YOUR EYE ON INNOVATIVE MACHINE LEARNING SOLVING REAL WORLD PROBLEMS
Azafran Capital Partners
INSIGHTS Voice, Acoustics and Imagery Upgraded to Mission Critical Prior to COVID-19 crisis, business markets and technology were driving adoption of these modalities - now they are fast becoming Mission Critical. The function and intelligence around voice, acoustics and imagery have been developing and used, in some shape or form, in the last 200K years. With the inﬁnite spectrum these modalities offer, one can easily view the keypad/board as a step back, albeit a necessary one, for the computer age. For the past 3.5 years our journey has taken us across the globe, attending nearly 100 events, visiting tech hubs from Helsinki to Denver, Toronto to Pittsburgh, Tel Aviv to Berlin and dozens of points in between. Along the way meeting thought leaders, institutions, incubators, and searching out companies/technologies that ﬁt the Azafran Investment Thesis. This journey has been a key ingredient to the fabric and curation of Azafran INSIGHTS, which now has over a dozen issues published. This road less traveled enabled us to ﬁnd companies focused on our target modalities, with machine learning / deep science solutions matching ACP’s target market dynamics (see Page 3). Concurrently, our research team, guided by our Partners’ average 30 years of industry experience, created our research database (KESAR - tracking 1,800+ AI/ML companies worldwide via 348 attributes), the foundation of our data-driven approach.
The Tech Perspective Over the the past ﬁve years, progress has turned exponential as we build on the decades of work laying the networks, scaling the Internet, computing, programming, storage, using and analyzing stores of data unimaginable even a decade ago. One of the key elements holding back progress for AI / machine learning was access to the rich data tapestry that voice, acoustics and imagery offer. In effect, turning the single dimension modality of text into a complex and intelligent multi-dimensional data landscape. One watershed moment was Amazon’s launch of Alexa in 2015. The voice interface spread like wildﬁre to over 100M households in just a few years, Google, Apple and others followed. This rapid consumer adoption of voice pushed developers and manufacturers to deploy voice as an integral component of their product development strategy. Alexa alone is forecast to be $18B to $19B in revenue next year. (Continued on Page Two) Azafran INSIGHTS © Azafran Capital Partners 2020 - All Rights Reserved
SPECIAL REPORT SERIES Part Two
part two FOCUS Azafran Capital Partners is 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, and IoT / enterprise markets. Part Two (of Three) of our Special Report Series focuses on the technology, markets and research that form the basis of the Azafran Thesis, now taking into account new global realities we are experiencing personally and professionally. This Series will also be accompanied by a podcast with Azafran partners Marty Fisher and James Keneﬁck discussing the main topics of each Issue.
Humankind is now facing a global crisis. Perhaps the biggest crisis of our generation. The decisions people and governments take in the next few weeks will probably shape the world for years to come. They will shape not just our healthcare systems but also our economy, politics and culture. We must act quickly and decisively. We should also take into account the long term consequences of our actions. When choosing between alternatives, we should ask ourselves not only how to overcome the immediate threat, but also what kind of world we will inhabit once the storm passes. Yes, the storm will pass, humankind will survive, most of us will still be alive — but we will inhabit a different world.” -
Yuval Noah Harari, FT.com, March 19, 2020
Special Report Series, Part Two - Page One
YOUR EYE ON INNOVATIVE MACHINE LEARNING Voice, Acoustics and Imagery SOLVING REAL WORLD PROBLEMS from the FRONTLINES Move to the Forefront (Continued from Page One) Imagery as a modality has had a similar ﬂashpoint when compared to voice and acoustics over the past ﬁve years. Apple’s acquisition of Emotient for their facial recognition technology and Facebook’s acquisition of Oculus embracing augmented reality / virtual reality (AR/VR) technologies were pivotal moments as imagery has rapidly come to the fore of mainstream developer and manufacturing product roadmaps. As opposed to other hot topic technologies like robotics and drones - which have not yet been widely productized - the voice, acoustics and imagery modalities have been broadly accepted into our home and work environments. In 2017 the Azafran team chose voice, acoustics and imagery as a focal point for our Investment Thesis. And, almost overnight, this is the new environment further accelerated by the COVID-19 crisis. From physical access/entry, to activating hardware, software, and sensors, all segments of industry are prioritizing this transition. The developed world is now a connected world. This will accelerate exponentially as new algorithms, alongside the ﬁelds of TinyML (Machine Learning with TensorFlow) and embedded AI make networks more effective and efﬁcient. At the same time, a new generation of analogue / digital low power sensors are moving computing to the edge.
AI in healthcare to grow in preparation for future public health risks (Pitchbook) AI has been deployed in the detection, diagnosis and treatment of COVID-19 and we believe the virus demonstrates the need for improved AI in healthcare. Several AI models were able to detect the outbreak of COVID-19 in Wuhan based on natural language processing of government healthcare reports and news releases, including those of VC-backed startups BlueDot and Metabiota.
