Machine Intelligence - 2026

A chronological archive of Machine Intelligence reading list posts.

2024

April 2024

πŸ”— MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training

πŸ”— Enhancing GPT's Response Accuracy Through Embeddings-Based Search

πŸ”— Cheat Sheet: 5 prompt frameworks to level up your prompts

πŸ”— Emergent Mind

πŸ”— The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey

πŸ”— Full Steam Ahead: The 2024 MAD (Machine Learning, AI & Data) Landscape

πŸ”— Replicate.com

πŸ”— Natural language instructions induce compositional generalization in networks of neurons

πŸ”— Outset.ai: Revolutionizing User Surveys with GPT-4

πŸ”— Awesome Code AI

πŸ”— How to unleash the power of AI, with Ethan Mollick

πŸ”— Bland.ai Turbo

πŸ”— OpenAPI AutoSpec

πŸ”— What Is an AI Anyway? | Mustafa Suleyman | TED

πŸ”— CometLLM: Logging and Visualizing LLM Prompts

πŸ”— What Computers Cannot Do: The Consequences of Turing-Completeness

πŸ”— Accelerating AI Image Generation with MIT's Novel Framework

πŸ”— Generative AI is still a solution in search of a problem

πŸ”— Anthropic's Prompt Engineering Interactive Tutorial

πŸ”— Hello OLMo: A truly open LLM

πŸ”— More Agents Is All You Need

πŸ”— Screen Recording to Code

πŸ”— LLM inference speed of light

πŸ”— How (Specifically) AI Will 100x Human Creativity and Output

πŸ”— Here’s Proof You Can Train an AI Model Without Slurping Copyrighted Content

πŸ”— The Question No LLM Can Answer

πŸ”— Comprehensive Guide to AI Tools and Resources

πŸ”— Financial Market Applications of LLMs

πŸ”— LLM in a flash: Efficient Large Language Model Inference with Limited Memory

πŸ”— This prompting technique is insanely useful

πŸ”— GR00T: NVIDIA's moonshot to solve embedded AI

πŸ”— OpenAI Create Batch

πŸ”— RAFT: A new way to teach LLMs to be better at RAG

πŸ”— Transformer Math 101

πŸ”— The Death of the Big 4: AI-Enabled Services Are Opening a Whole New Market

πŸ”— Embeddings are a good starting point for the AI curious app developer

πŸ”— CoreNet: A Library for Training Deep Neural Networks

πŸ”— The Pipe

πŸ”— Thoughts on the Future of Software Development

πŸ”— Dify

πŸ”— Making Deep Learning Go Brrrr From First Principles

πŸ”— Stanford AI Index Report 2024: An In-depth Analysis of AI's Current State

πŸ”— VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time

πŸ”— 3Blue1Brown: Neural Networks

πŸ”— Looking for AI Use Cases

πŸ”— Adobe Is Buying Videos for $3 Per Minute to Build AI Model

πŸ”— An Agentic Design for AI Consciousness


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