applgo443

What's the simple explanation for why these VLM OCRs hallucinate but previous version of OCRs don't?

Why are traditional OCRs better in terms of hallucination and confidence scores?

Can we use logprobs of LLM as confidence scores?

When i deploy a webapp on azure, it expects me to put env variables in a file or their own tool (key value fields) where you can add env variables one by one.

Is there a way to use envelope in places like those?

If it's 5 common crawls, isn't data across multiple common crawls mostly similar?

Is ETL/ELT same as writing SQL scripts and periodically executing them? I assumed there's more to it.

May be rewriting user's description might help you match code better?

Similar to the prompt engineering for previous era GPT completion models.

How do you approach the problem of what files to look into to fix a bug? Just embeddings doesn't seem to cut it.

How is your experience with Modal?

And I'm curious to know more about your costs of deployment and running on Modal.

Did you consider first asking LLM to explain what a code snippet does and use that instead?

It'd significantly increase the costs though.

I saw your comment, got curious, and looked at a lot of your old comments. Lots of interesting insights - Thanks for sharing them.

If you don't mind me asking, what do you do? I'm a researcher at FAANG working on language models and starting a new company in the space. Would love to connect. Feel free to email me - [email protected]

Used OpenAI APIs before but not function calling. What's the use of function calling in this example?

How does the confidence scores work?

I’m a researcher in the space exploring few ideas with the intention of starting up. Would love to reach out to you and talk to you. Is there a way I can contact you?

My email is [email protected]

I think we can detect atleast a few things like PII leaks etc. Don't you think those things alone are valuable?