[ankit219]

The other comment posted YT videos where Open AI researchers are talking about TTC. So, I am wrong. That $200 subscription is just because the number of tokens generated are huge when CoT is involved. Usually inference output is capped at 2000-4000 tokens (max of ~8192) or so, but they cannot do it with o1 and all the thinking tokens involved. This is true with all the approaches - next token prediction, TTC with beam/lookahead search, or MCTS + TTC. If you specify the output token range as high and induce a model to think before it answers, you will get better results on smaller/local models too.

> huge headroom for TTC to improve results ...1B/3B models

Absolutely. How this is productized remains to be seen. I have high hopes with MCTS and Iterative Preference Learning, but it is harder to implement. Not sure if Open AI has done that. Though Deepmind's results are unbelievably good [1].

[1]:https://arxiv.org/pdf/2405.00451v2