[zacksiri]

This is interesting. I think the future of AI will not be re-creating something like ChatGPT, but using variations of these methodologies to train AI models for specific tasks.

There are some advantages to not having to make an LLM that impresses every human being on the planet. Imagine training the AI to be good in only one specific thing. I think it will become much more precise and deterministic.

This is just my hypothesis. I'm excited to see where this goes.

[kkielhofner]

There is plenty of less attention-grabbing work being done on "domain specific LLMs" like BioMedLM[0], Med-PaLM[1], BloombergGPT[2], etc.

That reminds me - I saw a somewhat-clever acronym variant for LLM that communicated this the other day but it escapes me ATM...

[0] - https://www.mosaicml.com/blog/introducing-pubmed-gpt

[1] - https://cloud.google.com/blog/topics/healthcare-life-science...

[2] - https://dev.to/reaminated/thoughts-on-bloomberggpt-and-domai...

[zacksiri]

Yeah that's awesome. I honestly think the next 'leap' in AI will come from these 'domain specific' models.

Also I'm not talking about just 'prompt' output model. These ones are great and I'm sure they will be extremely impressive. However I'm talking more about being able to 'operate' something.

Imagine this, an AI able to operate some specific API in a deterministic / reliable way. I'm talking about complex operations.

SO the output is not so much a text prompt but an SOP and then actually Operating the SOP.

Imagine going into an app and say "can you boot up a cluster on AWS and run a wordpress site, point domain example.com to the site".

Imagine this "you know my database for app X, what was the latest snapshot", it replies with the date / time of the snapshot, and you reply with "can you move that snapshot from google cloud and create a new database from that snapshot on AWS cloud?", and it does it for you.

That's what I look forward to.

[kkielhofner]

So training an LLM on OpenAPI specs ;)?

It actually seems like more of a task for good 'ol fashioned NLP (intent recognition) with some wiring for all of the connectors...

[toomuchtodo]

https://news.ycombinator.com/item?id=35634120 (LlamaAcademy: Teach GPTs to understand API documentation with LoRA) ?

https://github.com/danielgross/LlamaAcademy

[antonvs]

> Imagine this, an AI able to operate some specific API in a deterministic / reliable way.

It doesn’t seem like LLMs are going to be able to do this, unless the application has a high tolerance for mistakes.

[zacksiri]

Maybe something new needs to be invented? Or utilize something we already have? Anyway I think this is the next leap in AI.

Operative Language Models. Where the model is trained to do specific tasks very well. In a reliable way. I don't anticipate them to be 'large' and expensive also.

Then we have lots of these models and some kind of 'orchestration' layer that makes them all work together. This I believe will be the future. Micro Operative Language Models.

[antonvs]

The next leap will be decided by what someone is able to actually implement, not by what anyone thinks it should be.

[zacksiri]

Yes! This is where I'm at!

[Tepix]

LangChain

[MrMovl]

I'm wondering about just that, I want to have a minimal model with little overhead that I can train to a specific body of texts but it doesn't need to know about all the rest. So basically it should be good at conversation and able to learn what I teach it, nothing else.

But I'm having trouble finding resources about how to achieve that.