using more brownfield than greenfield – fibre can be where the people are, and the data can be processed as close to people as possible.”
As well as the practical advantages, this shift opens up huge possibilities for data and its utilisation.
“We can accelerate the rate and pace at which we adopt AI and those kinds of technologies. And, if you think about the onset from there, adopting AI in healthcare will massively enhance the rates of survival and early diagnosis; it will massively reduce the amount of time that nurses waste on triage and A&E.”
And that’s just one example. This technology can enhance all industries, expanding their capabilities, increasing their efficiencies and making our vision of smart cities a reality.
“
In five years’ time, the young generation who really care about sustainability will be budget holders. And I think you'll see a whole set of people struggling to survive, because they just waited too long to innovate”
“The more that we can transform perceptions of high performance computing from a wacky thing in the corner to a mainstream high-performance that’s powering smart cities, autonomous vehicles, advanced healthcare, advanced retail, then you start to really move forward.”
Alongside this, another benefit of Iceotope’s technology is that servers can be made much smaller than conventional air coolants.
“If they're much smaller, they're also much cheaper with fewer precious metals,
fewer raw materials, fewer component placements, and fewer inventory movements,” Craig explains.
“Actually, the whole supply chain becomes much simpler and much cheaper, while also adding value and margins back in for those who make the devices.”
According to Craig, data centres at large continue to use a completely extractive model.
power
“Most of what has been done is quite incremental – and that's understandable, because there's a lot of risk in the business; you don't want your data centre to fail or to go down, and changes are expensive.”
“It’s totally understandable that you have that kind of constraint sitting there. But I think this is one of those times that occurs once in a generation, where incrementalism becomes potentially quite dangerous, in the sense of actually what the impact could be on our competitiveness. Because there is no
DAVID CRAIG ICEOTOPE TECHNOLOGIES“ You cannot cost-reduce your way to success. You have to manage costs carefully, but if you're just cutting, you won’t have the space and time for innovating. And it's the innovators that drive things forward”
doubt that ESG is going to be a very, very strong factor in the future.”
In short, adopting sustainable technologies is no longer a choice.
“There's a rising generation of people half my age and less, who really passionately care about the environment. They will be making buying decisions and they will be consumers. And I think they will hold greenwashers to account.
The global drive for sustainability –and the responsiveness of the global data centre industry – has effectively set a pace of change. If not followed, data centres are risking nothing less than the future of their business.
“If we stay in this incrementalist, safe world where we're not joining the dots, it's a dangerous place. Joining the dots and grabbing that vision is what the companies who’ll make a serious impact on the future will be playing towards.”
So, as we look to a hugely promising future for data centres and their increasing role within economies, businesses and societies, Craig has high hopes that the demand for innovation will actually make data centres a solution to aid the world’s net-zero targets.
“I really think there is a moral case for growth, but we have to conduct growth in a moral way.
“We have an obligation to go beyond the balance sheet and do these things because they will make fabulous, fabulous differences to our future. So more technology, moving faster, please. And I think that's why those who remain afraid to change will be caught in a set of perfect storms.”
There is no doubt that COVID-19 negatively impacted a number of industries, but one industry that was hit especially hard was retail. As the virus spread across the world, a number of countries enforced strict lockdown measures in an attempt to control its proliferation.
These lockdown measures meant that many non-essential retail stores (such as clothing, music and shoe stores) were forced to lockdown, with those that had the capability moving to online shopping only.
In April 2020, the sales of non-food products in the EU dropped by 23.8%. Worldwide, total retail sales volumes fell by 1.9% compared with 2019, the largest annual fall on record. Despite this fall, online sales
rose to a record high of 33.9% as a share of all retail spending.
Undoubtedly, the pandemic highlighted the need for artificial intelligence (AI) and machine learning (ML) as the technologies have the ability to help shoppers locate the right product, strengthen retail supply chains and boost personalisation for brand differentiation.
“AI provides opportunities to elevate brand engagement and interaction via immersive experiences. ML enables higher levels of personalisation and the delivery of relevant content, product, offers, etc. based on shopping behaviours, purchases and the collection of zero-party data,” said Terri Gaughan, Director of Enterprise Strategy and Architecture at Cheetah Digital.
