Feb 28, 2024

Reinforcement learning from human feedback (RLHF) is widely used to fine-tune pretrained models to deliver outputs that align with human preferences. New work aligns pretrained models without the cumbersome step of reinforcement learning.

The combination of  language models that are equipped for retrieval augmented generation can retrieve text from a database to improve their output. Further work extends this capability to retrieve information from any application that comes with an API. 

Pruning weights from a neural network makes it smaller and faster, but it can take a lot of computation to choose weights that can be removed without degrading the network’s performance.

OpenAI is focusing on autonomous agents that take action on a user’s behalf. The maker of ChatGPT is developing applications designed to automate common digital tasks by controlling apps and devices, The Information reported.

An upstart chip company dramatically accelerates pretrained large language models. Groq offers cloud access to Meta’s Llama 2 and Mistral.ai’s Mixtral at speeds an order of magnitude greater than other AI platforms. Registered users can try it.

An update of Google’s flagship multimodal model keeps track of colossal inputs, while an earlier version generated some questionable outputs.

This week's top AI news and research stories featured Google's troubled Gemini launch, OpenAI's next act, Groq's blazing inference speed, and a method for faster network pruning. But first:

I think the complexity of Python package management holds down AI application development more than is widely appreciated. AI faces multiple bottlenecks — we need more GPUs, better algorithms, cleaner data in large quantities.

The Batch AI News and Insights: I think the complexity of Python package management holds down AI application development more than is widely appreciated. AI faces multiple bottlenecks — we need more GPUs, better algorithms, cleaner data in large quantities.