Ramin Hasani: prediction

Transcript context

…Yeah, well, I mean, that's a great question. Obviously, the local coworker is as it stands today. It's obviously just to open minds, like, hey, you know what, this type of applications you can enable. The class of what this format of local agents are going to enable is basically a local computer. You have an orchestrator. If something is so complicated, it should be able to send it to the cloud, fetch the answers for you. If it's not sensitive, we have like, let's say, smaller models that are PII models. It should be able to use the PII models to really like filter out all the personally identified information, send it to the cloud for you. don't need to even see these models. These models should be like on the background. The model that you have to tune is that orchestrator that be able to route between many different services or even smaller specialized models that are doing stuff, and also some of the cloud models that are out there, right? That router is the computer, that's like the local computer. That's like a definition of, but when you open your laptop, it should be just that, you literally have just that, and then you start working with all the services you want to have, it's just the same way that you communicate with your, let's say, assistant, it should be in the form of an assistant that does all sort of those jobs. It takes a while for people to get not weirded out by the user interface, like just being that and not seeing all the file formats and what you have to do, but you've got to get used to it. Like now cloud code is even as for the IDE. Is the 24B off the shelf is going to be there on the quality that does all of those stuff for you? No, it's not. None of the local models today are there. On the local models today, you got to fine tune them. You got to get them to be specialized for the stuff that you want to do with the proper explanations for your Claude agent, you basically give it these things. But is Claude being able to go out there and actually build this model for you, let's say, Do the fine-tuning and getting it to that place? No, because today, even Fable level kind of models, they would not be able to, first of all, you wouldn't have access to that because Anthropic is actually having access to the auto-tune and stuff like automated models, models generating models kind of platform. There are companies and also ourselves, we are building platforms that enables you to do fine-tuning of this whole thing. That would cost you between 10s of dollars to, let's say, low thousands of dollars to actually get you to the cloud quality for your, and with all the checks, production quality kind of model, and it's not gonna cost you like 10s of thousands of dollars it's going to be like between 10s of dollars to actually like... those thousands of dollars. the checks, production quality kind of model, and it's not gonna cost you like 10s of thousands of dollars it's going to be like between 10s of dollars to actually like... those thousands of dollars. And that's kind of the scale that we are thinking about, because again, efficiency here matters a lot because we don't want, and we want this fine tuning to happen on the compute that you already have. Or if you don't have it, you would actually put it like in a secure and proper kind of data center that you would actually like host it like from the providers basically. And you would be able to get to that quality of the models. There are platforms that hopefully like as we go forward in the next few months, we are going to announce like some Platforms that would you can hook it just directly in your channel you don't need to do anything, you just say, Hey, you know what, go call this platform now for fine-tuning this thing, go call this platform, and this would give you a production-grade foundation model that you can deploy it now for yourself. either fine tune on that data or depending on the use case, depending on what you want to do, it doesn't even have to see that data. It can even synthetically generate data on its own and actually train the model to be like just the perfect reliable tool caller and understands when is the shortcomings of it and it can actually go away and deliver it to some other places. Yeah, so I would say you're extremely close to get to that point. I'll wait for your platform to be ready. I don't have to DIY is the message. Yes, this has been. Brilliant. Maybe one last question, and then I'll just kind of give you the floor to close however you'd like. How far do you think this goes in terms of kind of miniaturization of intelligence, if you will? One intuition would be like the biological world that we see is maybe on some sort of Pareto frontier already. And so the watts that go into our brain is maybe like getting us close to the maximum that we could get for that amount of power. but maybe you have a different intuition. What would you expect in terms of upper limits of intelligence that I could have on my phone or on my laptop as we really get to the kind of physical limits of the technology?…

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