A modern network must be able to respond easily, quickly and flexibly to the growing needs of today’s digital business. Must provide visibility & control of applications, users and devices on and off the network and Intelligently direct traffic across the WAN. Be scalable and automate the process to provide new innovative services. Support IoT devices and utilize state-of-the-art technologies such as real-time analytics, ML and AI. And all these must be provided with maximum security and minimum cost.
This is the power that brings the integration of two cloud managed platforms, Cisco Meraki and Cisco Umbrella. This integration is binding together the best of breed in cloud-managed networking and Security. cisco.com
“There are no major setbacks once the technology is in place and a sound strategy is developed to be executed, though it does require specialised resources and monetary investments” she adds. “It’s also important to understand which processes need automation while ensuring that there isn’t a lack of quality data. Creating adequate infrastructure, ensuring seamless integration and making sure there are enough skilled resources are also critical.”
In the wake of COVID, shoppers now expect everything to be connected all the time with shopping being a fast and efficient process –with ease being a top priority.
“Retailers and brands must align their offerings and capabilities with these new consumer expectations that have emerged from the crucible of COVID,” notes Camilla Freeman Strategic Analytics Consultant AI & Analytics at IBM Consulting.
Research into this shift in expectations by IBM found that consumers now see digital tools as a necessary part of the shopping experience. Consumers expect stores to be digitally enabled with brands and retailers supporting hybrid shopping journeys, which blend physical and digital channels.
“If data is not turned into information and knowledge that can be leveraged to make better decisions, it will not provide any insight. For example, if you think about the impact of weather on your outfit, the data would be the information that it is raining. Without taking this data and turning it into actual insight – understanding that the rain will make you wet –you will be unable to decide to wear a raincoat and boots.”
Interestingly, these new expectations are found to be especially true for Gen Z, who use hybrid shopping more than any other generation. Reacting to this shift, retailers are rapidly increasing their adoption of AI technologies to improve customer experience and keep up with other industries.
“Although AI usage has been increasing over a number of years, this has historically been largely with regard to improving customer experience and operational efficiency. However, during 2021, 4 in 5 retailers surveyed by IDC1 viewed AI as being essential in each of eight key areas – although the figure for current usage was much lower with fewer than 2 in 5 in all bar one category. Digital commerce was the most popular of these areas with 43% of retailers currently using AI and a further 40% planning to use AI in the next 12 months,” says Freeman.
“IDC research suggests that only two years ago, retailers viewed use cases for AI as being more visionary and less critical in the near term. Since the pandemic and the dramatic shift toward digital engagement, in addition to highly publicised supply chain challenges, AI is now becoming a high priority among retailers,” she continues.
“RETAILERS AND BRANDS MUST ALIGN THEIR OFFERINGS AND CAPABILITIES WITH THESE NEW CONSUMER EXPECTATIONS THAT HAVE EMERGED FROM THE CRUCIBLE OF COVID”
Happily, the introduction of this technology is set to have a positive impact on the climate. As ecommerce has grown and more people turn to online shopping due to COVID, consumer behaviours have changed, leading to a dramatic increase in sales.
Many big companies started offering next day delivery along with a number of perks, meaning many consumers expect goods to be delivered on the same day and to return them without cost. Although digital technology has enabled features such as these, they do not come without a cost.
The rising online shopping trends have a significant impact on our environment. This stems from the production and packaging to the shipping of goods all over the world. Now, ecommerce is responsible for a huge portion of global emissions.
By 2030, the estimated environmental impact of ecommerce logistics will be much higher in the largest 100 urban areas worldwide. The delivery car fleet could reach 7.2 million vehicles by the end of this decade, and total emissions caused by parcel and freight shipping are forecast to generate 25 million tonnes of CO2.
“AI can demonstrate how to properly use a particular product to reduce consumer frustration. From a logistics perspective, ML could make recommendations on how to reduce the number of packages required to complete an order by combining units bought. There is also the possibility of creating virtual showroom experiences and personalising recommendations based on previous purchases/browse data,” explains Gaughan.
