Could there be a benefit to releasing a new model, slowly dumbing it down over a couple months, then releasing a new model that’s marginally if at all better than the original to create a perceived improvement when in reality there isn’t really one?
For an industry that’s stagnant in progress yet relies on new frequent releases to survive (non-progress being an existential risk), this could make sense.
I have no idea if that’s what’s happened, I completely pulled it out of my butt. And I have no idea is the actual frontier is stagnating.
There must be some benefit if all the providers are doing it independently.
GPT5.6-Sol on Max thinking just became regarded as of a few days ago.
The boosters will tell me it’s my fault for using such an old, cheap out-of-date low quality near useless wish.com model (that was SOTA and better than human coders one month ago).
Again, I’m out of my element here, but isn’t the entire industry dependent on “new better releases frequently”? If so, and if no one has made any meaningful breakthrough, might they all pursue this kind of deception just to stay afloat/“competitive”/relevant?
Kinda. Off the top of my head, DeepSeek and their thinking model was pretty new and interesting. Multi input models are also newish (combined input of text, image, video, audio, etc). Then there's Jev, a recently release that has a lot of people talking. It isn't really an LLM, but also is one.
Sam Altman believes he can train a model entirely on synthetic data, which he admits would not have human world knowledge but is interesting none the less, which likely led to their mathematical models.
Overall models have become cheaper to run and smarter per token.
talon8635 · · focus · HN ↗
For an industry that’s stagnant in progress yet relies on new frequent releases to survive (non-progress being an existential risk), this could make sense.
I have no idea if that’s what’s happened, I completely pulled it out of my butt. And I have no idea is the actual frontier is stagnating.
nxc18 · · focus · HN ↗
GPT5.6-Sol on Max thinking just became regarded as of a few days ago.
The boosters will tell me it’s my fault for using such an old, cheap out-of-date low quality near useless wish.com model (that was SOTA and better than human coders one month ago).
The cycle repeats.
talon8635 · · focus · HN ↗
Thanks for your insight
dalenw · · focus · HN ↗
Sam Altman believes he can train a model entirely on synthetic data, which he admits would not have human world knowledge but is interesting none the less, which likely led to their mathematical models.
Overall models have become cheaper to run and smarter per token.