Small Models
topic on 6 shows · 17 statements across 17 episodes
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17 statements about Small Models, every show
Zhang: Fine-tuned small models can match or beat large frontier models
“And if you fine tune it to be really good at that task, it can be just as good or better than the big models.”
Roy: Running AI models locally undermines centralized data center capex narratives
“Small models are gonna run locally on device. And that's actually gonna be how infrastructure gets built out. That throws such a wrench into any of these stories that we've been talking about for the last 30 minutes, like that completely destroys those stories…”
Andreessen: Small AI models match frontier capabilities within 6 to 12 months
“If you track the capability of the leading edge models over time, what you find is after six or 12 months, there's a small model that's just as capable.”
Evans: On-device AI models will fail as capability gains outpace compression
“Will we have small models running on devices? No, because the small models, the capabilities are moving too fast for the small models to shrink the small model onto the device.”
Morris: Small models should be defined as runnable on a single GPU
“I think that we should establish the definition of small model as being a model that a grad student can inference at reasonable time on a single GPU. Which is probably like seven B maybe. I don't think 27 is small under any reasonable.”
Brown: Small LLMs default to skipping tool calls without explicit training
“If you set these models up to use tools, They just won't. Like if you say, hey, here's a question. You have access to these tools. Do as many rounds of tool calling as you want, and then submit your answer. They'll just submit their answer because they like ar…”
Khosla: Small models will not replace large frontier models for intelligence
“If you want human level intelligence from a model, it'll be a big model, and there'll be a couple of them around, some better than others, some a year or two ahead of others, but I don't think small models substitute
For big models”
Ben Allal: Small models make more sense than large models for text extraction
“So I think text extraction is like one use case where small models can be really performant, and it makes sense to use them instead of just using larger models.”
Khosla: Small models will never substitute for large, human-level AI models
“If you want human level intelligence from model, it'll be a big model, and there'll be a couple of them around. Some better than others, some a year or two ahead of others, but I don't think small models substitute for big models, but they do some things reall…”
Lambert: Scaling from 7B to 70B parameters fixes nuance and repetition
“I think the things that people see now is like the small models don't really handle nuance as well, and they could be more repetitive if, even if they have really good instruction tuning, but if you take that kind of seven to seventy billion parameter jump, li…”
Cohen: Undertrained large AI models underperform well-trained smaller models
“If you have a large model, That is undertrained. It will underperform a small model, which is really well, like well, well trained. So you're just wasting resources and you're going to get like less efficient results.”
Qiu: The AI industry hasn't pushed data limits on small models
“We're definitely not pushing the bounds of what we can do with data today on small models, and so, you know, smaller things can work well.”
Sutskever: Larger AI models will unlock unprecedented value over small models
“I do think though that as models continue to get larger and better, then they will unlock new and unprecedentedly valuable applications. So yeah, the small models will have their niche for the less interesting applications, which are still very useful.”
Murati: AI market will feature a diverse range of models
“You can see even today, you know, we make a lot of models available through our API and from the various, from the very small models to our frontier models, and people don't always need to use The most powerful, the most capable model. Sometimes they just need…”
The Token Shortage Crisis Only Applies to AGI, Not Small Models
“I would say if we are aiming for AGI, there is a token crisis, but if we are aiming for useful small models, I don't think there is a token crisis.”
Small Hive Architecture AI Models Will Massively Outperform Large Monolithic Models
“I think that small models will outperform large models massively, like I said, the Hive model aspect”