Fashion is a US$2.5tn industry, producing 10% of global carbon emissions, 20% of global wastewater, and vast biodiversity loss. Consumers are demanding change and forcing sustainability in fashion as a requirement, not just a trend or empty promise.
“BY LEVERAGING ML-BASED FORECASTING ALGORITHMS, FASHION INDUSTRY PLATFORMS ARE ABLE TO PROVIDE ACCURATE DEMAND FORECASTS IN AN EFFICIENT WAY”
VIKRAM MURTHI VP OF INDUSTRY STRATEGY, O9 SOLUTIONS
While acknowledging the importance of AI and ML, Freeman also suggests that AI and ML are not the sole means of sustainably transforming the online shopping experience: “These approaches can go some way to making the online shopping experience closer to the experience in store and reduce the return rate accordingly. But there is more that can be done outside of the AI space, including the development of sustainable packaging.”
Growing expectations – as well as fuel costs – have also put enormous pressure on the global supply chain, which has now reached a breaking point. If data generated by ecommerce is not turned into information and knowledge that can be leveraged to make better decisions, it will fail to provide insights to help improve supply chain challenges.
“By leveraging ML-based forecasting algorithms, fashion industry platforms are able to provide accurate demand forecasts in an efficient way, removing the tribal knowledge and manual effort from the equation,” comments Vikram Murthi, VP of Industry Strategy at o9 Solutions.
AI platforms for supply chain management and ecommerce will be able to use data to provide insights on upcoming risks or opportunities. This may include demand or supply alerts such as demand surge, orders exceeding forecasts, shipments arriving later due to bad weather or port delays, procurement alerts and production alerts.
Murthi concludes: “By investing in nextgeneration platforms powered by AI, fashion companies will not only be able to bridge the gap between demand and supply, but they will also be able to sense demand and predict consumer preference shifts in order to better align their supply, absorb rising materials and shipping costs while eventually reducing waste and better using the planet’s resources.”
The digital password as we know it quietly marked its 60th birthday earlier this year. Back in 1962, MIT professor Fernando Corbató came up with the system in order to allow four colleagues to access the then-new IBM 7090 in a “time-sharing” environment. For context, it would be another seven years before ARPANET – which would eventually morph into the internet and World Wide Web – was turned on.
After six decades, the traditional password is in decline. Growing security risks brought about by the introduction and growth of the Internet of Things (IoT) mean a new breed of AI-powered biometric identification services is going to be needed to keep the world safe. Your first pet’s name is no longer required. Instead, expect faces, fingers and voices to be called upon more often as we navigate the new networks.
Prove – a US-based provider of authentication services – surveyed 2,000 consumers and asked them what they felt about passwords and how they used them. Less than 10% offered biometric authentication as their preferred way of proving their identity in the future, while 30% were happy to continue with traditional passwords.
The world needs an IoT future, so it’s time to forget your password – for good. A new breed of AI-powered biometric security measures is required
the future of IoT biometric technology
However, the survey also noted that three-quarters of respondents agreed biometric authentication is more secure than a traditional password. A move away from traditional passwords is essential now the Internet of Things (IoT) means the world is awash with opportunities for cyber criminals.
Domestic IoT devices have the potential to collect and access a large amount of personal information about users and sensitive data relating to their environment, says Steven Furnell, IEEE Senior Member and Professor of Cyber Security at the University of Nottingham: “Devices, such as smart speakers and TVs, are often linked to the accounts that consumers use on other devices. The difference is that on these other devices they are more readily protected against unauthorised use.
“On the smart device people may set them up initially and forget that they are essentially ‘logged in’ all the time,” explains Furnell. “Without further precautions, this may mean that others can come along and access other content via the linked account, such as cloud-synchronised contacts, schedule information, and photos.”
ROLAND ATOUI
FIDO sheds AI light on IoT cybersecurity blind spots “The more points of entry to a network, the more potential there is for hackers to break in, so it’s not hard to imagine how quickly the vulnerabilities stack up in an IoT system,” says Roland Atoui, Security Certification Secretariat with FIDO Alliance.
