James F. Kenefick - Azafran Capital INSIGHTS Vol. 8 by James F. Kenefick

YOUR EYE ON INNOVATIVE MACHINE LEARNING SOLVING REAL WORLD PROBLEMS

Azafran Capital Partners

INSIGHTS Platforms, to be or not to be... Looking at the stats, predictions and progress (examples throughout this issue) over the past decade it is hard not to jump on the platforms bandwagon. Many prognosticators are going as far as saying go platform or get out of the way. Our team definitely looks for and is favorable towards investments with platform possibilities but we stop short of seeing this trend as a panacea for success. The pace of change in tech is accelerating and as fast as the “incumbent” platform companies listed below so quickly took over most of the Global Top 10 list, another group could usurp them just as quickly or faster. One example we see moving fast from the horizon to the here and now is quantum computing. Changes that used to take decades are now taking years, or less. We don’t see platforms going away, per se, but definitely another strategic element in the investment equation. Stepping back for a moment, the simple Azafran definition of a platform is a connected set of technologies that other people can leverage, that they can cobble together for end to end solution. What you are doing really is fostering an ecosystem where others create value and you then participate in that, take a sliver of that, but the shift to a platform is a huge change. The tall order of extra work comes in the form of documentation, evangelizing, getting partners on board, maintaining all those requirements, the effort cannot be underestimated. The payoff could be huge, but distraction looms around every corner and the discipline of the team, from product, content and finance must be airtight to effectively make the jump to platform speed. Here and now, as we factor in the platform variable, we ask ourselves at each opportunity, what would get the attention of Google, Amazon or IBM, something that could plug right into their platforms and add value. We look as much for companies that can plug into one or more platforms, looking across the opportunity in the context of voice, acoustics and imagery applying machine learning and deep science in health & wellness, IoT and Enterprise spaces.

issue EIGHT issue eight FOCUS At Azafran Capital Partners, we are an early stage venture fund investing in companies ($2M to $8M) that are using deep learning and machine learning, emphasizing voice, acoustics and imagery datasets in the health, wellness, IoT and enterprise spaces. Issue Eight of INSIGHTS focuses on the incredible advance and phenomena of the new platform economy. In just over a decade, the top ten companies in the world have transformed from extraction, manufacturing and other “old world” businesses to those firmly rooted in platform economy dynamics. This is a wave that has been building in various forms for decades, since even before the advent of the Internet, expansion of broadband and ramping of big data, machine learning and deep science. The Azafran team is keenly focused on the platform opportunity, as our investment thesis includes companies that either already have a platform dynamic or have the potential to become integrated into a platform downstream.

Largest Global Companies: 2018 vs. 2008 7 of the Top 10 now platform companies 2018

2008

Powerful platforms have given digital natives from Alibaba to Amazon global reach and towering market capitalizations. While that’s no secret, these platforms raise difficult questions for CEOs of incumbent companies pushing ahead with their own digital transformations: Should they emulate the frontrunners, join forces with them, or not play at all? Not playing may seem risky in a world where “platforms beat products.” Yet building your own platform, in a majority of markets where global platforms are already thriving, may be akin to arm wrestling with a bulldozer. -

McKinsey Quarterly: The Right Digital Platform Strategy

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Platform Use Cases

market PREDICTIONS

As many of the articles in this issue highlight, there is quite a spectrum in the platform play, is it a true platform company? Or just an application, software development kit (SDK), or a service that plugs into or helps form a platform. Many of the companies we see fall into the Software as a Service (SaaS) arena, which are cloud based and either inherently a platform or can be adapted to the model.

Evolution of Platform Economy v1.0 vs. v2.0

In the end, much to consider and this is where Azafran’s amazing team and history building, running and funding companies in the tech world for decades is crucial. Add with our intensive research and partner network, that creates leverage for not only investment in great companies but helping them to grow and thrive in the space. Following are a few use case examples we are looking at or have already invested in at this juncture:

More than 30% of global economic activity — some $60 trillion — could be mediated by digital platforms in six years’ time, according to a McKinsey research report, and yet experts estimate only 3% of established companies have adopted an effective platform strategy.”

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Home and Enterprise AI Assistant that brings the convenience of voice AI technologies to homes & enterprises through Voice-as-a-Service (VaaS), facial recognition from a cloud-based AI Platform; Services on an edge device that covers conversational speech to text and NLP and NLU and even cognitive going against it - could evolve to platform or SDK; Solution that takes visual data hospitals historic and current & puts it in a data lake & allows third parties to create solutions.

NEWSWORTHY… 3 Forces Pushing on the Platform Economy Digital platforms are transforming the way companies do business, but the last few years have shown these platforms still have their own need to evolve. Today especially, digital platforms are navigating a changing landscape.

