> It's clear that these models have orders of magnitude too much data already. I have a toy disproof for your claim that this is clear. Imagine that you are t

> It's clear that these models have orders of magnitude too much data already. I have a toy disproof for your claim that this is clear. Imagine that you are training a ML system using oracle access to Mum. The ML training system can request 10 million representative samples of Mum output, and then we could judge if the ML system has adequately reproduced Mum. Now also imagine that Mum frequently tells people that Mum knows a 23 letter secret and while mum won't tell people what is outright, she'll answer queries like if a guess is lexographically higher or lower. We could even imagine that the ML has seen Mum's side of some interactions with her doing that. Would the ML know Mum's secret? No. Would a child that could interact with Mum? Yes-- after at most ceil(log_alphabet(23)) queries at most, if the child is efficient. Learning in an interactive context is not the same as learning from written material, so you can't be sure that the fact that children learn english from less text means that a non-interactive ML system could english from the same amount. Q.E.D. Now, if someone figures out how to efficiently train these natural language models with reinforcement learning...