Let's be honest, Generative AI isn't going all that well
A sampling of recent news
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 1,521 posts.
A sampling of recent news
Anthropic researchers find weaknesses in cryptographic algorithms with Claude Mythos Preview
About an aggravating tool-calling regression in newer Claude models.
Today, we open sourced our Zero-Knowledge Proof (ZKP) libraries, fulfilling a promise and building on our partnership with Sparkasse to support EU age assurance.
I used to be one of these people. I read Yudkowsky and was like, OMG recursive self improvement hard takeoff AI is coming. Then I joined the real world and actually tried to do things. At comma, we ship a hardware product of similar complexity to a cell phone, and it’s really hard. Reality has lots of finicky details…
Large language models may be standardizing human expression and subtly influencing how we think, says study led by USC Dornsife researcher
Inside our performance sprint: the benchmarks Claude built, the loop each Slack thread ran, and the guardrails that let us ship 3,000 changes safely.
Scores represent the mean of the following eight benchmarks listed below, excluding xbench-DeepSearch. The Step 3.5 Flash score is derived under standard settings (i.e., $w/o$ Parallel Thinking).
A deep dive into the open weight Trinity Large model, covering architecture, sparsity, training at scale, and why we shipped Preview, Base, and TrueBase checkpoints.
Does AI-assisted cognition threaten human development? Explore the risks of AI-assisted thinking and learn strategies to use AI tools without freezing your critical thinking.
Why coding agents perform better in cohesive ecosystems like Go than fragmented ones like JavaScript or Python
As agents grow more capable, so does their potential blast radius. Here's what we learned building containment for claude.ai, Claude Code, and Cowork.
1991: T and P of ChatGPT, distillation, deep residual learning, LSTM, GAN
/prewalk hands the cheap model a trajectory, not a plan, retaining 92–97% of frontier pass rate at roughly half the cost on SWE-Bench Pro.
I'm a designer and creative technologist based in Brooklyn, NY.
The largest tell for me to tell where culture and sentiment is shifting for AI tools is usually X, viral GitHub repositories and Hacker News. One of these tells I’ve been seeing a lot lately is skills like I have ADHD and Agents.md instructions such as giving outputs in only ASD-STE100 Simplified Technical English.
Frontier models can now produce novel historical knowledge, but in a really weird way
Look at the monthly numbers...
Soon, access to frontier AI will be scarce and selective
LLM-based agents can do a lot of tasks. Or, at least, they can appear to do them. For example, they write code, summarize papers, plan trips, and fill in forms. If you ask one for a probability or a confidence score, it will give you one of those too. I have seen many agent designers use LLMs to generate confidence…
Agents are unlocking enormous productivity gains for customers, but their ability to work across files, networks, and applications can introduce new security risks. This can leave customers feeling like they only have two choices: give agents unrestr
Any sufficiently complicated AI system contains an ad hoc, informally-specified, bug-ridden implementation of half of DSPy.
The Claude Platform on AWS is now generally available, offering a new way for AWS customers to access the full set of Claude platform features with AWS authentication, billing, and commitment retirement.
Introducing FLUX.2 [klein], our fastest image models. Unified generation and editing in under a second, on hardware you already own. Apache 2.0 on 4B.
Fable is cool yo, it takes jobs yo, - Dario "steve" Altman
Ask Claude to explain a concept or analyze your data, and it can respond with interactive charts, diagrams, and visualizations — rendered inline as part of the conversation.
At the core of the attention mechanism in LLMs are three matrices: Query, Key, and Value. These matrices are how transformers actually pay attention to different parts of the input. In this write-up, we will go through the construction of these matrices from the ground up.
Fable’s price ended the free lunch of ever-cheaper frontier models. Now we have to think about which model gets which work.
“The devil is in the details,” they say.