Lists (15)
Starred repositories
Un-0: an image generator powered by a simulated system of coupled oscillators, an example of an emerging physical computing substrate.
The design language that makes your AI harness better at design.
TMLR | This survey presents a comprehensive and structured synthesis of memory in LLMs and MLLMs, organizing the literature into a cohesive taxonomy comprising implicit, explicit, and agentic memor…
Extract residual-stream activations and apply steering vectors (including activation oracles) to any vLLM model during inference.
A Curated List of Vision-Language-Action (VLA) and World Action Models (WAM) Research and Beyond
Comprehensive ML/AI interview codex with iterative system design, production-ready code, and 2026 standards. Includes LLM/GenAI, RAG systems, agentic AI, and algorithms from scratch.
Research into AI engineering interview assignments, take-home challenges, and hiring practices from 2026
AgentFlow: In-the-Flow Agentic System Optimization
A benchmark for evaluating AI agents on frontier ultra long-horizon auto research tasks.
A research framework for evaluating proactive AI assistants through active user simulation
This repository contains the code to train and evaluate TRIBE v2, a multimodal model for brain response prediction
Use Garry Tan's exact Claude Code setup: 23 opinionated tools that serve as CEO, Designer, Eng Manager, Release Manager, Doc Engineer, and QA
The open-source app everyone uses to manage agents at work
Get the main content of any page as Markdown.
My personal Obsidian vault template. A bottom-up approach to note-taking and organizing things I am interested in.
AI agents running research on single-GPU nanochat training automatically
High-Performance Symbolic Regression in Python and Julia
Deep Learning Interpretability with Symbolic Regression
Hypernetworks that update LLMs to remember factual information
[ICLR 2026 Blogpost Track Poster] JustRL: Scaling a 1.5B LLM with a Simple RL Recipe
Interpretable Causal Diffusion Language Models
This repo has scripts to compare various powerful RL methods
Code, labs, and resources for O'Reilly AI Systems Performance Engineering: GPU optimization, distributed training, inference scaling, and full-stack tuning.
A project to digitalise results from physics into Lean.