TMTB: Gavin Baker ILTB Podcast Key Quotes

Full link here…Lot of good stuff here so including a lot of the quotes

1. Token costs, low-cost producers, and Google vs. Nvidia/Blackwell/GB300

• “Google for sure has this temporary advantage right now from a pre-training perspective. I think it’s also important that they’ve been the lowest cost producer of tokens.”

• “AI is the first time in my career as a tech investor that being the low-cost producer has ever mattered. Apple is not worth trillions because they’re the low-cost producer of phones. Microsoft is not worth trillions because they’re the low-cost producer of software. Nvidia is not worth trillions ‘cause they’re the low-cost producer of AI accelerators. It’s never mattered.”

• “What Google has been doing as the low-cost producer is they have been, I would say, sucking the economic oxygen out of the AI ecosystem which is an extremely rational strategy for them… let’s make life really hard for our competitors.”

• “The GB300 is a great chip. It is drop-in compatible in every way with those GB200 racks… You’re going to put those GB300s in and then the companies that use the GB300s, they are going to be the low-cost producer of tokens, particularly if you’re vertically integrated.”

• “If you have a decisive cost advantage and you’re Google and you have search and all these other businesses, why not run AI at a negative 30% margin? It is by far the rational decision… You take the economic oxygen out of the environment… and then on the other side of that maybe have an extremely dominant share position.”

• “All that calculus changes once Google is no longer the low-cost producer, which I think will be the case… and I do think it’s very interesting like the strategic and economic calculations between the players. I’ve never seen anything like it.”

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2. Scaling laws, reasoning, Gemini 3, and the trajectory of AI progress

• “I do think Gemini 3 was very important because it showed us that scaling laws for pre-training are intact. They stated that unequivocally and that’s important because no one on planet Earth knows how or why scaling laws for pre-training work.”