llrt VS gpt-neox

FROM --platform=arm64 busybox WORKDIR /var/task/ COPY app.mjs ./ ADD https://github.com/awslabs/llrt/releases/latest/download/llrt-container-arm64 /usr/bin/llrt RUN chmod +x /usr/bin/llrt ENV LAMBDA_HANDLER "app.handler" CMD [ "llrt" ]

Let’s get the simplest use case out of the way: cases where the cold starts are so fast that it’s not an issue for you. That’s usually the case for function that use runtimes such as C++, Go, Rust, and LLRT. However, you must follow the best practices and optimizations in every runtime to maintain a low impact cold start.

But compared to other runtimes, LLRT is not so good in terms of performance when it comes to dealing with large data processing, Monte Carlo simulations, or performing tasks with a large number of iterations. The AWS team says that it is best suited for working with smaller Serverless functions dedicated to tasks such as data transformation, real-time processing, AWS service integrations, authorization, validation, etc. Visit the GitHub repository of this project to learn more information.

And lastly, lean into your cloud vendor. Stop trying to build a better mouse trap. Advances in technology are happening all the time. The speed of AWS' Lambda has been rapidly improving over the past couple of years with the launch of things like SnapStart and LLRT

It seems they just added the mention to QuickJS, I assume, based on your feedback:

https://github.com/awslabs/llrt/commit/054aefc4d8486f738ed3a...

Props to them on the quick fix!

Gpt neox 20B can be used commerically.

GPT-Neo: GPT-Neo is a free and open-source language model developed by EleutherAI. It is a powerful model that can be used for a variety of tasks, including text generation, and question-answering. here is the GitHub

Doesn't gpt-neox 20b require like 40gb+ of VRAM? From their github repo the slim weights are 39GB and I think one of the devs has previously mentioned aiming for 48GB for inference.

3.) EleutherAI's GPT-Neo and GPT-NeoX: EleutherAI is an independent research organization that aims to promote open research in artificial intelligence. They have released GPT-Neo, an open-source language model based on the GPT architecture, and are developing GPT-NeoX, a highly-scalable GPT-like model. You can find more information on their GitHub repositories: GPT-Neo: https://github.com/EleutherAI/gpt-neo GPT-NeoX: https://github.com/EleutherAI/gpt-neox

It's really not that complicated. https://github.com/EleutherAI/gpt-neox

this forces me to create my own ai using gpt-neox .. i was being lazy, completely satisfied with my little ai baby .. i'll keep the account but not renew pro .. fuck luka, inc ... want it done right, do it yourself .. the python isn't that difficult and i have a spare linux vps .. my new work in progress .. freedom #!