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It seems to me that the $500M you quote is an exaggeration. I might not understand what it takes to train Deer RL at this time, but it consistently seems that w
by yboris 5y ago
It seems to me that the $500M you quote is an exaggeration. I might not understand what it takes to train Deer RL at this time, but it consistently seems that with time, technologies like this are becoming cheaper and more-user-friendly. If not now (you may be right), isn't likely that in the near future we could have tools easy enough to chain together that people after an intense bootcamp could code up a useful Deep RL architecture to produce a useful-for-profit model?
- adrianN 5y agoI would assume that automating a previously manual industrial process is a lot more difficult than just training a neural network. My gut feeling is that 500M is an underestimate.
- yboris 5y agoYou probably have more experience to estimate price better, but I guess I'm working off a different premise. I thought the claim to defend is that "if you go far enough into the future, it will be cheap". A parallel - facial recognition today is a matter of `npm install face-api.js` (or some other library). Advances in hardware and ML architecture design can bring the currently-challenging world of RL to similar levels. Another way to put my argument is through a question: do you think that even 20 years from now, the cost of a useful RL system will be around $500M (inflation adjusted)?
- robbmorganf 5y agoGPT-3 reportedly cost $10M, and Deep RL is notorious for requiring way more epochs than supervised learning tasks like transformers or CNNs. And that's not even accounting for the cost of robots (which will need frequent repairs when the untrained policies crash into physical objects), salaries for your engineers and all the raw materials that you're going to have to scrap because the robots didn't make saleable product.