TLDR AI 2023-03-13

OPEN SOURCE CHATGPT REPLICATION TRAINED ON 43 MILLION INSTRUCTIONS

One of the reasons chatGPT is so powerful is because of the instruction tuning process. By feeding the model data formatted as instructions, it becomes much more likely to follow instructions that users give it. Openchatkit is a 20 billion parameter instruction tuned Transformer and other useful tools to make an open source replication of the powerful and popular chatbot.

GPT-4 IS COMING NEXT WEEK SAYS MICROSOFT GERMANY

CHERRY PICKING ROBOT WITH ONLY 30 MIN OF INTERACTION DATA

Data efficiency is one of the challenges of many reinforcement learning algorithms. It usually takes millions of environmental interactions before the agent starts to learn. This is often infeasible with real world robotic systems. This work is one example of a system that is more data efficient.

PIXMIM: A SIMPLE AND EFFECTIVE METHOD FOR MASKED IMAGE MODELING

The paper proposes PixMIM, a simple and effective method for Masked Image Modeling (MIM) that addresses two previously overlooked bottlenecks. PixMIM filters high-frequency components from the reconstruction target and adopts a conservative data transform strategy to alleviate the problem of missing foreground in MIM training. The method can be easily integrated into most existing pixel-based MIM approaches, improving three MIM approaches consistently across various downstream tasks without additional computation. PixMIM can serve as a strong baseline for self-supervised learning and provide insights for future improvements of the MIM framework.

RUN STATE OF THE ART LANGUAGE MODELS ON YOUR LAPTOP

By taking advantage of the new Apple neural computing system, you can run the llama models on m1 and m2 computers. You can even get many tokens per second for the smallest model. This points at an exciting future of personalized AI running on consumer grade hardware.

DEAD SIMPLE WAY TO RUN LANGUAGE MODELS

Powered by the above code, this project packages things up nicely and allows you to install and run the llama models with familiar web tools like npx.

TEXT-GENERATION-WEBUI

COMBINE PEFT WITH RLHF

Parameter efficient fine tuning (PEFT) is a way to update only a small fraction of the weights of a model. Reinforcement learning from human feedback (RLHF) is a similar step to instruction tuning that improves model generation quality and model alignment. By combining the two, you can tune large models up to 20 billion parameters on a relatively small GPU with 24GB of on chip memory. This process would usually require multiple A100s.

CHATGPT’S API MAKES MOST TEXT GENERATING AI OBSOLETE

CHATGPT IS NOW AVAILABLE IN AZURE OPENAI SERVICE

LARGE LANGUAGE MODELS ARE HAVING THEIR STABLE DIFFUSION MOMENT

This article dives into how Large Language Models are exploding in innovation and popularity similar to the explosion in generative AI following Stable Diffusions release in August 2022.

TOOLBOX

This GitHub Repo is a mix of machine learning guides and tools.

PAN-VARIANT COVID VACCINE DEVELOPED WITH ML