Post #3734442

I studied transformer architecture models and have played around with them (unfortunately) enough to understand how they work. Under the surface the model produces what look like XML tags to designate which tokens are thinking tokens and which are “normal” output. That is literally the only hard difference between the two output modes. The reinforcement learning might tune the thinking to be more like “what a human would expect to see in a thinking block” but it’s still the same RNG madlib process generating everything underneath and any attempt to ascribe intelligence to this process should be met with ~lethal force~ incredulous cynicism.