[somewhereoutth]

Yes the huge discrete stepwise training spend is critical.

Maybe investors will realise that "the only winning move is not to play".

And so we are left with (as was) frontier models getting more and more out of date as whoever their post bankruptcy custodians are tries to eek pennies on the dollar for inference on their decaying property. Perhaps along with local and/or highly specialized models still feeding on the after-glow of the huge amount of training that was (and is no longer) done.

The next AI winter is going to be deep, savage, and long.

[extraextra]

Bankruptcies? The winners will gobble up the losers and the few remaining players will have pricing power. Don't be naive thinking that OpenAI or Anthropic can possibly go bankrupt. There will always be someone happy to buy them up for a nice price. Yes, the market will have to go through a consolidation phase though.

[galaxyLogic]

> frontier models getting more and more out of date

Why are they getting out of date? Is it because we have new content from the internet that the older models did not have? Or are we simply trying to increase the size of the training data? In other words not more up-todate in terms of time the content was created vs. wanting to use bigger training-input-sets?

[somewhereoutth]

lack of new content from the internet will make them go out of date. Not just facts and figures, but (for example) new programming languages/techniques.

[galaxyLogic]

I see makes sense. Then it it kinda says that quality of the model is the topicality of its inputs I assume.