AI research & data tools for developers

Dynamic continual learning model trained on 8GB VRAM

mini-AGI is a byte-level language model that trains from scratch on a single 8 GB VRAM GPU and keeps learning from a continuous stream of text. Weights live on disk and are paged onto the GPU as needed, so model size is bounded by disk spac

💬 0Y▲ 277 on HNLLMs & InfrastructureResearch & DataOpen Sourceby AI Launch Team

A visualization of the attention mechanism in LLMs.

An interactive visualization of the attention mechanism in a small large language model. Hover or tap any generated token to see which earlier tokens influenced it, with opacity scaled by attention weight across all heads and layers. Exampl

💬 0Y▲ 177 on HNResearch & DataLLMs & InfrastructureFreeby AI Launch Team

A reproducible benchmark for typed decision models

JevBench, from Benchmark Heaven, compares Jev-class decision models across intelligence, calibration, speed and cost. It sits alongside Benchmark Heaven's broader model rankings, which can be filtered by provider, lab, hosting region and da

💬 0Y▲ 153 on HNResearch & DataLLMs & InfrastructureFreeby AI Launch Team

Build the smallest neural network that plays strategy games well

TinyBrains is a ranked ladder for small neural networks that play strategy games. Train a model, write an adapter, upload two files, and get measured into a weight class starting at 8 KiB. First shared by its maker on Show HN: https://news

💬 0Y▲ 116 on HNResearch & DataFreeby AI Launch Team

How well can models one-shot a Pac-Man game?

PacBench tests how well a model and harness can recreate Pac-Man from one prompt: "Create a Pac-Man game in a single html page." Entries from different models and harnesses can be sorted by score, cost, time and tokens, with run data for ea

💬 0Y▲ 78 on HNCoding & Dev ToolsResearch & DataFreeby AI Launch Team

How long until a local LLM rig pays for itself?

Sunk Cost estimates how long a machine for running local AI models takes to pay for itself compared with paying for an API. Pick a Mac mini, Mac Studio, DGX Spark or Strix Halo box, see which open models fit and how fast they run, and adjus

💬 0Y▲ 47 on HNLLMs & InfrastructureResearch & DataFreeby AI Launch Team