A list of 85 funds investing in Artificial Intelligence and Machine Learning
I. Investing in AI
Investing in AI is not an easy job: AI technologies are black boxes and unless you are able to dig into lines of code they may be inscrutable. Simply looking at proof of concepts might not be enough to really understand the underlying stack behind specific applications, and this represents a big barrier for investors to efficiently allocate their capitals.
Generalist investors found then alternative ways to discern investable companies from the pile of tech-driven companies out there. Instead of looking at the code or the algorithms, they identified proxies for AI technologies, a sort of must-have list to help them cutting out media phenomena from interesting ventures:
i) Impossible problems: if a problem was not addressable before, it is really likely that a machine learning algorithm is behind the proposed solution of that problem;
ii) Data effect: it is common knowledge that neural nets require a lot of data to be trained, and if the startup has a way to create a virtuous data cycle (‘data network effect’) or has access to proprietary data, this is sometimes enough to be deemed as investable;
iii) Team and Patents: the biggest barrier to entry AI/ML is talents and IP. Therefore, if a team is composed of scientists/researchers and has patents (obtained or pending), it would already be a good candidate for an investment even without any revenues. This is driven by top tech companies acquiring smaller startups simply for their ‘brain power’ rather than their actual numbers.
II. So, who are the smart guys with the wallet?
AI specialists are luckily not that naive, but they are able to go much deeper and look behind the veil. As I already pointed out in previous articles, AI investors have different characteristics from more general investors:
i) Deep Capital Base: they usually should have a deep(er) capital base (it is not clear yet what AI approach will pay off);
ii) HigherRisk tolerance: investing in AI is a marathon, and it might take ten years or more to see a real return (if any). The investment so provided should allow companies to survive many potential “AI winters” (business cycles), and pursue a higher degree of R&D even to the detriment of shorter term profits. An additional key element of this equation is the regulatory environment, which is still missing and needs to be monitored to act promptly accordingly. Of course, in saying that, I only refer to the right hand of my AI Classification Matrix, because for narrow AI companies the risk tolerance may indeed be lower;
iii) First-Hand Coding/Engineering Experience: venture capitalists use the help of ‘venture partners’ or ‘scientists in residence’, but AI specialized investors are able to dig into codes and architecture by themselves.
III. List of AI Investors
I then compiled a list as extensive as possible of every investor I read or bumped into over the past months. It looks like there are at least 85 of them:
26 Ventures (NY): a seed investment fund focusing only on machine intelligence companies with 5 investments under the belt;
Andreessen Horowitz (Bay area): nothing to say on a16z because their work speaks for itself. They have though an interesting program called ‘Professor-in-residence’, through which they host CS experts in their fund for a year or so. Fei-Fei Li (the creator of ImageNet) was the last professor joining a16z, after Vijay Pande, probably one of the best biomed scientist of the last decade. They are investors in several machine learning companies, but in particular in what I believe to be the best AI company out there: Anki. Final point: one of their investors is Benedict Evans, who writes a brilliant blog/newsletter you should subscribe to, and they have a podcast page with very interesting insights on AI (check Frank Chen’s presentation here);
Asgard Capital (Berlin): early-stage European investor with few investments done but a strong focus on AI. He is managed by Fabian Westerheide and they are also the main organizers of the conference “Rise of AI”;
Crunch Fund (Bay area): many VCs of this list put money into Crunch Fund back in 2011, and they did with $60M over 200 investments (with only one check exceeding $1M), including x.ai, uBiome, Datos IO, and Marble;
Deep Knowledge Ventures (Hong Kong): Dmitry Kaminskiy and DKV invest in AI, biotech and fintech companies, and they are well-known in the space because they are employing an AI (or at least a sort of intelligence machine) as a director in their investment board. This machine is called VITAL (Validating Investment Tool for Advancing Life Sciences);
Dolan Family Ventures (NY): straight after having acquired Analytics Media Group (AMG), they announced the new fund investing in data, analytics, and technology;
Eclipse Ventures (Bay area): investors in companies like Kindred and Kinema Systems, they prevalently seem to focus on hardware (which it may take the form of robots, IoT devices, semiconductors, etc.);
EQT Ventures (Stockholm): even if EQT Ventures is in business since less than one year now, they were able to help and fund a discrete number on interesting companies such as Verto Analytics, Odeon Technologies, Watty. The fund, which will mainly focus on European companies, raised €566M to be invested in tech startups. Andreas Thorstensson, former Toborrow CTO and now partner at EQT, has also developed ‘Motherbrain’, an AI software that sources investment leads;
Formation 8 (Bay area): to my knowledge, they will not raise any additional fund anymore, but simply keep going doing follow-on investments for a while;
Frontier Tech Ventures (Bay area): formerly known as Rothenberg Ventures, they mainly focus on seed stage investments. In the last year, it has been investigated (and still are I think) by the SEC and other agencies. In their portfolio there are companies like Tissue Analytics, Wade and Wendy and Gridspace;
Giza Venture Capital (Tel Aviv): tech-driven investors in cleantech, healthcare, and semiconductors/IoT, they have invested in Logz.io in 2015;
