Unsupervised Investments (II): A Guide to AI Accelerators and Incubators

A list of 34 accelerators and incubators for AI startups

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“a fixed-term, cohort-based program, including mentorship and educational components, that culminates in a public pitch event or demo day.”

From this definition is clear that the authors looked at different traits to characterize and distinguish different programs from each other. The key features can actually be summarized as follows.

‘Accelerators = Business synopsis’

Academic research, even if not unanimously (check this beautiful work by Yu, 2016), seems to confirm with data the value of those programs (Hochberg, 2015). Studies prove that accelerated companies reach milestones faster (Hallen et al., 2014), have a higher probability to raise further funding with respect to angel-supported startups (Winston-Smith and Hannigan, 2015), and that have even spillover effects on the entire entrepreneurial ecosystem (Fehder and Hochberg, 2015).

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  • AI Nexus Lab (NY): an intensive program run by Future Labs (NYU) and ff Venture Capital. During the program, the startups can get access even to NYU AI faculty, which means for some lucky entrepreneurs to potentially have the chance to work along side with Yann LeCun. They have just announced their first cohort: Alpha Vertex, Behold.ai, Cambrian Intelligence, HelloVera, Klustera;
  • Alexa Accelerator (Seattle): powered by Alexa Fund in collaboration with Techstars, this accelerator has the goal of advancing voice-powered technologies. As one of the Techstars programs, startups receive $100k of funding upon acceptance in convertible notes, as well as $20k in exchange for 6% of equity (with a ‘Equity Back Guarantee’ clause, which basically gives the founders that chance to lower up to zero Techstars’ equity position within three days from the end of the program). Historically, it seems that Techstars companies go on to average more than $2M raised after the program;
  • Allen Institute for Artificial Intelligence (Seattle): the AI2 is expanding its incubator for AI companies to let in outside startups, after the first two spinouts — Kitt.ai and Xnor.ai. Companies will get up to $250,000, six months of free office space, help with sales and marketing and access to 70 AI researchers and PhDs;
  • Bosch DNA (Berlin): the Indo-German accelerator targets startups in different areas which uses enabling technologies such as deep learning, analytics, AI and machine learning to go from “Lab to Market”. The Nurture program lasts for 18 weeks: the first 3 weeks are dedicated to idea validation, a short 10-days bootcamp, and mentors meeting. Phase II is about 10 weeks mainly running through customer validation, while finally phase III concerns pitching preparation for final demo days. Usually 5 Indian and 5 German startups are selected;
  • Botcamp (NY): run by Betaworks’ team (very good media investors), it is a program specifically designed for conversational interfaces. A $200,000 uncapped, safe note with a 25% discount is offered to companies;
  • Cog Labs (London): a new embryonic accelerator launching this year and focusing on AI and cognitive sciences. No public information available up to date, so stay tuned for more as soon as further public announcements will be released;
  • Comet Labs (Bay area): I have already mentioned Comet Labs Research Team in a previous article on AI investors, but they are also product builders. They will run different ‘labs’ starting from this April. The first one just announced is the Transportation Lab, with two more to follow. The first cohort includes 7 (impressive to me) companies: Nomoko; AutoX; Oculii; Deep Vision; Minds.ai; Point One; Syntouch. They do not provide an investment by default but rather on a case by case basis (in the form of a warrant, a convertible note, or a discounted equity investment);
  • Creative Destruction Lab (Toronto): this is a program longer than usual, but aimed to support entrepreneurs with an MVP with mentorship on how to raise a round, develop the go-to-market strategy and deal with legal, accounting, and other business processes. In addition to the ‘standard’ AI/ML track, they also recently launched the first Quantum machine learning program in order to attract people who want to work at the intersection between AI and Quantum Computing. They will be supported by three machine learning focused VCs (Bloomberg Beta, Data Collective and Spectrum 28). Participants will need to be in Toronto for the technical training portion of the program (but full relocation is not required) and can opt in or out of the pre-seed investment (US$80k for 8% equity);
  • CyberLaunch (Atlanta): accelerator coming out from Georgia tech scene and with a focus on machine learning and information security. It is Chris Klaus’ second accelerator after Neurolaunch (focusing on neuroscience startups). They have incubated companies like C3Security, Chincapi, Cyberdot, Diascan, iTreatMD, Realfactor.io, Securolytics, Vyrill and Yaxa;
  • Data Elite Ventures (Bay area): Tasso Argyros and Stamos Venios founded DEV in 2013 with the idea of accelerating and investing in big data companies. They look to be inactive for a while (or at least off the radar), despite having supported good companies (Unravel, Weft, 451 Degrees) and an exit done (Weft has been acquired by Genscape last year);
