This year’s judges included: Tonya Custis, director of AI research, Autodesk Michael Jordan, professor of computer science, University of California, Berkeley Xuezhao Lan, founding and managing partner, Basis Set Ventures Andrew Ng, cofounder, Coursera computer science adjunct faculty, Stanford University Fay Cobb Payton, professor of information technology and analytics, North Carolina State University Gill Pratt, CEO, Toyota Research Institute chief scientist, Toyota Motor Corp. Silicon Valley remains the hub for AI startups, with 37 of 50 honorees coming from the San Francisco Bay Area. In terms of valuation, at least 13 of the AI 50 are valued at $100 million or less, while 13 are unicorns valued at $1 billion or more. This 2021 list features 31 companies appearing for the first time, while seven have qualified for three years in a row. “I'm finding that for multiple companies, by starting to help enterprises efficiently get the data they need to feed into an open source model, that's the key to unlocking the value for that business.”
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“There are plenty of open source models that you can download that work just fine for a problem, but what really needs to be customized is the data,” he says. Looking ahead, judge Andrew Ng, founder of Google Brain, cofounder of Coursera and founder and CEO of Landing AI, sees more opportunities for AI to help manufacturers and healthcare providers with data tailored to their specific needs. Autonomous vehicles are again represented on the list, this year by Gatik, which sees “middle mile” driverless deliveries as a lucrative, early market to target. Companies reliant on natural language processing, such as Duolingo, Lilt and Whisper, which developed an AI-enabled hearing aid, are yet another core category. Healthcare and biotech research, as conducted by Komodo Health, Genesis Therapeutics and Verge Genomics, remains a key area for advanced AI, as is computer vision, with companies such as Viz.ai and AMP Robotics using the technology to improve health care and waste recycling. Next, a panel of expert AI judges evaluated the finalists to find the 50 most compelling companies (they were precluded from judging companies in which they have a vested interest).Īmong trends this year are what Sequoia Capital’s Konstantine Buhler calls AI workbench companies-building of platforms tailored to different enterprises, including Dataiku, DataRobot Domino Data and Databricks.
From there, our data partners applied an algorithm to identify 100 companies with the highest quantitative scores-and that also made diversity a priority.
Forbes received several hundred entries, of which nearly 400 qualified for consideration. The application asked companies to provide details on their technology, business model, customers and financials like funding, valuation and revenue history (companies had the option to submit information confidentially, to encourage greater transparency). Our list was compiled through a submission process open to any AI company in the U.S. AI companies incubated at, largely funded through or acquired by large tech, manufacturing or industrial firms aren’t eligible for consideration. To be considered, businesses must be privately-held and utilizing machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to “understand” written or spoken language) or computer vision (which relates to how machines “see”).
With this in mind, Forbes has partnered with venture firms Sequoia Capital and Meritech Capital to create our third annual AI 50, a list of private, promising North American companies that are using artificial intelligence in ways that are fundamental to their operations.
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