About the Workshop
This workshop runs alongside the Thirty-First AAAI Conference on Artificial Intelligence (AAAI 2017), which is being held in San Francisco, California, from February 4th to 9th, 2017.
The objective of this workshop is to bring together members of the AI community with entrepreneurs and those who have been involved in a successful AI startup company, to explore the opportunities and challenges associated with developing successful companies based on artificial intelligence technologies. The workshop will take advantage of AAAI 2017’s proximity to Silicon Valley by attracting participants and contributors from that community.
The topic of this workshop is to explore as fully as possible the process, challenges and opportunities associated with creating successful startups focused on technologies based on artificial intelligence. Some examples of these companies include Palantir, Tesla, Brighterion, Savioke, Pathover, DeepMind, and Ner- vana. Some specific domains include, but are by no means limited to, self-driving cars, digital agents, robotics, and health.
While most workshops at AAAI focus on specific technical topics, this proposed workshop will take a broad view on how AI researchers can develop successful companies based on AI technology, and the issues that they should be aware of in that process. The workshop will consider recent commercial successes in the field and what lessons can be learned .
- 09:30 - Welcome & Objectives of the Workshop (Barry O'Sullivan)
- 09:40 - Markus Fromherz (SK Telecom Americas Innopartner & TripSeer)
- 10:05 - Barney Pell Co-Founder, Chairman & CSO at LocoMobi)
- 10:30 - George John (AI-focused Investor, Advisor, and Board Director)
- 10:55 - Coffee Break
- 11:20 - Fritz Heckel (ASAPP)
- 11:45 - Sean O’Sullivan (CEO, SOSV)
- 12:10 - Enda Keane (TreeMetrics)
- 12:25 - Alan Holland (Keelvar)
- 12:50 Wrap-up
- 13:00 End
About the Talks
Markus Fromherz, SK Telecom Americas Innopartner & TripSeer (founder)
Abstract. As a former AI researcher, later AI startup investor, and now AI startup founder, I will reflect on observations I’ve made along the way.
Fritz Henkel, Machine Learning Engineer, ASAPP
Abstract. Artificial intelligence in production is a very different beast from artificial intelligence in the lab. While rigor and repeatability are still core to the discipline, the goals of practice require taking a different perspective. I'll talk about what I've learned about building consumer-facing AI systems as a machine learning engineer coming from an academic background. I'll focus on what I have found most critical in the startup environment in my current role at ASAPP.
ASAPP, Inc. is a machine learning and artificial intelligence company focusing initially on improving the customer service space. In just over two years into the venture, ASAPP has built relationships with customers both large and small, including Fortune 100 companies.
Accelerating AI: Lessons from backing 40 AI companies a year in hardware, life sciences, software, and food.
Sean O'Sullivan, CEO & Founder, SOSV
Abstract. SOSV runs the world’s leading accelerators in hardware (HAX), life sciences (IndieBio and RebelBio), food (Food-X), smart cities (Urban-X) and cross-border software and apps (Chinaccelerator, MOX). SOSV backs 150 new startups per year in programs run in Europe, Asia, and the United States. About $250m per year are invested in these companies from SOSV and 120 other institutional investors.
Enda Keane, CEO & Founder, TreeMetrics
Abstract. Since 2005, Treemetrtics has been serving the forest industry with specific solutions to address the key issues that forest owners, foresters and managers face every day. Treemetrics' mission is to create new technology to preserve the enviroment and ensure sustainable use of the natural resources. Our technology is devoted to the protection of environmentally sensitive ecosystems.
Alan Holland, CEO & Founder, Keelvar
Abstract. This is the story of Keelvar, a startup founded in 2012 by an AI researcher specialising in combinatorial auctions and algorithmic mechanism design. It begins with the path to funding and building a minimum viable product. It also covers the pivots, mistakes, learnings and eventual discovery of product market-fit. It concludes with the founder's perspective on the most pragmatic approach to building a SaaS business that leverages AI.