  • Deep Science Ventures (London): DeepScienceVentures is not a proper AI oriented accelerator, but rather a deep tech lab where to incubate ideas. It targets people rather than companies, as you can notice from their cohort (very similar to what EF is doing). As a scientist, you join the DSV team for a 3-months internship and if you find the right idea and co-founders, you get access to the following 3-months of MVP prototyping;
  • Element AI (Montreal): created by famous AI scientist Yoshua Bengio, JS Cournoyer, Jean-Francois Gagné, Nicolas Chapados this lab lies on the idea the Canadian AI ecosystem is still one of the strongest worldwide — and this is very true about talents as well as funding raised. It is a mixed between a pure research lab and an incubator, and it has been backed up by Real Ventures. It has been announced not more than a few months ago (although they got already funded by Microsoft Ventures), so there are no more precise information about how it will work in practice (except that they are already working on 10 different projects). Very recent news: they acquired the entire team at MLDB.ai, an open source machine learning database;
  • Eonify (Los Angeles): they focus on healthcare vertical, so they offer perks such as help for Protocol development, regulatory applications, clinical trial design, or grant writing. There is not much more info out there about their accelerator program unfortunately;
  • Founders Factory (London): the Factory is a much wider accelerator who happens to have though a specific track for AI companies. The idea seems to be co-creation/development of two-three AI businesses within the acceleration program every year, for five years. The first two companies, recently announced, are Iris.ai (science research assistant) and Illumr (organizational pattern detection);
  • Google Developers Launchpad (San Francisco): a full-service studio that provides tailored technical and product support to AI and ML startups. Based on their assessment, they provide a customized offering for the AI startup and invite the entrepreneurs to work with us at Launchpad Studio in San Francisco without asking for any equity;
  • H2 Ventures (Sydney): H2 Ventures is an Australian venture capital specialized in fintech which will be running a first accelerator program for AI and data analytics companies starting next August. They have a few requirements (e.g., founding team no larger than 4 people) and they are likely the only Australian accelerator for AI startup. Applicants will need to demonstrate their ability to deliver an MVP within 6 months and the intention of raising a Series A round of capital within 6–12 months;
  • IBM Alphazone (Israel): IBM created this accelerator with the goal in mind of fostering long-term technology and business partnerships with smaller companies in the Cloud, Big Data & Analytics and IoT space. They have another partnership in place with Becton, Dickinson and Company to jointly select up to 3 startups in healthcare delivery and decision making. For those startups they offer extra professional mentorship and matter experts, as well as a grant of up to $25,000. They supported NeuroApplied, Magentiq Eye and Articoolo;
  • Innovat8 Connect (Singapore): a program that brings startups to work along side with Singtel group to develop new solutions useful to the group itself. Singtel Innov8, the VC arm of group (fund size of $250M) follows up with investments where and if needed. A good example of the program output is Xjera;
  • Kapsch Factory1 (Vienna): The Factory1 Kapsch TrafficCom Accelerator 2017 is an acceleration program with a focus on future intelligent mobility solutions (Connected & Autonomous Driving, Big Data Analytics & Deep Learning, Smart Mobility). The CEO and a second team member (preferably the CTO) will have to be present in Vienna for the Kick-Off Bootcamp, the three Acceleration Weeks in Vienna and Berlin and the Demo Day in Montréal (Canada). All travel and accommodation costs are covered;
  • Merantix (Berlin): run by Rasmus Rother (co-founder with Adrian Locher), Merantix is a venture builder specialized in AI and with a stronger focus on four specific verticals: Finance, Healthcare, Advertising and Automotive. Active since one year, they contributed to build companies like Blinq;
  • Microsoft Accelerator (Bangalore): this accelerator program is within for a different reason. It has not been set up, to my knowledge, as an AI-accelerator, but though in the last cohort all the 14 companies accepted were doing some sort of AI/machine learning. In other words, this is the first ‘ex-post AI’ accelerator, because it has been changing its own nature by the companies it selected;
  • Microsoft Accelerator (Paris): they just announced they will open an AI accelerator in partnership with INRIA within the Station F campus in Paris, the same place where Facebook opened its Startup Garage. The first startup incubated will be Recast.ai, but more information will come soon;
  • NextAI (Toronto): a Canadian accelerator for startups with no previous funding. You can apply either as individual as well as a team (but first always apply as individual). It provides startups with a capital of 50k CAD with can be increased by a 30k as well as other 150k throughout the program for top performing teams incorporating a venture ($50,000 for a SAFE with a $2mm CAP and up to an additional $150,000 no CAP, 20% discount to next round). They also provide structured business and technical curriculum taught by successful entrepreneurs and award winning faculty from Rotman (University of Toronto), Harvard, MIT, NYU, and others;
