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Comment by jmbiven | Hacker News Reader

Jordan Volz wrote an article speculating about this earlier this year. First time I heard the term Large Data Model, which I love and plan on using.

https://medium.com/@jordan_volz/who-owns-the-future-looking-...

"I won’t claim it’s simple, but as we’ve built AI that can understand human language, we can similarly build AI that understands data...Instead of building a large language model, we instead can build large data models (LDMs?)."

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But how do we communicate with an entity that understands data but not human language?

It doesn't seem to me that that's a problem. You just put data in and expect data out.

For example, a weather continuation model could take in all the available weather data up to the present moment and provide a continuation of that, i.e. a weather forecast.

Likewise financial market predictions etc.

That's a good point, Math is just as much a communicable language as English, French, Japanese, etc... maybe even more so according to some formal definitions.

How about a multi-headed approach. LDMs specializing in certain data operating under one LLM that acts as our point of access?

> a weather continuation model could take in all the available weather data up to the present moment and provide a continuation of that

And it turns out to work really well:

https://arxiv.org/abs/2212.12794

predicts hundreds of weather variables, over 10 days at 0.25 degree resolution globally, in under one minute

Send it a sequence of raw UTF bytes and see what it replies with.

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