“As IoT matures, there’s a desperate need for standardisation to help organisations remove these cybersecurity blind spots costing them billions – not least in reputational damage.” Atoui’s concerns are echoed by research from Gartner, which predicts that 45% of organisations worldwide will have experienced attacks on their software supply chains by 2025, a three-fold increase from 2021.
“As IoT matures, there’s a desperate need for standardisation to help organisations remove these cybersecurity blind spots costing them billions”
People are often less mindful of the security risks posed by IoT devices, as they do not necessarily think of devices as storing and communicating data in the same way as traditional computing devices, says Furnell.
“If you ask people to characterise a smart device, they are likely to do so by referring to it being ‘online’ or simply ‘connected to the Internet’. However, the wider implications of what this means – and what the device may be collecting and sharing – is often lost.”
AI biometrics need to stay simple says SailPoint Biometrics done well can nudge people towards the adoption of good security practices without imposing an additional burden, explains Mike Kiser, Director of Strategy and Standards, SailPoint. Facial recognition on mobile devices involves simply looking at the phone or screen, for example, something done in the course of regular interaction. Users are not asked to adopt a new approach.
“In this way, security is improved, all while accelerating authentication as compared to some older approaches,” explains Kiser. “For IoT devices, biometric authentication might be a more appropriate form factor as well: not every IoT device will have a screen or keypad — biometrics could use a fingerprint or voiceprint reader to authenticate the user rather than adding additional, unwieldy technology.”
IEEE’s Furnell agrees this level of convenience is essential if biometrics are going to be adopted quickly. No one wants to type a password into a smart TV or speaker, whereas being recognised by face or voice is a natural way to interact with each type of device, he says.
“Users control the smart speaker via voice commands and are typically sitting in view of a smart TV when they use it. The process of being authenticated by the device becomes transparent and non-intrusive from the user perspective. As a result, it feels more usable or frictionless.”
Presentation attacks involve an impostor using an artefact of some kind to mimic an individual who has been enrolled in the system.
An attacker may seek to modify or intercept the data output from the sensor. A previously captured sample might be replayed, or a captured biometric sample could be substituted with biometric data of a different individual at enrolment.
An attacker may target data during transmission, or in storage by the biometric system. For example, a biometric reference in the enrolment database could be modified to include the biometric features of an impostor.
The enrolment process could be subverted, allowing the acceptance of inappropriate enrolment data. Alternatively, if an
enrolment record contains biometric data of two individuals, this may allow one to impersonate the other.
Attacks against the underlying IT on which the biometric system runs are certainly feasible and must be considered in cases where the assets being protected are of significant value and where the attackers are relatively sophisticated.
All systems are vulnerable to denial of service attacks. In the case of a biometric system, this will divert subjects to the exception handling system. It is therefore important that this fallback system is no less secure than the biometric system.
All security systems are vulnerable to an attack by a trusted system administrator or operator. Due to the level of access and trust held by such people, insider attacks on a biometric system can take any of the forms outlined above.
“On the smart device, people may set them up initially and forget they are essentially ‘logged in’ all the time”
“Security is improved, all while accelerating authentication as compared to some older approaches”
We may not see the kind of password inflation that has emerged in the past 20 years – according to the Prove research, respondents had six “go-to” passwords which are used across the broad range of accounts in their lives – but there is unlikely to be one biometric to rule them all.
“It is useful to have multiple solutions because the same biometrics are not equally suited to different devices,” says Furnell. “For example, face recognition would not work well with smart speakers. At the same time, there will be some classes of IoT device that do not have any suitable sensors as standard, such as a smart thermostat or washing machine; neither could be relied upon to have a camera or microphone.”
In these cases, devices would be required to work together, with the biometric captured on one being shared with another in a secure, trustworthy manner.
Humans have been feeding thousands of years' worth of data into AI algorithms. Now, we are required to correct the bias that infected these datasets
WRITTEN BY: GEORGE HOPKIN
Artificial intelligence (AI) does not have opinions. There are no baked-in beliefs it would like to champion, no self-evident propositions it's itching to share with the world. Instead, AI relies on and learns from huge datasets generated by humans.