“The question is: will today’s successful Platforms 1.0 use these new technologies to simply make their current platform model more efficient or will they enable different, more decentralized, more transparent, more cooperative new business models, where governance principles are co-developed by the community,” says Reillier [Launchworks’ Laure Claire Reillier}. Smart contract ecosystems like Ethereum pave the way to enable new organizational models that we call Platforms 2.0. We are at the very beginning of this trend, and probably a few years before widespread adoption, but it is important to keep an eye on this next wave of disruption.” Source: Jennifer L. Schenker, THE INNOVATOR

Regulation: With Facebook and Google in control of 84% of global spending on online ads (excluding China) and Amazon handling close to half of all e-commerce purchases, it’s no surprise that talk of regulating big tech and avoiding data monopolies are frequent topics of conversation. New Technology: Peter Evans, principal in the innovation and enterprise solutions group at KPMG, highlighted two technology areas in a state of change: artificial intelligence-as-a-service and 5/6G, the next-generation cellular networks. Inversion and disruption: “Think of a platform as an inverted firm,” said Marshall Van Alstyne, a professor of information systems at Boston University’s Questrom School of Business. “The value creation is being done by the partners and the users rather than by the firm itself.” Source: MIT Management, Meredith Somers

Once They Were Companies, Now They Are Platform Businesses A survey by Forbes Insights, conducted in 2017, found 31% of organizations consider themselves to be top performers in platform thinking, defined as enabling both external and internal stakeholders to more easily do business with the organization, opening up digital resources to all stakeholders. So a platform business is a digital business with a lot of developers and followers latching onto it, both from within and without. The catch is, of course, a well-functioning platform needs to attract developers and committed followers. To commit their time and energy to building and supporting platform, they have to see the value to their own businesses. Everyone seeks that "network effect" that will amplify their message, and hopefully sales, well beyond their existing bases. -

Source: Joe McKendrick, Forbes

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from the ROAD Highlights from Conferences, Pitch Days, Openings and other Events around the U.S. and World Standard procedure and part of the Azafran team process - we are out on the front lines every week, attending and speaking at conferences, events, pitch days, openings. We are all seasoned entrepreneurs, operators and start up geeks so this part comes easy for us. It also is crucial to delivering on the Azafran investment thesis, one more way we are staying on top of the latest companies, partners, and tech that is hitting the street, and most importantly, helping us to find the best companies that fit our thesis. So, we are excited to add the from the ROAD section to each INSIGHTS, highlighting our favorite events and happenings from the past weeks between issues. Following are a few from the NYC area we just attended and experienced.

RLab Launches at the Brooklyn Navy Yard Martin and Greg attended an AR & VR get together at the Brooklyn Naval Yard last week. The event was part of the launch of RLab – the first City-funded virtual and augmented reality (VR/AR) lab in the country. There were about a dozen companies who had various products in this space. For more info on RLab - link and more on the event link. The one company that stood out for them was Surgarai. Surgarai has a product for surgeons created by surgeons using VR improving patient care and surgical outcomes. This VR product is voice controlled. We already made an introduction to Azafran portfolio company Yobe CEO, Ken Sutton, and have an interest in continuing discussions.

miratech M-FORCE19 @ Hudson Yards James was excited to recently attend the miratech’s M-FORCE19 event in NYC, highlighting their Incubator for startups focused primarily on ML and AI. miratech is a fellow YPO company and have a platform that supports Global 1000 companies for their IT. miratech is looking for innovation and there are many startups looking for dollars and IT partners, so a good fit there.

Azafran Launches New Website - Focus on Content and Connecting with our Ecosystem The Azafran team is excited to launch v2.0 of our website this past week. The new site is aimed at creating an environment where we open a two-way dialogue with our ecosystem of partners, investors, institutions, portfolio companies and the 1,500+ companies on our research team’s radar screen. Out of the gate, we are offering select articles from the past two INSIGHTS editions as well as our Happenings section, which offers key news spotted by our research team impacting our investment focus at the intersection of deep learning and machine learning, emphasizing voice, acoustics and imagery datasets in the health, wellness, IoT and enterprise spaces. Stop by AzafranCapitalPartners.com and let us know what you think!

