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Awesome Rust

I learn Rust by reading The Rust Programming Language (aka. TRPL) book.

This is my mind map and collection of resources for learning Rust in early 2019.

I plan to continuously update this list if time allows in future. I will move this into its own GitHub repo or something more permanent when this grow.

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🐐 Llama 3.1 405B matches or beats the best closed models

Llama 3.1 405B, 70B, 8B is officially out. Llama 3.1 405B is the first openly available model that matches or beats the best closed models across many benchmarks.

Model evaluations

The performance of 405B model is very similar to Claude 3.5 Sonnet. It beats GPT4 on every single benchmark but one.

70B model has an even more impressive performance. It is significantly better than GPT-3.5 Turbo and beats Nemotron 4 340B on many tests.

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Llama 3.1 Leaks: SoTA Open Model 405B & What We Know So Far

TLDR: 8B gets a big bump across the board, 70B instruct shows minor improvements, and 405B is the SoTA open model. But 405B still lags behind flagship models.

Here are the notable upgrades:

• Every model now supports 128k context length (up from 8k)
• Trained on a massive ~15T tokens of public data
• Fine-tuning data includes publicly available instruction datasets and over 25M synthetically generated examples
• Multilingual support for 7 languages: French, German, Hindi, Italian, Portuguese, Spanish, and Thai

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Vibe checking Claude 3.5, DeepSeek-Coder-V2, and GPT-4o for "alien" Coding Skills

Introduction

In the world of AI and LLM, it's often said that "vibe checks" can provide valuable insights into model performance. With this in mind, I've conducted a brief evaluation of Claude 3.5 Sonnet, DeepSeek-Coder-V2, and GPT-4o to assess their capabilities in solving complex coding problems. This evaluation aims to provide a better intuition of these models' strengths and weaknesses, verifying findings published in public benchmarks and leaderboards.

Evaluation Design

For this assessment, I selected a challenging problem from recent competitive coding competitions (2023 onwards). The chosen problem, "Power of Heroes", is a dynamic programming challenge that requires advanced knowledge of algorithms and data structures. This problem was selected because:

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Co-Intelligence: Living and Working with AI - A Book Review

In 200 Words

If you're just dipping your toes into the AI pool, Ethan Mollick's "Co-Intelligence" is a solid starting point. But let's be clear — when we're talking AI here, we're really discussing the cutting-edge innovations: those Large Language Model (LLM) powered Generative AI applications that are creating buzz in the tech world.

Book cover	Sample pages

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info 9-3-23 Added 4bit LLaMA install instructions for cards as small as 6GB VRAM! (See "BONUS 4" at the bottom of the guide)

warning 9-3-23 Added Torrent for HFv2 Model Weights, required for ooga's webUI, Kobold, Tavern and 4bit (+4bit model)! Update ASAP!

danger 11-3-23 There's a new torrent version of the 4bit weights called "LLaMA-HFv2-4bit". The old "LLaMA-4bit" torrent may be fine. But if you have any issues with it, it's recommended to update to the new 4bit torrent or use the decapoda-research versions off of HuggingFace or produce your own 4bit weights. Newer Torrent Link or [Newer Magnet Link](magnet:?xt=urn:btih:36945b5958b907b3ab69e963ba0de1abdf48c16c&dn=LLaMA-HFv2-4bit&tr=http%3a%2f%2fbt1.archive.org%3a6969%2fannounce&tr=http%3a%2f%2fbt2.archive.org%3a696

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4 Steps in Running LLaMA-7B on a M1 MacBook

The large language models usability

The problem with large language models is that you can’t run these locally on your laptop. Thanks to Georgi Gerganov and his llama.cpp project, it is now possible to run Meta’s LLaMA on a single computer without a dedicated GPU.

Running LLaMA

There are multiple steps involved in running LLaMA locally on a M1 Mac after downloading the model weights.

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Voice AI Research

Goal: make computers talk like human.

My notes from audio (voice + speech) AI research started in 2023.

Emerging Research

Audio-to-audio Models

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Summary of "Clean Code" by Robert C. Martin

A summary of the main ideas from the "Clean Code: A Handbook of Agile Software Craftsmanship" book by Robert C. Martin (aka. Uncle Bob).

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.

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General rules

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AI Agents

In response to Dr. Andrew Ng's letter, "Four AI agent strategies that improve GPT-4 and GPT-3.5 performance".

When I read Andrew's letter, I'm imagining him as Steve Balmer, shouting "Agentic, agentic, agentic workflows!". Haha, we can hear you. No need for that.

Before we move on, let's be clear what is agent in this context. The context is, we're now in 2024 and LLMs such as GPT-4 and Llama 3 is the state-of-the-art. In early 2022, everybody in the field knew about the agent from RL, but the general public had no conception of what it was. Their narrative were still everything is a chatbot. All sorts of different things are being called agents. Chatbots are being called agents. Things that make a function call are being called agents. Now when people think agent, they actually think the right thing.

An agent is something that you can give a goal and get an end step workflow done correctly in the minimum number