Gary Marcus, a prominent figure in AI, is on a mission to instill a breath of fresh air to a discipline he sees as in danger of stagnating. Knowledge graphs, the 20-year old hype, may have something to offer there.

“This is what we need to do. It’s not popular right now, but this is why the stuff that is popular isn’t working.” That’s a gross oversimplification of what scientist, best-selling author, and entrepreneur Gary Marcus has been saying for a number of years now, but at least it’s one made by himself.

The “popular stuff which is not working” part refers to deep learning, and the “what we need to do” part refers to a more holistic approach to AI. Marcus is not short of ambition; he is set on nothing else but rebooting AI. He is not short of qualifications either. He has been working on figuring out the nature of intelligence, artificial or otherwise, more or less since his childhood.

Questioning deep learning may sound controversial, considering deep learning is seen as the most successful sub-domain in AI at the moment. Marcus on his part has been consistent in his critique. He has published work that highlights how deep learning fails, exemplified by language models such as GPT-2, Meena, and GPT-3.

Marcus has recently published a 60-page long paper titled “The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence.” In this work, Marcus goes beyond critique, putting forward concrete proposals to move AI forward.

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