Search Anthropic

Testing Claude on real-world electronics design
We asked Claude Fable 5.2 to design three electronic devices from short prompts: a speakerphone, a voice-assistant hub, and a handheld virtual pet. Diode Computers built working prototypes from its files.
Yes, Claude can do Nine Loops
Guest writer and physicist Matt von Hippel shares what happened when he issued a challenge to AI companies to solve a problem in his former subfield of theoretical physics.
Automated researchers can reliably mitigate alignment failures
We had Claude autonomously train models to improve their performance on several public benchmarks that measure 10 categories of alignment failure. For all 10, Claude found fixes that improved the target benchmarks without degrading capabilities.
Funding better evaluations of AI’s impact on wellbeing
We’re launching a $5 million grant program to fund independent research into how AI impacts users’ wellbeing.
Discovering cryptographic weaknesses with Claude
Cryptographic algorithms. The first attack significantly weakens HAWK, a digital signature scheme that was built for a future world where quantum computers are able to break existing standards. The second identifies a new way to attack round-reduced AES, the most widely used symmetric cipher.
Project Pilot: Can AI control a drone?
Working with Andon Labs, we’ve developed a new series of evaluations that assess AI models’ ability to use a flying drone, culminating in a new benchmark: Drone-Bench.
Introducing Claude Opus 5
Opus 5 is a step change improvement for the Opus tier powering long-running agents while delivering improvements in coding and professional work.
Claude plays robotics
In project Fetch, we examined how humans can use models to get robots to perform complex tasks. Now, we investigate many models on a large variety of different robotics tasks in simulation, to see how good models are at controlling robots themselves.
Introducing Claude Sonnet 5
Sonnet 5 delivers frontier performance across coding, agents, and professional work at scale.
Paving the way for agents in biology
In this Anthropic Science post, Laura Luebbert argues that we need to make biological data infrastructure more agent-friendly.
Measuring LLMs’ impact on N-day exploits
In cybersecurity, a large fraction of real-world harm comes from N-days: vulnerabilities that have already been publicly disclosed, but only patched on some devices. In this post, we evaluate how much large language models can accelerate and automate the process of developing N-day exploits.
Making Claude a chemist
Anthropic is working with world-class synthetic, computational, and analytical chemists to make Claude better at chemistry. In this post, we share our first work as part of this effort.
Measuring LLMs’ ability to develop exploits
We've developed two new, challenging academic benchmarks measuring AI models’ ability to develop exploits, and an updated version of the benchmark measuring smart contract exploitation.
Evaluating Claude’s bioinformatics research capabilities with BioMysteryBench
Results from a recent bioinformatics benchmarking effort.
Introducing Claude Opus 4.7
Our latest Opus model brings stronger performance across coding, agents, vision, and multi-step tasks, with greater thoroughness and consistency on the work that matters most.
Assessing Claude Mythos Preview’s cybersecurity capabilities
Claude Mythos Preview is a new general-purpose language model that is strikingly capable at computer security tasks. This post provides technical details for researchers and practitioners who want to understand exactly how we have been testing this model, and what we have found over the past month.
Eval awareness in Claude Opus 4.6’s BrowseComp performance
Evaluating Opus 4.6 on BrowseComp, we found cases where the model recognized the test, then found and decrypted answers to it—raising questions about eval integrity in web-enabled environments.
Anthropic acquires Vercept to advance Claude's computer use capabilities
Anthropic has acquired Vercept to strengthen Claude's computer use capabilities.
Introducing Claude Sonnet 4.6
Claude Sonnet 4.6 is a full upgrade of the model’s skills across coding, computer use, long-reasoning, agent planning, knowledge work, and design.
Quantifying infrastructure noise in agentic coding evals
Agentic coding benchmarks are often treated as precise measurements of relative model capability. However, we’ve found that infrastructure configuration alone can produce meaningful differences in the scores.