Let’s make AI count as it should.
Over the last 10 years, I’ve realized that applied research (and more specifically AI) is a double-edged sword. On the one hand, it can help you solve incredibly complex problems, and create an insane Return-On-Investment for companies. But on the other hand, according to a Venturebeat article (based on a Gartner report), only 20% of AI projects ever get deployed to production, and among those, only 40% are profitable! Unfortunately, these figures do not surprise me, as I’ve seen countless algorithmic and machine learning projects fail in my career (and thankfully also some great successes).
I created this blog in order to analyze the reasons behind such failures, share experiences (mine and others), and generate discussions that could eventually help maximize the impact of AI research in the real world.
Who is this blog for?
At a high level, this blog is for people that - like me - believe that AI’s impact should be much larger than it is today. More specifically, I think 3 types of people can learn from this blog:
- Applied researchers like myself, who love reading papers and solving hard technical problems, but who are more motivated by their actual impact than their salary or implementing the latest cool AI paper (who said GAN ;-)?).
- Entrepreneurs and leaders, technical or not, on questions such as: “what to look for when recruiting?”, “what kind of ML infrastructure will make my teams most effective?”, “When to know when to stop an AI project”, etc…
- Investors or future entrepreneurs, on questions like “what are the problems in the world of AI today”, “who is tackling them and how”, etc…
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