1981
Using Large Language Models to Catch Vulnerabilities
Posted by the Big Sleep team Introduction In our previous post, Project Naptime: Evaluating Offe...
Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 3,242 posts.
1982
Life of an inference request (vLLM V1): How LLMs are served efficiently at scale
vLLM is an open-source inference engine that serves large language models. We deploy vLLM across GPUs and load open weight models like Llama 4 into it. vLLM sits at the intersection of AI and systems programming, so we thought that diving into its details might interest our readers.
1983
Introducing gpt-oss
We’re releasing gpt-oss-120b and gpt-oss-20b—two state-of-the-art open-weight language models that deliver strong real-world performance at low cost. Available under the flexible Apache 2.0 license, these models outperform similarly sized open models on reasoning tasks, demonstrate strong tool use capabilities, and…
1984
1985
HealthBench – An evaluation for AI systems and human health
HealthBench is a new evaluation benchmark for AI in healthcare which evaluates models in realistic scenarios. Built with input from 250+ physicians, it aims to provide a shared standard for model performance and safety in health.
1986
JetBrains IDEs Go AI: Coding Agent, Smarter Assistance, Free Tier
All JetBrains AI tools – including our improved AI Assistant and new coding agent Junie – are now available within our IDEs under a single subscription and come with a free tier.
1987
Cerebras Inference: AI at Instant Speed
We are excited to announce the release of Cerebras DocChat, our first iteration of models designed for document-based conversational question answering. This series includes two models: Cerebras Llama3-DocChat, a large language model (LLM), and Cerebras Dragon-DocChat, a multi-turn retriever model.
1988
Designing more efficient quantum circuits with Claude
Working largely on its own, Claude designed quantum circuits that improve on the best published versions, in some cases by an order of magnitude or more.
1989
Stable Diffusion launch announcement
The model itself builds upon the work of the team at CompVis and Runway in their widely used latent diffusion model combined with insights from the conditional diffusion models by our lead generative AI developer Katherine Crowson, Dall-E 2 by Open AI, Imagen by Google Brain and many others. We are
1990
AARON: AI Art Generator from 1973
Harold Cohen (1928 – 2016) explored AI and art for nearly 50 years before we saw the rising popularity of these new machine learning tools. In those five decades, Cohen worked on a single program called Aaron that involved teaching a robot to create drawings. Aaron’s education took a similar pa
1991
Horizon: Facebook’s Open Source Applied Reinforcement Learning Platform
In this paper we present Horizon, Facebook’s open source applied reinforcement learning (RL) platform. Horizon is an end-to-end platform designed to solve industry applied RL...
1992
1993
We made Grok 4.5, GPT-5.5, and Claude build the same apps
Grok 4.5 just launched. So we had it, GPT-5.5, Claude Opus 4.8, and Fable 5 one-shot the same interactive apps, then measured latency and cost. Here is who won.
1994
1995
1996
1997
Against LLM Maximalism
LLMs are not a direct solution to most of the NLP use-cases companies have been working on. They are extremely useful, but if you want to deliver reliable software you can improve over time, you can't just write a prompt and call it a day. Once you're past prototyping and want to deliver the best system you can…
1998
Introducing LFM3: Every Modality for Specialized Intelligence
LFM3 is Liquid AI’s new open-weight model family: 2B-class text, vision, audio, omni, and decision models built to fine-tune and run fast on any device.
1999
Agents that imagine and plan
Imagining the consequences of your actions before you take them is a powerful tool of human cognition. When placing a glass on the edge of a table, for example, we will likely pause to consider how stable it is and whether it might fall. On the basis of that imagined consequence we might readjust the glass to prevent…
2000
Google Research: Themes from 2021 and Beyond
Posted by Jeff Dean, Senior Fellow and SVP of Google Research, on behalf of the entire Google Research community Over the last several decades, I'v...
2001
How to use Alpaca-LoRA to fine-tune a model like ChatGPT
Low-rank adaptation (LoRA) is a technique for fine-tuning models that has some advantages over previous methods:
2002
Building a recommendation engine inside Postgres with Python and Pandas (2020)
Learn how you can leverage Python and Pandas from directly inside PostgreSQL to build your own recommendation engine.
2003
2004
2005
Circuit Tracing: Revealing Computational Graphs in Language Models (Anthropic)
We describe an approach to tracing the “step-by-step” computation involved when a model responds to a single prompt.
2006
2007
The Alan Turing Institute has failed to develop modern AI in the UK
The UK’s flagship institute for artificial intelligence, the Alan Turing Institute, has been at best irrelevant to the development of modern AI in the UK.
2008
How AI is affecting productivity and jobs in Europe
Artificial intelligence promises to reshape economies worldwide, but firm-level evidence on its effects in Europe remains scarce. This column uses survey data to examine how AI adoption affects productivity and employment across more than 12,000 European firms. The authors find that AI adoption increases labour…
2009
Pixel Visual Core: Google’s first custom-designed co-processor
Google’s first custom-designed co-processor for consumer products is built into every Pixel 2. Soon, it will enable more applications to use Pixel 2’s camera for taking …
2010
Fixing Tool-Call Accuracy in vLLM
Tool call accuracy is an important part of serving open-weight AI models. When your tool calls aren’t accurate, the model builds up on nonsensical context. We’ve been carrying our own fork of vLLM to hit 100% in tool call schema accuracy with Kimi and DeepSeek. Fortunately, vLLM 0.31 added support for constrained…