The Ledger
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Patel: $10B AI data centers aim to automate software engineering, not chatbots
“No one is trying to make with these, you know, with these ten billion dollar data centers, they're not trying to make chat models, right? They're not trying to make models that people chat with, just to be clear, right? They're trying to solve things like soft…”
Patel: OpenAI's Orion training run failed to reach GPT-5 performance levels
“There were hopes that Orion could be used for GPT-V but its improvement was, like, not enough to be, like, really a GPT-V. Furthermore, it was trained on the classical method, which is, like which is a ton of pre-training, and then some reinforcement learning …”
Patel: Model inference costs dropped 60x from GPT-4 to DeepSeek-V3
“And likewise, when we look at from GPT-IV to DeepSeq VIII it's fallen roughly 600 X in cost. Right. So we're not quite at that 1200 X, but it has fallen 600 X in cost from 60 dollars to less than you know, to about a dollar. Right. Or to less than a dollar. So…”
Patel: Frontier AI cluster costs have scaled from $100M to $10B
“For GPT-IV, it was a few hundred million dollars and it's one building full of GPUs, too. GPT-IV 4.5 and the reasoning models, like, oh, one, oh, three were done in a, in three buildings on the same site, and, you know, billions of dollars to, hey, these next …”
Patel: GPT-5 will simultaneously scale pre-training and post-training reasoning
“And so now GPT-Five, as Sam calls it, is, is gonna be a model that has huge pre-training scale, right? Like GPT-Five, but also huge post-training scale, Like O-one and O-three and continuing to scale that up, right? This would be the first time we see a model …”