181
Donating the Model Context Protocol and establishing the Agentic AI Foundation
Anthropic is donating the Model Context Protocol to the Linux Foundation's new Agentic AI Foundation, co-founded with Block and OpenAI.
Most cited
Posts that commenters keep linking to, ranked by how many different people have cited them in Hacker News comments. 205 posts.
182
Deploying DeepSeek on 96 H100 GPUs
DeepSeek is a popular open-source large language model (LLM) praised for its strong performance. However, its large size and unique architecture, which uses Multi-head Latent Attention (MLA) and Mixture of Experts (MoE), require an advanced system for efficient serving at scale.
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AI coding tools can reduce productivity
Study Shows That Even Experienced Developers Dramatically Overestimate Gains
184
Marble: A Multimodal World Model
Marble, our frontier multimodal world model, is available to everyone starting today
185
The Einstein AI Model
I shared a controversial take the other day at an event and I decided to write it down in a longer format: I’m afraid AI won't give us a compressed 21st century.
186
Developing our position on AI
This post is about how we've tried to develop a position on AI in the context of learning and growth at RC.
187
What if you don't need MCP at all?
Got Bash and some code interpreter? Skip MCP.
188
AI is not our future
We are not adding generative AI to our apps. Here's why.
189
Why LLMs still have problems with OCR
LLMs excel at text generation but fail at precise document extraction due to nondeterminism. | Pulse AI
190
Composer: Building a fast frontier model with RL
Composer is our new agent model designed for software engineering intelligence and speed.
191
Just talk to it – A way of agentic engineering
A practical guide to working with AI coding agents without the hype.
192
Who Invented Backpropagation?
Its modern version (the reverse mode of automatic differentiation) was first published in 1970 by Seppo Linnainmaa
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Project Vend: Phase Two
How Claude turned around its failing vending machine business
195
Windsurf SWE-1: Our First Frontier Models
Introducing our first Frontier Models!
196
Revenge of the Chickenized Reverse-Centaurs
In AI circles, a “centaur” describes a certain kind of machine/human collaboration, in which “decision-support” systems (which the field loves to call “AI”s) are paired with human beings for results that draw upon the strengths of each, such as when a human chess master and a chess-playing computer program collaborate…
197
How much Anthropic and Cursor spend on Amazon Web Services
So, I originally planned for this to be on my premium newsletter, but decided it was better to publish on my free one so that you could all enjoy it. If you liked it, please consider subscribing to support my work. Here’s $10 off the first year of annual.
198
Open-sourcing circuit tracing tools
Our open-source tools generate attribution graphs showing how language models reach decisions.
199
The (economic) AI apocalypse is nigh
Like you, I'm sick to the back teeth of talking about AI. Like you, I keep getting dragged into discussions of AI. Unlike you‡, I spent the summer writing a book about why I'm sick of writing about AI⹋, which Farrar, Straus and Giroux will publish in 2026.
200
The "AI 2027" Scenario: How realistic is it?
Everyone’s been talking about it. JD Vance read it. What does it actually tell us?
201
Understanding Spec-Driven-Development: Kiro, Spec-Kit, and Tessl
Notes from my colleagues on AI-assisted software delivery
202
Qwen2.5-Max: Exploring the intelligence of large-scale MoE model
QWEN CHAT API DEMO DISCORD It is widely recognized that continuously scaling both data size and model size can lead to significant improvements in model intelligence. However, the research and industry community has limited experience in effectively scaling extremely large models, whether they are dense or…
203
Claude Code Is My Computer
I run Claude Code with --dangerously-skip-permissions flag, giving it full system access. Let me show you a new way of approaching computers.
204
Design Patterns for Securing LLM Agents Against Prompt Injections
This new paper by 11 authors from organizations including IBM, Invariant Labs, ETH Zurich, Google and Microsoft is an excellent addition to the literature on prompt injection and LLM security. …
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