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Another failure mode for deep learning, precisely anticipated by my 2001 book, The Algebraic Mind.https://www.newscientist.com/article/2198761-deepmind-created-a-maths-ai-that-can-add-up-to-6-but-gets-7-wrong/ …
This is a harsh take. Yes, there are discontinuities and issues that need more work. And yes, it was "only" able to get 14/40 on a test it never studied for. But could those 16-yr-olds do better on its questions? Heck, could I?pic.twitter.com/LHchprQNWE
i would urge you to read the linked arxiv @egrefen @FelixHill84 and others paper and the book (mine) cited there; issue is not overall performance but performance on a specific class of items.
Want to bet that DeepMind has no dramatic improvement within a year?
No bet on timeframe, but I will predict that progress will require something that directly maps onto symbol-manipulation, as articulated in my 2001 book. @geoffreyhinton care to bet?
You know we cited you in the paper, literally in the first few lines, right?
Yep, thanks :) (but year is 2001, fyi, not 2003). Didn’t mean it as a critique of you! Really glad you continue to do great work.
Also @Wolfram_Alpha solves ALL maths through most college level stuff and great deal of beyond. For the life of me I don’t see why researchers insist on recreating wheels that aren’t round.
How can Spelke's "core knowledge" from human cognitive development research be applied here to help improve #AI?
https://www.harvardlds.org/wp-content/uploads/2017/11/Core-Knowledge-Language-and-Number.pdf … – at Vismaya Montessori
Are these multiple choice?
What about Deepmind's Neural ALU https://arxiv.org/abs/1808.00508
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