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Good investment portfolios require a balance of shorter and longer term, different risks and payoff profiles. You are focusing on the riskiest end of a diversified AI portfolio to support your parti pris.
Really?! who besides me thinks deep reinforcement learning is most risky, rather mainstream? between investments at OpenAI and DeepMind, deep RL is by far the best capitalized strand of current AI — hardly an outlier. it’s the other flowers that are getting less chance to bloom.
Deep RL is just a (pretty good) means to explore parts of design space, not an end. Lots more going on at DM and elsewhere, but that diversity is inconvenient for your single-track argument.
again you are being unfair to me and distorting my argument, somewhere in this thread i tweeted something like not “largest not sole”, and i am arguing for diversity not against it.
I don't know how much of DM's overall budget goes into Deep RL. Certainly at least half of their PR budget does. DM must be spending a lot on health care research. And I know other DM folks work on Google's core recommendations business
AFAIK (I could be wrong) DM doesn't sell any products. It doesn't have any income. So "loss" is just a statement of how much alphabet is investing in DM's basic research. Or am I missing something?
I agree with you that RL methods are moving into a regime of diminishing returns. Quite analogous to what we have seen in High Energy Physics (HPC). The low hanging fruit have been picked and we have to seek other pastures.
Drop me a note guys if you want to hear about one route to said pastures. I'm 1-2 years away from a proof of concept that should demonstrate the first step away from ML. object in-variance, low overhead training, non prescriptive symbolisation etc.
What are the other "flowers" that you are talking about? And why in economic terms they dont get a chance to bloom?
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