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The most popular blog posts about ai & machine learning on Hacker News. 6,331 posts.
The past week was a momentous occasion for protein structure prediction, structural biology at large, and in due time, may prove to be so for the whole of life sciences. CASP14, the conference for …
This document proposes an analysis of the systemic impact of AI systems, and in particular ones based on Machine Learning models, on the Web, and the role that Web standardization may play in managing that impact.
One of my favorite ¹ concepts for multi-dimensional data visualization is the Chernoff Face . The idea here is that for a dataset with many...
Protein “language” is a lot like human language. Given the similarities, researchers have been building and training language models on protein sequence data, replicating the success seen in other domains, with profound implications. In this post, I will explore how transformer models have been applied to protein data…
Posted by Chris Shallue, Software Engineer, Google Brain TeamIn 2014, research scientists on the Google Brain team trained a machine learning syste...
Practical guide to improving LLM finetuning with better instruction datasets, covering data curation, prompt-output pairs, synthetic data, and experiment ideas.
Matthew Honnibal is a computational linguist from Sydney based in Berlin, Germany. He's the author of the spaCy Natural Language Processing library and the co-founder of Explosion.
The lead in the last month or so was an indicator of having good chances, but there was a huge shuffling of ranks in the last week and some last minute casualties.
In high-dimensional vector spaces, numerical optimization is omnipotent.
For some inane reason, Github classifies me as a "major open source maintainer", which means I get a free copilot subscription.1 I've been using it for a...
We have been learning quickly from how people are using Sora and taking feedback from users, rightsholders, and other interested groups. We of course spent a lot of time discussing this before...
From magical to frustrating in months. Why AI coding agents feel like dial-up internet and what ultra-fast inference could unlock for developer productivity.
Serious learning requires friction, frustration... and other humans
Company updates and technology articles from Scale AI.
A little AI tells detector helps us promote good writing.
TL;DR: MCP tool definitions can burn 55,000+ tokens before an agent processes a single user message. We built the Apideck CLI as an AI-agent interface instead:an ~80-token agent prompt replaces tens of thousands of tokens of schema, with progressive disclosure via `--help` and structural safety baked into the binary…
The team and I are pumped to be back at Build with the developer community this year. Over the last year, Windows has continued to see incredible growth fueled by Windows 11 adoption. In fact, one of the mo
Model Context Protocol (MCP) has became the standard for tool calling when building agents, but contrary to popular belief your LLM does not need to understand MCP.
Back in 2009 I posted a simple Mandelbrot fractal viewer on the web: a single HTML file with inline Javascript. Just 329 lines of code, each pixel a tiny table cell. Click to zoom. Watch it iterate. That was about it!
I’ve been coding entirely with Claude Code for the past two months. At first it was exhilarating. I was speeding through tasks. I was committing like mad.
Posted by Petros Maniatis and Daniel Tarlow, Research Scientists, Google Software isn’t created in one dramatic step. It improves bit by bit, one l...
The evolution of the AI landscape, and YC's Copilot era.
Automated attack surface analysis and reduction can meaningfully improve the security of deployed software in the near term. In this post, we preview data we’ve collected from applying attack surface reduction techniques to large open-source codebases using Claude.
This is the story of how I used a Gmail message to trigger code execution through Claude Desktop, and how Claude itself (!) helped me plan the attack.
The state of California just made it clear: Face recognition surveillance isn’t inevitable. We can — and should — protect our communities from this dystopian technology.
I wrote earlier about a neural net-powered dungeon crawling text adventure game called GPT-2-Adventure in which gameplay is incoherent and dreamlike, as you encounter slippery sign text, circular passages, and unexpected lozenge rooms. A PhD student named Nathan trained the neural net on classic dungeon crawling…
Building a simple neural net in Java.
MIT researchers have developed a machine-learning system that can comb through repairs to open-source computer programs and learn their general properties, in order to produce new repairs for a different set of programs.