  • Nvidia Inception (Virtual): this is a virtual accelerator program that helps startups during product development, prototyping, and deployment. They can apply for GPU hardware grants and the NVIDIA Deep Learning Institute (DLI) will show the latest techniques in designing, training, and deploy neural network-powered machine learning in different applications. With respect to others, it looks like a soft program, but it directly makes startups to be considered for the GPU Ventures Program ($500K — $5M, and help in sales & marketing, joint development, and product distribution). Apparently, the Inception program includes over 1,300 startups up to date. 14 of those companies have been recently asked to pitch in front of investors and 6 of them eventually got funded through the venture programs (Abeja; Datalogue; Optimus Ride; SoundHound; TempoQuest; Zebra Medical);
  • Play Labs (Cambridge, MA): this is a brand new accelerator, apparently only for MIT students and alumni. They have a strong focus on gamification and ‘playful technologies’, and provide companies with $20k funding plus other $80k (typically in convertible notes) at the end if certain requirements are met;
  • Rockstart AI Accelerator (Netherlands): usually these guys run 5–6 months accelerators in Netherlands. The new program in AI is starting accepting applications in May and it will cost 6% of equity to startups (but only after having raised a further round of funding);
  • Startup Garage (Facebook) (Paris): another brand new accelerator sponsored by Facebook within the startup campus called Station F. Facebook will provide 80 desks and space for 10–15 data-driven startups fro 6 months at no cost (or obligations to use FB products), as well as operational mentoring (marketing, legal, etc.) and technical help (from FAIR — Facebook AI Research). This confirms Facebook’s strategy to have a stronger technical presence in Europe and the ability of France to potentially become one of the major AI hub worldwide. According to VentureBeat, they have already selected a few startups for the first incoming program (Chekk; Mapstr; The Fabulous; Onecub; Karos);
  • TechCode Global AI+ (Bay area): TechCode is a global network of startup incubators and entrepreneur ecosystems which will especially help companies in approaching the Chinese and Asian markets. 10 startups out of the 50 they selected for the program will benefit from an initial investment of $50k. Originally, they would earn a ‘success fee and equity stake’ only if the startup raised funding within 12months from the end of the program. Not sure how this changed for the Global AI+ program;
  • The Hive (Bay area): they define it as a ‘co-creation studio to build and launch startups’ in AI (subdivided in deep learning, blockchain, AR, ‘ambient intelligence’ and ‘context computing’). They built companies as Sensify, Snips and Skry with their $22M second fund. They also host a meetup called ‘The Hive Think Tank’. Their business model is a bit atypical but not completely new: simply speaking, they either incubate existing companies or they think the idea, create the MVP and recruit executives to run this new startup;
  • Voicecamp (Betaworks) (NY): as Botcamp above, this is also run by Patrick Montague and the Betaworks’ team but focuses on early stage companies building voice-based products. $200k uncapped, SAFE note with a 25% discount is offered to all the startups accepted.
  • Winton Labs (London): the famous hedge-fund is now presenting the second cohort of its data science accelerator. First of all, it is really interesting to me that an investment firm in London decides to start an accelerator program without asking for anything in return. But it is more interesting to see what areas they want startups to work on: machine intelligence, forecasting, innovative data, or wildcard (not clear projects). Startups also get direct exposure to Winton Ventures, of course;
  • Y Combinator (Bay area): Y Combinator is known to be one of (if not the) best accelerators in the world. They didn’t have any specific focus on AI until now, but they just announced an experimental batch on artificial intelligence. They claim to be agnostic to the industry and would eventually like to fund an AI company in every vertical. A specific thing they are looking for though is Robot Factories, and teams that use deep (reinforcement) learning to help to fix it.
  • Zeroth AI (Hong Kong): Zeroth.AI is run by tak_lo and his team in Hong Kong, and has a wide spectrum of AI advisors although its young age and 10 early stage AI startups in their first cohort (4 of which in the bots/assistant space). This is probably going to change, with up to 20 startups and optional $120k of funding. The relocation for the program is not mandatory for the entire time frame but highly recommended at the beginning and at the end of the program.
Summary of all the information for the accelerators listed above (only for those ones I could find information about). If you are interested in knowing why some accelerators don’t disclose information, check the theoretical work of Kim and Wagman (2014). Please consider the value of the funding as expressed in accelerator’s local currency (except for Creative Destruction Lab which is in US$) and the length of the programs expressed in months sometimes approximated if originally in weeks.

Research Lead @Balderton. Formerly @Anthemis @UCLA. All opinions are my own.

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