Yeah they are both fighting for survival. No surprise really.
replyNeed to keep the hype going if they are both IPO'ing later this year.
The AI market is an infinite sum market.
replyConsider the fact that 7 year old TPUs are still sitting at near 100p utilization today.
How many IPOs can a company really do?
replyAs many as they want. They can "spin off" and then "merge" again.
replyWhat happened to you?
replyAI fried brains, unfortunately.
replyI mean, he has a point it’s just not very eloquently written.
replyI empathize with the situation, no elegance from them, no eloquence from me :)
replyWhat'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.
reply"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)
replyWhat evidence do you base your opinions on capability transfer on?
reply>There is no moat besides that.
replyCompute.
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
replyProbably why it's selling them TPUs.
reply> is new datasets + post-training shaping the model's behavior (instruction + preference tuning). There is no moat besides that.
replysure, but acquiring/generating/creating/curating so much high quality data is still significant moat.
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