What happened to you?

AI fried brains, unfortunately.

I mean, he has a point it’s just not very eloquently written.

I empathize with the situation, no elegance from them, no eloquence from me :)

What's funny is that most of this "progress" is new datasets + post-training shaping the model's behavior (instruction + preference tuning). There is no moat besides that.

"post-training shaping the models behavior" it seems from your wording that you find it not that dramatic. I rather find the fact that RL on novel environments providing steady improvements after base-model an incredibly bullish signal on future AI improvements. I also believe that the capability increase are transferring to other domains (or at least covers enough domains) that it represents a real rise in intelligence in the human sense (when measured in capabilities - not necessarily innate learning ability)

What evidence do you base your opinions on capability transfer on?

> is new datasets + post-training shaping the model's behavior (instruction + preference tuning). There is no moat besides that.

sure, but acquiring/generating/creating/curating so much high quality data is still significant moat.

>There is no moat besides that.

Compute.

Google didn't announce $185 billion in capex to do cataloguing and flash cards.

Google didn't buy 30% of Anthropic to starve them of compute

Probably why it's selling them TPUs.

Yeah they are both fighting for survival. No surprise really.

Need to keep the hype going if they are both IPO'ing later this year.

The AI market is an infinite sum market.

Consider the fact that 7 year old TPUs are still sitting at near 100p utilization today.

How many IPOs can a company really do?

As many as they want. They can "spin off" and then "merge" again.

IPO only ONE but followups are called FPOs.