Glasswing Ventures (Boston): still in the process of properly raising the fund (target at $150M), it is managed by former partners at Fairhaven Capital;
Global Community of Innovation Fund (Tel Aviv): this is the second fund raised byShenzhen-based Chinese technology firm Kuang-Chi Group to invest in AI, IoT, smart cities and robotics. Although Chinese, the fund is located in Israel, but it will invest worldwide;
Innovation Works (Pittsburgh): seed stage investor that helps entrepreneurs also through a series of different programs. Plenty of investments in robotics (e.g., BossaNova), AI software (e.g., Conversant Labs) and life science applications (e.g., Qualaris);
Intel Capital (Bay area): these are their official numbers: in 25 years, $11.8 billion invested in over 1,478 companies in 57 countries; 214 portfolio companies have gone public and more than 403 were acquired or participated in a merger. Impressive;
Kensington Capital Partners (Canada): another big Canadian investor, with a hybrid structure to invest in cutting-edge companies (e.g., D-Wave Systems) but also in other funds as well (e.g., Georgian Partners — see above for details)
Lenovo Capital (Beijing): Lenovo Capital and Incubator Group (LCIG) represents the $500M Lenovo’s venture arm; Face++ is an example of recent company they invested into;
London Co-Investment Fund (London): managed by John Spindler and Capital Enterprise, they have a ‘Seed Enterprise Investment Scheme’ (to invest in early stage AI companies coming out from their member universities and accelerators) and they launched the ‘Turing Initiative’ to co-invest with four other funds monthly in AI-driven startups;
Loup Ventures (Minneapolis): super recent fund launched this year with one investment under the belt (Neurable). Let’s wait and see.
March Capital Partners (LA area): they raised last year a $240M fund with the goal of investing in AI, ML and Big Data technologies. They have already invested in Dojo Madness and co-founded two accelerators in the Bay (The Fabric and the Hive). In addition, one of the founding partners has been hosting an annual summit since a few years now to introduce startups to investors;
OS Fund (NY): founded by Bryan Johnson after selling Braintree to Ebay, it is a VC that invests ‘with the purpose to improve the lives of billions of people around the world for generations to come’. I love the spirit they invest with, and they invested in incredible companies (Emulate, Human Longevity, 3Scan, Viv, Vicarious, Atomwise, etc.);
OurCrowd (Israel): a different type of VC which places initial bets on several companies, and then raises additional money from their network (the crowdfunding part). They invested in Zebra Medical Vision and VocalZoom among others;
pi Ventures (Bangalore): founded by Manish Singhal and Umakant Soni, they just announced their first close ($13M) a few months ago for half of the target fund ($30M). They plan to invest in 18–20 early-stage startups in the following 3–4 years and they just completed their fourth investment;
Quantum Valley Investments (Waterloo, Canada): a $100M (CDN) fund which invests in ‘Quantum Information Science’ companies. The founder Mike Lazaridis is, for the ones who do not know that, the former founder of BlackBerry. The reason why this fund is within the AI list is because of the recent wave of results in quantum computing thanks to machine learning, as well as the potential impact it of quantum computing on AI (a few articles here, here, and here). His last investment has been Cognitive Systems;
Samsung Ventures (Tel Aviv): in addition to pre-existing funds, Samsung has just launched NEXT, a new $150M fund in emerging technologies. They have already invested in MindMeld (formerly Expect Labs) as well as Dashbot and BioBeats;
Schibsted Media Group (London): the Venture and Foresight group at Schibsted is acting as a VC arm for the media colossus Schibsted. Although I don’t think they have done any investment yet, the team is led by azeem Azhar, a former entrepreneur, investor, technologist, and the list goes on. He also writes ‘The Exponential View’, a brilliant blog/newsletter, which you should definitely subscribe;
Serena Data Ventures (Paris): a less than a month old $80M European VC with a focus on data technologies. They recently closed the first investment in Heuritech, a French startup specialized in deep learning technologies. They also teamed up with Firstmark to launch ‘Data Driven Paris’;
StartX (Bay area): the Stanford StartX fund offers to invest 10% of any venture round raised by companies that go through the university-affiliated startup program. They were investors in companies like Gauss Surgical (ca. $13M in the last round) and PredictionIO (acquired by Salesforce);
A final remark: there is a fund which does not make AI investments, but it is an AI investor. It is called ‘The AI VC’, and it claims to be entirely powered by an artificial intelligence engine. THE AI VC has ‘Unicorn Identification Capabilities’ (or at least it claims to have them) and it was created by anonymous founders. Well, even if the reality is that it is simply another RocketAI, I thought it was at least worthy to mention it because the concept is intriguing, regardless of the real value of the fund.
Furthermore, it is useful to notice that AI is sometimes seen as an asset class. Indeed, Smith & Williamson has just launched a fund to “offer investors pure exposure to a concentrated portfolio of companies that derive most, or all, of their revenues and growth from AI”. Well, let’s see what will happen!
IV. Other Works
This is my personal list. I have performed an extensive research work, but I still might be missing someone or misleading some deals or investment strategies (please let me know if this is the case!). However, I believe this is a temporary list because in five years everyone will be investing in AI. I will try to keep this list as updated as possible in the meantime, so check it out from time to time to see if anyone new is on the list.