burhanultayyab

It can be, however it's not fully deterministic, because the agent can hallucinate or misbehave, which is fairly common. Because MCP is a separate process, we can ensure that safety pipeline is fully followed.

Currently we are not tackling agent identity verification, however, it can be done by generating a public private key and authenticating based on that.

Faz is a middleware that sits between AI agents and databases and ensures all query passes through safety pipelines, so that your agents can't nuke your databases or access data that they are not supposed to.

This happened because AI agents are directly talking to databases or equivalent infrastructure, so it was bound to happen.

I've built something to fix it.

https://github.com/fazhq/faz

Faz sits between your AI agent and your database, so every query passes through a safety pipeline before it ever touches your data.

We're releasing NeuCore - a no code tool for your AI needs.

Currently, we have three AI models 1. Image Segmentation (performs better than Landing AI , and works with very few data points ). 2. Text Recognition (works with 80+ languages ) 3. Receipt Extraction (work with 12 languages, with almost every receipt design )

Check out the tool, and kindly give us feedback to improve it. We'll be adding more models in the future.

P.S: We believe Few Shot Learning would be the next big thing :)

I think all these models are oriented towards detecting people that are simply copying pasting text from these large language models into their assignments / homeworks.

If the text generated from these models are passed through an article spinner, there is no way these models can detect that it has been generated by an AI model.

At the end of the day, it's just a system to detect lazy people copying pasting stuff.

We've implemented DetectGPT paper in Pytorch. Our implementation can be found below

Github: https://github.com/BurhanUlTayyab/DetectGPT

Website: https://gptzero.sg

Discord: https://discord.com/invite/F3kFan28vH

We're also working on a GPTZerov2 (inspired by LLM based transformers and GANs), which would be more accurate, and can detect lines changed by humans.

Please give some feedback on our work.

Thanks

It's amazing what you guys are working on :)

We're working on v2 where two large LLMs fight with one another.

Thanks for the complement. We would be more cautious in the future.

You are correct, that's why we're working on a version 2 of it where we're using LLM Transformers fighting adverserially to make it better.

Thanks for the complement.

We've gone through the original implementation of GPTZero and successfully reverse engineer it. (it gives the same results as original GPTZero). We've also recorded the implementation process which can be found below.

Youtube Implementation Video: https://youtu.be/x9H-aY5sCDA

Github: https://github.com/BurhanUlTayyab/GPTZero

Website: https://gptzero.sg

Discord: https://discord.com/invite/F3kFan28vH

We're also working on a GPTZerov2 (inspired by LLM based transformers and GANs), which would be more accurate, and can detect lines changed by humans.

Please give some feedback on our work.

Thanks