SPECIAL REPORT SERIES Part Two
The accuracy of the models’ predictions of COVID-19’s spread weakened over time but proved to be valid alerts. Over the past three months, numerous AI-powered diagnostics have been developed based on CT scan data, including those from Huawei, Ping An and Alibaba. These approaches claim to reduce the time to analyze CT scans for COVID-19 diagnosis to mere seconds.
In the next ﬁve years, and further accentuated by the repercussions of the COVID-19 crises, billions of handsfree, always‐on, sensing devices running on battery-power will assist us in our daily lives at home and at work: playing music on request, controlling our home’s temperature and lights, alerting us to danger, monitoring the wear and tear of factory equipment, even continuously monitoring our health. Our team identiﬁes these technologies as foundational and mission critical elements of our investment strategy.
Leveraging our Experience & Passion to the Early Stage The challenge and opportunity with early stage companies is capital and experienced leadership. This where Azafran’s Partners bring critical expertise to every company in our portfolio because they have launched and scaled dozens of companies. Add to that our global network of partners, companies, and experts, which are integral elements of every investment we make. Whether it's building out a team, productizing and scaling company’s technology, or building / expanding channels and partnerships, this is our specialty and defensible advantage in the market. The third and ﬁnal installment in this Series will focus on this topic.
Informed, Experienced Research The COVID-19 crisis has increased the need and speed to market for companies in the Azafran thesis, our research team and database (KESAR) are now tracking 1,800+ companies against 348 separate data points, which serve as the foundation of our Thesis: Investing in companies that are using deep learning and machine learning, emphasizing voice, acoustics and imagery datasets in the health / wellness and IoT / enterprise markets. See Page Four of this report for more details on KESAR and Azafran’s Research. Azafran INSIGHTS © Azafran Capital Partners 2020 - All Rights Reserved
Artiﬁcial intelligence is typically presented in Hollywood movies as a human-hating robot in a doomsday scenario. However, in the current Covid-19 pandemic, AI has emerged as the superhero that is saving humanity from disease and greatly reducing the number of deaths globally. AI researchers around the world have, over the past few years, engineered drastically new capabilities in health care, just in time to combat the novel coronavirus. Over just the past few years, there have been major advancements in AI technologies, in areas including natural language processing, speech recognition, data analytics, machine learning and deep learning, and a wide range of applications from chatbots to facial recognition. These technologies have affected all industry sectors and are now being deployed as powerful weapons against Covid-19.” — Andy Chun, South China Morning Post, March 2020
Special Report Series, Part Two - Page Two
Market Focus and Use Cases
from the HEADLINES
Within our modalities and tech focus (AI/ML/Deep Science), we look for companies delivering solutions into the Health / Wellness and IoT / Enterprise markets. Below is a high level update on three of our priority market areas:
AI Is Changing Work — and Leaders Need to Adapt
Healthcare: In the areas of voice, acoustics and imagery we are currently looking at a range of companies that will change how we use, administer, apply and think of healthcare going forward. Some important use cases that we are investing in are: ● ●
Solution that listens for vocal patterns such as pitch, tone, rhythm, volume, that serve as powerful data points - "vocal biomarkers." A hardware/software platform that “sees” and processes your breath patterns, feeding the results into a machine learning platform for diagnosis of respiratory diseases
The type of output and data from these applications help healthcare and clinical teams diagnose a variety of conditions — from chronic respiratory disease (COVID-19) to cognitive disorders, early cancer detection (esp. melanoma) and even heart attacks. Internet of Things (IoT): From software platforms making neural networks more efﬁcient to devices/sensors providing self-contained functionality with low/no cloud use, the application and implication of this segment is signiﬁcant. A dual primary beneﬁt here is a reduction in cost and increase in performance of microchips doing machine learning inference “at the edge” as well as the development of middleware allowing a broader range of applications to run seamlessly on a wider variety of chipsets. Azafran has already invested in this segment via ACP1 (Fund One) and here are some use cases that we are investing in ACP2: ● ●
AI-Driven optimizer to make Deep Neural Networks faster, smaller and energy-efﬁcient from cloud to edge computing. A new and unique data type which encapsulates more information than traditional tensors, vectors and ﬂoating points, learning more from 2D and 3D images. Solution which reduces the power consumption of any wireless chip to a fraction of the original chip - applicable to wireless sensors, data loggers, and consumer electronics.
Enterprise: This broad category with lots of participants deploying solutions from HR & talent to customer care, when viewed through the lens of ACP’s modalities, it narrows the ﬁeld to fewer, high value opportunities. Prior to COVID-19 we saw great opportunity in the hospitality arena, which may return to pre-COVID levels, but until then our team is focused on solutions using imagery for security and voice for automation and efﬁciency at point of sales and call centers.
