---
title: Things I Learned - 12 Nov 2023
date: 2023-11-12T00:00:00+00:00
categories:
  - til
description: I discovered Julius.ai for data queries and AutoGen for multi-agent systems. I also explored high-performance LLM inference using vLLM and DeepSpeed, alongside architectural patterns and critiques of the Foundation Model Transparency Index.
keywords: [julius.ai, autogen, vllm, deepspeed, llm architecture, multi-agent systems]
---

This week, I learned:

- [Julius.ai](https://julius.ai/) queries structured data.
- TODO: Explore <https://github.com/microsoft/TaskMatrix>
- [microsoft/autogen](https://github.com/microsoft/autogen) enables multi-agent conversations.
- [Architecture of today's LLMs](https://github.blog/2023-10-30-the-architecture-of-todays-llm-applications/) is similar to the A16Z architecture
- [Stanford Foundational Model Transparency index](https://crfm.stanford.edu/fmti/) was [critiqued as misleading](https://blog.eleuther.ai/fmti-critique/)
- [vLLM](https://vllm.ai/) runs HuggingFace transformers models faster. So does [DeepSpeed](https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-fastgen#introduction)