James noted it was a great experience to see at this conference a mutual 3-4 layer solution in the works. First, there are global companies looking for innovation in technology at one end of the spectrum. At the other end, there are a plethora of startups that are working with transformational innovative tech to solve deep problems and are focused on efficiencies. Then, there are IT partners who can help grow those companies and last, financial stewardship from the investment community for venture capital, which is where Azafran comes into the equation. Overall, a great realization of the role that Azafran fits into which is the $2M to $8M capital stack oppty, alongside our operational experience, all very compelling and encouraging. The day also included the R&D4Equity Pitch event, where entrepreneurs pitch their vision, innovation, and company where Miratech is already assembling the region’s leading investment firms and global enterprises for M-Force19. Then, they invite and combine that with some of the most innovative technology start-ups to pitch their companies to leading investment firms, angel investors, technologists, and corporations. For more information: https://miratechmforce.com/

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Investment Segment Highlight: Cloud Services Component: Easy, scalable access to application solutions and services Description/Definition: As with connectivity, no need to delve into basic definitions on the cloud computing front, but specifically related to our themes of deep tech + machine learning + acoustics and the various components highlighted in this document. From his piece in Forbes on Jan 1, 2019, An Executive's Guide To Understanding Cloud-based Machine Learning Services, Janakiram MSV writes, “ML platforms are one of the fastest growing services of the public cloud. Unlike other cloud-based services, ML and AI platforms are available through diverse delivery models such as cognitive computing, automated machine learning, ML model management, ML model serving and GPU-based computing.” As with “traditional” cloud delivery models of SaaS, IaaS, and PaaS, the ML and AI spectrum span infrastructure, platform and high-level services exposed as APIs, as depicted in the diagram below.

The Azafran Take: The benefits of ML and AI in the cloud are many and well understood. It’s pay-per-use model is good for bursty AI or machine learning workloads. The cloud also makes it easy for enterprises to experiment with ML capabilities and then scale as projects enter production phase and demand increases [source]. The cloud makes intelligent capabilities accessible without requiring advanced skills in AI or data science. In addition, “as AI & ML-based business opportunities expand and become more pervasive, privacy and security professionals in all walks of life are likely to face similar dilemmas of where to draw a line in terms of gathering and retaining personal data and being transparent about its use.” (Security & Privacy considerations in Artificial Intelligence & Machine Learning — Part-6: Up close with Privacy, published on Medium by Manish Prabhu). It is with this consideration in mind that it is important to point out that cloud systems have built in privacy and security systems and algorithms, helping to build guardrails where necessary to protect these elements.

IN THE KNOW How Artificial Intelligence is Empowering Platform Business Models One of the most effective applications of AI is its predictive and prescriptive model that can help businesses optimize their strategy and operations by analyzing customers’ historical data — buying patterns, customer behavior, etc. Prominent social media platforms such as Facebook, Twitter, etc., are using AI and Machine Learning (ML) to curb content misuse and filter fake content, which wouldn’t have been possible manually. Apart from these, there are a plethora of applications for AI in platform businesses like sentiment analysis, speech recognition, text recognition, chatbots, etc. Companies are rapidly deploying AI platform tools and solutions to gain competitive advantage and get maximum benefits of the technology. AI-powered platforms can help companies across verticals enhance their decision-making and increase their revenue. It can help automate simple, repetitive tasks, and thus reduce cost while increasing efficiency. To implement AI, platform businesses need to design and plan their course of action. AI has the potential to enable platform businesses to redefine customer experience by automating decision-making and deep learning. As data continues to flood businesses, AI is becoming a floodgate for platform business models. -

Source: Medium, Zinnov

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Conversational AI Shifts Towards Open Source As reported recently in VentureBeat, there is a strong trend of developers “adopting open source conversational AI and leaving behind closed source alternatives.” For instance, Uber has released an AI library, Plato, serving as a research dialogue system. Prior to that Cisco had acquired the company MindMeld ($125M transaction) and then open-sourced its conversational AI platform. Overall, a majority of the the conversational AI developed over the past three years is open source and the trend is holding, leaving close-sourced solutions with a more limited role in the standard conversational AI stack. Google kicked off the trend, largely, when it open sourced TensorFlow in 2015 and, as demonstrated in the graph to the left, open source platforms like TensorFlow and PyTorch have grown significantly in the same timespan, with closed source options like IBM’s Watson and Amazon’s Sagemaker taking less and less share.

Source: Venture Beat / Google

Feedback, going forward

“The market is driving this shift. Companies are increasingly deciding that many of the AI capabilities they need are strategically important and should be developed in-house. By using open source tools, they can build up their own training data sets and other IP, such as custom integrations with their backend systems. By developing the talent, data, and software to ship AI themselves, these companies control their own AI destiny.” Source: VentureBeat, click here for the full article.

Thank you for the work you are doing in the world and your continued support of Azafran INSIGHTS’ monthly journey into the intersection of deep learning and machine learning, emphasizing voice, acoustics and imagery datasets in the health, wellness, IoT and enterprise spaces. Our intention is to use this as a vehicle to open a dialogue with each of you, together as a group, and we strongly encourage and welcome your feedback. We’ve made feedback/comments simple, please reach out via any of the means below and/or visit our website at AzafranCapitalPartners.com. We will be publishing INSIGHTS at least monthly going forward and look forward to growing this sector together and all the benefits to our respective organizations, as well as those to humanity as a whole that are here today and coming down the road.

voice-techINDUSTRY At a Glance: Top 5 Markets & Global

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