One of my favorite sayings in the startup world is “Innovation happens at the edges.”
In AI, on one end of the spectrum, billions in investments and acquisitions are pouring in from giants like Nvidia, Google, and Microsoft. On the other side, small, imaginative teams are trekking out to new frontiers untouched by AI.
A great look at the performance of companies big and small is the inaugural AI Index 2017 report, which came out a few weeks ago. If you haven’t gotten to it yet, I suggest you check it out.
It’s put together by some of the best known and most reputable people in AI, like Jack Clark at OpenAI and Yoav Shoham, an AI professor at Stanford. It’s part of the AI100 study at Stanford University that documents the progress and impact of AI.
The report counts a 14x increase in AI startups since 2000, and a 6x increase in VC funding to AI startups since 2000.
Most of the study’s graphs about the spread and growth of AI in 2017 are showing up and to the right, hockey stick growth over the past 2-3 years. So if you were looking for an assessment of the state of AI startups this year, it seems pretty strong. That comes as no surprise, however, since tech giants made more than 30 AI startup acquisitions in the first half of 2017.
At the same time, the report acknowledges its own shortcoming and imperfections.
As its authors freely admit, it makes no attempt to address matters of race or gender or how to mitigate AI’s impact on society. It also fails to mention markets outside the United States or investments that government or institutional entities are making in R&D.
The two slight declines that appear in the report were in VC investment in AI and in the AI Vibrancy Index. Bet you’ve never heard of that last bit before. The Vibrancy Index tracks enthusiasm about AI based on a combination of the number of published AI papers, course enrollment, and VC investment.
Jaw-dropping advances in some places with room for improvement in others is also the theme of the section that measures AI system performance in tasks like speech recognition and object detection.
For example, some computer vision today can identify skin cancer as well as a panel of doctors, but AI systems still have less common sense reasoning than a 5-year-old.
There’s a sense throughout Index 2017, much like the year that’s coming to a close, that there’s plenty of room for growth, but also much left to understand, document, and consider.
The steering committee of the inaugural AI Index strongly encourages feedback, so reach out if you’d like to shape the next edition of this project to track the progress and impact of AI.
P.S. Please enjoy this video: Ali Rahimi’s talk at NIPS (NIPS 2017 Test-of-time award presentation).
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