And while nobody consciously includes bias in a database, over time it has crept in. Without human intervention, AI could be reinforcing some damaging societal bias, limiting its impact as the next great technical innovation.
AI needs data that is collected and labelled by data scientists, and algorithms defined, trained and tested by
AI developers, according to Francesca Rossi, IBM Fellow and AI Ethics Global Leader. And that’s where the problems often start.
“People are biased – mostly in an unconscious way – so it is possible that, without a careful methodology, such biases are embedded in both the data and in any other developer’s decisions in building an AI system,” says Rossi. “We devote significant effort to tools, methods, education and impact assessment processes to ensure that AI bias is detected and mitigated by our developers, consultants, sellers and all other IBMers in their respective roles.”
A company-wide approach is overseen by a centralised governance structure, with the IBM AI Ethics board providing guidance and support throughout.
The IBM playbook goes beyond fairness and also covers other trustworthy AI pillars, such as transparency, explainability, robustness, and privacy, explains Rossi. “In this way, we ensure that the AI systems we build and deliver to our clients can be trusted and have a positive impact on the relevant communities.”
Alteryx says executives need to know what AI and ML mean Although AI can be trained to perform many tasks without human interaction, it’s essential those designing the system fully understand any possible defects before AI amplifies them, says Alan Jacobson, Chief Data and Analytic Officer at Alteryx.
“While analysts and data scientists often build machine learning (ML) models, those in executive positions and other leadership roles frequently need to understand the
results. Explainable AI (XAI) offers significant transparency and trust advantages over black-box models.
“These interpretable models ensure that ML, AI algorithms and the reasoning behind a specific result are more understandable to people who don't have a data science background.”
For example, an ML model trained using a collection of financial data to help approve or deny a loan applicant could use XAI to provide not only the answer but also detail how and why it arrived at its response, explains Jacobson.
“Rather than believing AI will simply deliver the correct autonomous insights, it’s imperative to fully understand how and why it arrived at the answer it did,” says Jacobson. “The importance of explainable AI goes beyond making the wrong decision.”
Accenture examines “what is fair” to tackle AI bias There is still a lot to be done by people as well as machines. Identifying and prioritising which biases to address requires experts from a wide range of disciplines to develop and implement technical improvements, says Sue Tripathi, Managing Director, Global GTM, Data, AI at Accenture.
“To complicate matters, making ‘fair’ decisions to minimise bias implies there is a uniform and standard way in defining ‘fairness’, which is not the case,” explains Tripathi. “How then do we define ‘fairness’ and also measure it?”
Those involved in codifying definitions of fairness and attempting to provide ‘fairness’ metrics highlight the complexities involved. Various academic centres of AI, highlight cases where determining the “fair” percentage in their algorithms may not actually represent the real world in terms of pay or health equity practices, for example.
“Should an organisation set different decision thresholds for different groups, based on race, gender, social, and economic factors?” asks Tripathi. “Is there a single universal definition of fairness or metrics that can be applied?”
Democratise data to do away with AI bias, says Alteryx Upskilling in-house experts in data literacy and analytics is also a crucial preventative measure to avoid the pitfalls and ethical issues around deploying AI, explains Alteryx’s Jacobson.
“Cloud-based and on-premise platforms with drag-and-drop – or no-code/low-code – and automated ML capabilities will shorten the learning curve for many users,” he says. “Additionally,
“DECREASING BIAS OVER SOME PROTECTED VARIABLE MAY INCREASE BIAS OVER ANOTHER. THIS IS WHY INCLUSIVENESS, TRANSPARENCY AND EXPLAINABILITY ARE FUNDAMENTAL”
“MAKING
We asked the AI-powered art creator Craiyon to draw a picture of “a CEO being served a drink by a flight attendant”. Craiyon (formerly DALL·E mini, an AI model that creates new images from a text prompt) complied and you can see the results here.
Sadly, this AI artist seems to have an outdated concept of gender roles in the air and on the ground, with women in uniforms serving men in suits.
