chatgpt-failures VS llama.cpp

Related / fun :

https://emaggiori.com/chatgpt-fails/

(I don't know the author or the book.)

https://github.com/giuven95/chatgpt-failures

"Plausible explanations

There is a whole list of ChatGPT failures here. Such as the time traveling user error. Why did it insist the user had time traveled? Because when it made the initial error it feed that error into the "attention" of the conversation, using matrix addition, as if it was an authoritative fact of the evolving conversation. That matrix is the only actual piece of the conversation it retains for transforming new input from that user. The matrix addition nonlinear, so ChatGPT can't simply unwind such a mistakes and redo the matrix addition with valid information. So, when pressed, it generates the most "probable" explanation based on the best fit to the existing matrix at that time that defines the "true" state of the conversation as defined by that matrix. The "attention" part of ChatGPT, which is the part that makes it so convincingly powerful, is a matrix state that cannot unwind itself and reflect on how it came to that state. There is, and cannot be, a self correction mechanism using such a mechanism (matrix) to define the state of a conversation.

Is anybody compiling a list of errors specific to GPT-4?

This has been a great resource to-date:

https://github.com/giuven95/chatgpt-failures

As a result, it confidently asserts obvious inaccuracies, like "it takes 9 women 1 month to make a baby."

Here's a github repo of chatGPT failing. There's a PopSci article describing what chatGPT is doing, why it's susceptible to errors: It's trying to predict what words are used together, irrespective of what information is correct.

You could try any of the prompts ChatGPT failed from here https://github.com/giuven95/chatgpt-failures

In this article, the author Dmitri Brereton shows some mistakes the Bing AI committed in the recent Microsoft demo. I have archived more failure case examples in this repo: https://github.com/giuven95/chatgpt-failures

Previously it said 1.

if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp

the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...

And you can search for any GGUF on huggingface

Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182

For anyone interested in exploring this, llama.cpp has an example implementation here:

https://github.com/ggerganov/llama.cpp/tree/master/examples/...

Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.

well https://github.com/ggerganov/llama.cpp/issues/6849