AWS Bedrock is a fully-managed service that provides LLM interactions and has models from lots of leading organisations. In my opinion, it's a great way to get started with LLMs if you're using AWS since there's no worry about infrastructure scaling.

This post is a short description of how to get AWS Bedrock responding to your Rust code. It's a simple example, but should point the way forward for more complex interactions.

Large Language Models are hot stuff at present. Using them, and integrating them into workflows, is still an open-area of investigation for many people and organisations.

I'm currently using VSCode, the Continue 'open-source autopilot' extension, and Ollama.

I recently read Rebooting AI, as book discussing how the recent focus on Deep Learning as the path towards Artificial General Intelligence is flawed. It was a good read, and made many interesting points. It left me wanting to learn more about other areas of AI, and luckily there was a 'Suggested Reading' list at the end.

This is a Too Long; Didn't Read summary of the paper Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning. Inspired by the blog post on the same paper published by the Berkeley Artifical Intelligence Research (BAIR) Lab last week.