OpenAI, the AI research and development company behind DALL-E, are onto this and taking it seriously. Earlier this year, developers introduced a new technique to ensure generated images more accurately reflect the diversity of the world’s population.
The company reported a 1,200% increase in the number of results that would pass as a more acceptable representation of a diverse world.
platforms that offer guided paths and recommendations for model usage, while providing clear data lineage trails and notes for explaining data points, will provide the level of interpretability and explainability needed to help democratise data science understanding and accessible AI implementation across your domain experts.”
But even the experts working around the clock on these problems say we shouldn’t expect bias to be entirely removed from artificial intelligence any time soon.
“AI bias can be detected and mitigated, but often it cannot be completely eliminated, because of intersectionality issues,” says IBM’s Rossi. “While decreasing bias over some protected variable, one may increase bias over another protected variable. This is why inclusiveness, transparency and explainability are so fundamental in AI models.
“These properties allow AI users to know what kind and how much bias is still present in the AI system, and to make an informed decision on whether it is appropriate to use the AI system in the deployment environment. It is therefore essential to have a global approach to AI ethics and not just focus on a single issue.”
Human judgement and processes are still needed to ensure AI-supported decision-making or prediction is fair and unbiased, says Accenture’s Tripathi.
She concludes: “A confluence of humans and machines working together offers many prospects that may well lead to a common language and standardisation in how best AI could operate in multiple contexts, while reducing bias.”
We’ve known about the gender gap in the technology industry for years. The problem has become a fierce talking point, with the movement to encourage more women to enter STEM fields leading to the creation of many nonprofit organisations focused on supporting women in these industries.
This drive to encourage more women into STEM is promising and, quite frankly, a giant step in the right direction.
To shed light on the incredible contributions women have been making in the artificial intelligence (AI) industry, we take a look at some of the top women innovating and challenging the field’s status quo.
The technology industry still strives for more gender equality. Here, we celebrate women in AI by looking at the top females innovating in the field
Dr Joy Buolamwini uses art and research to illuminate the social implications of AI. She founded the Algorithmic Justice League to create a world with more equitable, accountable technology, and her TED Featured Talk on algorithmic bias has over 1.5 million views.
As a creative science communicator, she has written op-eds on the impact of AI for publications like TIME Magazine and the New York Times. Buolamwini serves on the Global Tech Panel convened by the VP of the European Commission to advise world leaders and technology executives on ways to reduce the harms of AI.
Shivon Zilis has spent time on the leadership teams of several famous innovative AI companies, including OpenAI, Neuralink, Tesla, and Bloomberg Beta. At Tesla, Zilis served as a project director for Tesla, Inc.'s Autopilot product and chip design team. In 2015, Zilis was listed on the Forbes 30 Under 30 list for venture capital.
She is the youngest board member at OpenAI and at Neuralink, and works on high-priority strategic initiatives in the office of the CEO, reporting directly to Elon Musk.
Ex-VP of Engineering at NVIDIA, Claire Delaunay has 20 years of experience in robotics and autonomous vehicles, and is an expert at building and working with high-performing teams while iterating at high velocity.
At NVIDIA, Delaunay was responsible for the Isaac robotics initiative, leading a team to bring Isaac to market for roboticists and developers around the world. Prior to joining NVIDIA, Claire was the director of engineering at Uber after it acquired Otto, the startup she co-founded.
With all this experience under her belt, she now works as a board advisor and investor.
Microsoft’s Kate Crawford is a leading scholar of the social and political implications of artificial intelligence. Over her 20-year career, her work has focused on understanding largescale data systems and AI in the wider contexts of history, politics, labour, and the environment.
Crawford is currently a Senior Principal Researcher at Microsoft Research. The AI specialist has also published a book titled, Atlas of AI: On Power, Politics and the Planetary Costs of AI.
The
supply
tackle
channel, supply, logistics, and global
through direct
the
The
control of supply
meet customer
Heena Purohit is a Product Leader for IBM’s Corporate Accelerator programme, where she helps some of the best IBM teams discover, validate, and, ultimately, build new products and businesses.