NEWSWORTHY… A Massive Opportunity Exists To Build ‘Picks And Shovels’ For Machine Learning (Forbes) “Many multi-billion-dollar companies have been built by providing tools to make software development easier and more productive. Venture capitalists like to refer to businesses like these as “pick and shovel” opportunities, a reference to Mark Twain's famous line: “When everyone is looking for gold, it's a good time to be in the pick and shovel business.” AI is the most important “gold rush” of our era. To date, the picks and shovels required to support this ﬁeld remain underdeveloped. This represents a massive opportunity for entrepreneurs.” - Rob Toews in Forbes, March 2020 Azafran INSIGHTS © Azafran Capital Partners 2020 - All Rights Reserved
(Excerpt from HBR) As AI is increasingly incorporated into our workplaces and daily lives, it is poised to fundamentally upend the way we live and work. The stakes are high. AI is an entirely new kind of technology, one that has the ability to anticipate future needs and provide recommendations to its users. For business leaders, that unique capability has the potential to increase employee productivity — by taking on administrative tasks, providing better pricing recommendations to sellers, and streamlining recruitment, to name a few examples. Whether it is workers who are asked to transform their skills and ways of working, or leaders who must rethink everything from resource allocation to workforce training, fundamental economic shifts are never easy. But if AI is to fulﬁll its promise of improving our work lives and raising living standards, senior leaders must be ready to embrace the challenges ahead. Source: Harvard Business Review, Martin Fleming, March 24, 2020
Coronavirus is prompting companies to adopt AI call center solutions The future of contact centers was always going to be AI-powered messaging: “Consumers prefer communicating on SMS, WhatsApp, Apple Business Chat, and other messaging channels, and brands see better business results compared to the old world of voice,” said LivePerson. “But this shock to the system will accelerate brands’ embrace of remote contact centers and work-from-home solutions for their agents. Brands that do this will be able to maintain a sense of normalcy throughout periods of crisis because they’ll be communicating on the same channels consumers use to talk to family and friends — without all the mess of routing voice calls to remote locations, where agents are dealing with kids or pets in the background.” Weekly
- Source: VentureBeat | AI Special Report Series, Part Two - Page Three
Azafran Research - KESAR
data and research TRENDS
Combining Experience and Timing with Deep Research
Tableau - AI Moves from the Abstract to the Actionable
Our quantitative research team has created a proprietary data repository for our relationships, business contacts and companies, a database we call KESAR (Hindi for Saffron). KESAR is comprised of many categories of data, surrounded by a suite of best-in-class software tools (see below) to analyze the core data and generate output reporting and visualizations that our team employs.
One of the hardest parts about AI projects is identifying the questions you want to ask.”
Today we track 1,800+ AI/ML companies worldwide broken into select categories, markets, themes, industries and metrics. We track 348 attributes across the 1,800+ companies, some examples include geography (97 attributes), technology focus (9), modalities (voice, imagery, machine learning, etc.), as well as tech tools (162). There are already 617 companies that ﬁt our initial investment criteria and enterprise value. We will invest in the best 15 to 25 companies in ACP2. Highlights of the data categories tracked are below, as well as the best in class tools we currently employ:
deep tech funds
ACP KESAR DATABASE
Rachel Kalmar, Data Scientist & Staff Software Engineer, Tableau
Taking a collaborative approach can unveil the parts of a business decision that are best suited for AI and the parts that need human intervention. As Richard Tibbetts, Principal Product Manager for AI at Tableau explains, “The emergence of AI does not mean that an algorithm will tell you how to run a business. It will be the domain experts that help ensure that AI is adopted and trusted in an organization.” Increasing collaboration between technology experts and domain experts encourages knowledge sharing on both sides. In an article from McKinsey Quarterly, Cameron Davies, Head of Corporate Decision Sciences at NBCUniversal shared a use case that involved annual forecasting. They decided to build and surface a set of machine-learning algorithms to help augment the process. In the early stages, they brought in a researcher to contribute to the project. He ended up becoming an evangelist in the business units and trained other people how to interpret the recommendations. Source: Tableau Data Trends 2020
voice-acoustics-imagery & AI/ML Industry Snapshot At a Glance: Top 5 Markets & Global
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Special Report Series, Part Two - Page Four
A Year of INSIGHTS
Below is a quick snapshot of some of the covers from Azafran’s INSIGHTS over the past year - please let us know if you would like PDFs of any issues - just email us at firstname.lastname@example.org and we’ll send along.
Azafran INSIGHTS © Azafran Capital Partners 2020 - All Rights Reserved
Volume 13 of Azafran Capital Insights.