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Could you train a ChatGPT-beating model for $85k and run it in a browser?

simonwillison.net

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Re: Could you train a ChatGPT-beating model for $85k and run it in a browser?

#42
post #18

Earlier quoted context omitted.

> I don't get it why people love software running in a browser. If you read the article, part of the argument was for the sandboxing that the browser provides. "Obviously if you’re going to give a language model the ability to execute API calls and evaluate code you need to do it in a safe environment! Like for example... a web browser, which runs code from untrusted sources as a matter of habit and has the most thor…

Thinking about it... I don't know exactly about the browser sandboxing. But isn't it's purpose to prevent access to the local system, while it mostly leaves access to the internet open? Is that really a good way to limit and AI system's API access?

The same-origin policy in browsers defaults to preventing JavaScript from making API calls out to any domain other than the one that hosts the page - unless those other domains have the right CORS headers.

https://developer.mozilla.org/en-US/docs/Web/Security/Same-o...

Re: Could you train a ChatGPT-beating model for $85k and run it in a browser?

#43
post #20

Earlier quoted context omitted.

you're comparing the capital cost of acquiring a GPU machine with the operational cost of renting one in the cloud. Ignoring the operational costs of on-prem hardware is pretty common, but those costs are significant and can greatly change the calculation.

For a server farm, sure, for one machine, I don't know. Assuming it plugs into a normal 15A circuit, and you have a we-work or something where you don't pay for power, is the operational cost of one machine really material?

it's hard to tell from what you're saying: you're planning on putting an ML infrastructure training server on a regular 15A circuit, not in a data center or machine room? And power is paid for by somebody else?

My thinking about pricing doesn't include that option because I wouldn't just hook a server like that up to a regular outlet in an office and use it for production work. If that works for you- you can happily ignore my comments. But if you go ahead and build such a thing and operate it for a year, please let us know if there were any costs- either dollar or in suffering- associated with your decision

[edit: adding in that the value of this machine also suggests it cannot live unattended in an insecure location, like an office]

signed, person who used to build closet clusters at universities

Re: Could you train a ChatGPT-beating model for $85k and run it in a browser?

#44
post #17

Now imagine loading 3.9 GB each time you want to interact with a webpage

10yrs from now models will be in the OS. Maybe even in silicon. No downloads required.

The OS will be in the cloud interfacing into our brain by then. I don't want this btw.

Re: Could you train a ChatGPT-beating model for $85k and run it in a browser?

#45
post #20

If you have ~100k to spend, aren't there options to buy a gpu rather than just blow it all on cloud? How much is an 8xA100 machine? 4xA100 is 75k, 8 is 140k https://shop.lambdalabs.com/deep-learning/servers/hyperplane...

you're comparing the capital cost of acquiring a GPU machine with the operational cost of renting one in the cloud. Ignoring the operational costs of on-prem hardware is pretty common, but those costs are significant and can greatly change the calculation.

Heh, you work at AWS or Google Cloud perhaps? ;) (Only joking about this as I constantly see employees from AWS/GCloud and other cloud providers claim that cloud is always cheaper than hosting things yourself)

Sure, if you're planning to service a large number of users, building your infrastructure in-house might be a bit overkill, as you'll need a infrastructure team to service it as well.

If you're just want to buy 4 GPUs to put in one server to run some training yourself, I don't think it's that much overkill. Especially considering you can recover much of the cost even after a year by selling much of the equipment you bought. Most of your losses will be costs for electricity and internet connection.

Re: Could you train a ChatGPT-beating model for $85k and run it in a browser?

#46

Earlier quoted context omitted.

> I want the best LLMs to be open source too How do you do this without being incredibly wealthy?

Pooling resources a la SETI@home would be an interesting option I would love to see.

My understanding is that can work for model inference but not for model training.

https://github.com/bigscience-workshop/petals is a project that does this kind of thing for running inference - I tried it out in Google Collab and it seemed to work pretty well.

Model training is much harder though, because it requires a HUGE amount of high bandwidth data exchange between the machines doing the training - way more than is feasible to send over anything other than a local network connection.

Re: Could you train a ChatGPT-beating model for $85k and run it in a browser?

#47
post #34
post #14

His estimate is that you could train a LLaMA-7B scale model for around $82,432 and then fine-tune it for a total of less than $85K. But when I saw the fine tuned LLaMA-like models they were worse in my opinion even than GPT-3. They were like GPT-2.5 or like that. Not nearly as good as ChatGPT 3.5 and certainly not ChatGPT-beating. Of course, far enough in the future you could certainly run one in the browser for $85K…

Yeah, you're right. I wrote this a couple of weeks ago at the height of LLaMA hype, but with further experience I don't think the GPT-3 comparisons hold weight. My biggest problem: I haven't managed to get a great summarization out of a LLaMA derivative that runs on my laptop yet. Maybe I haven't tried the right model or the right prompt yet though, but that feels essential to me for a bunch of different applications…

my biggest problem with these models is that they cannot reliably produce structured data.

even davinci can be used as part of a chain, because you can direct it to structure and unstructure data, and then extract the single component and build them into tasks. cohere, llama et al are currently struggling to consistently produce these result reliably, even if you can chat with them and frankly it's not about the chat

example from a stack overflow that split the questions before sending it down chain for answering all points individually:

This is a customer question:

I'm a beginner RoR programmer who's planning to deploy my app using Heroku. Word from my other advisor friends says that Heroku is really easy, good to use. The only problem is that I still have no idea what Heroku does...

I've looked at their website and in a nutshell, what Heroku does is help with scaling but... why does that even matter? How does Heroku help with:

    Speed - My research implied that deploying AWS on the US East Coast would be the fastest if I am targeting a US/Asia-based audience.

    Security - How secure are they?

    Scaling - How does it actually work?

    Cost efficiency - There's something like a dyno that makes it easy to scale.

    How do they fare against their competitors? For example, Engine Yard and bluebox?
Please use layman English terms to explain... I'm a beginner programmer.

Extract the scenario from the question including a summary of every detail, list every question, in JSON:

{ "scenario": "A beginner RoR programmer is planning to deploy their app using Heroku and is seeking advice about deploying it.", "questions": [ "What does Heroku do?", "How does deploying AWS on the US East Coast help with speed?", "How secure is Heroku?", "How does scaling with Heroku work?", "What is a dyno and why is it cost efficient?", "How does Heroku compare to its competitors, such as Engine Yard and Bluebox?" ] }

Re: Could you train a ChatGPT-beating model for $85k and run it in a browser?

#49
Are there any training/ownership models like Folding@Home? People could donate idle GPU resources in exchange for access to the data, and perhaps ownership. Then instead of someone needing to pony up $85k to train a model, a thousand people can train a fraction of the model on their consumer GPU and pool the results, reap the collective rewards.

Re: Could you train a ChatGPT-beating model for $85k and run it in a browser?

#50

If you have ~100k to spend, aren't there options to buy a gpu rather than just blow it all on cloud? How much is an 8xA100 machine? 4xA100 is 75k, 8 is 140k https://shop.lambdalabs.com/deep-learning/servers/hyperplane...

If you bought an 8xA100 machine for $140k you would have to run it continuously for over 10,000 hours (about 14 months) to train the 7B model. By that time the value of the A100s you bought would have depreciated substantially; especially because cloud companies will be renting/selling A100s at a discount as they bring H100s online. It might still be worth it, but it's not a home run.
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