Model Training
topic on 6 shows · 8 statements across 8 episodes
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8 statements about Model Training, every show
Altman: Massive Inference Revenue Will Easily Fund Frontier Model Training
“We will have so much usage of our models that we do not need to be a gigantically high margin business to be able to afford model training. Like, so much of our future compute plans Will be used to sell inference to customers that even if we can enjoy a modest…”
Ethan He: Daily iteration speed is the top factor in model training
“When I look at like training models, I don't so actually the top important thing is like how many how many iterations can you do like per, per day? And the more iteration can you do, you can train the model much faster. So if you have a very strong infra and y…”
Morcos: Proper training curricula could reduce model training costs by 10x
“And getting a curriculum right could literally make the difference between, you know, spending 10 times as much on a model training, you know, hundreds of millions of dollars potentially.”
Laskin: AI Apps Without Custom Model Training Are Fundamentally Limited
“The important part, I think, is to be able to tweak every part of the system from, you know, the product features to the agent design to the model training in order to build the best overall system. And if you are capped in which parts you can change, like if …”
Nguyen: Model Training Is More Art Than Science, Debugged Like Software
“Model training is more an art than a science, and in a lot of ways, like, we as, like, model trainers think a lot about, like, data quality. So, like, it's one of the most important things in model training is, like how do you ensure the highest quality data f…”
Nguyen: AI model training requires evals where prompted baselines fail
“Prototype was prompted baseline. It's all, all, everything starts with, like, prompted baseline, and then, like, we craft, like, certain, like, evaluations that we want to, like, capture, that we want to, like, measure progress, at least, for the model, and th…”
Wood: Vast Majority of AI Compute Cost Is Inference, Not Training
“And whilst A lot of focus is put on training. If you think about it, you may train a model once a month, once a week, let's say, but you're going to be running predictions and inference and chatting with that model 100,010 of thousands of times a day. And so i…”