Prior to that, she launched and grew products that involved using data and AI to help customers across a variety of industries transform their operations while driving tangible business outcomes. Purohit’s products spanned across a variety of advanced AI technologies such as Conversational AI (digital assistants, speech transcription, and synthesis), NLP, computer vision, and pattern recognition.
Google’s Kamelia Aryafar is the Head of Retail and Consumer Solutions Engineering at Google Cloud AI, where she leads applied AI and engineering teams focused on solving retailers’ problems.
Aryafar holds a PhD and MSc in Computer Science from Drexel University. To further contribute to the industry, the AI expert has published several papers in scientific journeys and speaks frequently at academic and industry conferences focusing on advancing the field of AI, ML, technology and women in STEM.
Accomplished AI entrepreneur, advisor and investor, Allie Miller has a rich background in AI, ML, humancomputer interaction, technology, cognitive science, analytics, product and user experience, consumer insights, startups, and venture capital.
Miller has previously worked for AWS and IBM as Global Head of Machine Learning Business Development, Startups and Venture Capital, and Lead Product Manager at IBM Watson, respectively. She is the youngest ever woman to build an AI product at IBM – spearheading large-scale product development across computer vision, conversation, data, and regulation.
As CEO of AI cyber company
Darktrace, Poppy Gustafsson has led the company through significant growth and global expansion. For her work, Gustafsson was named Vodafone’s Woman of the Year for Technology and Innovation in 2020, Tech Businesswoman of the Year at the UK Tech Awards 2019 and won the Veuve Clicquot Business Woman Awards 2019.
Also in 2019, the CEO – along with Darktrace’s CTO – was awarded an OBE (Officer of the Order of the British Empire) for services to cybersecurity.
Anna Patterson is, as you’d expect, an accomplished AI leader. As a VP of Engineering at Google, she architected the search serving system that increased the index size by over 10x at the time of launch, helped Android scale from 3 million to over a billion phones. While she was working in Google's Android organisation, Patterson oversaw the Google Play division, which included Books and Search, Recommendations, and Infrastructure for scaling up Android from 40 million phones to over 800 million phones.
Gradient Ventures was launched by Alphabet and Patterson together, with the aim of investing in early-stage artificial intelligence start-ups.
Patterson also co-founded Xift, later Cuil, a clustering-based search engine, and Recall, the first history-based search engine, both acquired by Google.
Patterson received her PhD in Computer Science from the University of Illinois and was an AI Research Scientist at Stanford University.
Showcase your values, products and services to your partners and customers at FINTECH LIVE LONDON 2022.
Brought to you by BizClik, FINTECH LIVE LONDON, the hybrid event held between 1st-2nd November is broadcast live to the world and incorporates three zone areas of FinTech LIVE, Crypto LIVE plus InsurTech LIVE in to one event.
With a comprehensive content programme featuring senior industry leaders and expert analysts, this is an opportunity to put yourself and your brand in front of key industry decision makers.
From keynote addresses to lively roundtables, fireside discussions to topical presentations, Q&A sessions to 1-2-1 networking, the 2-day hybrid show is an essential deep dive into issues impacting the future of each industry today.
Global giants and innovative startups will all find the perfect platform with direct access to an engaged and active audience. You can’t afford to miss this opportunity.
See you on:
1st-2nd November 2022
Rana el Kaliouby is an Egyptian American scientist who co-founded Affectiva, a software company that builds AI with an understanding of human emotions, cognitive states, activities and the objects people use. Having spun out of MIT Media Labs, Affectiva created a new technology category: Artificial Emotion. Dedicated to the ethical development and deployment of AI, el Kaliouby is part of Partnership of AI and the World Economic Forum’s Council of Young Global Leaders, driven by her passion to advocate for standards that ensure data privacy, while mitigating both data and algorithmic bias. El Kaliouby has published a memoir titled ‘Girl Decoded’, which shares her journey and provides an intimate view of her personal transformation as she follows her calling – to humanise our technology and how we connect with one another. The talented technologist is a rarity in both the tech world and her native Middle East: a Muslim leader and CEO; a woman in charge in a field that’s still overwhelmingly white and male.
