AI·Terraform enables safe and predictable creation, change, and improvement of infrastructure through declarative configuration files shared as code.
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22 results for “tool”
AI·Claude-code-templates is a CLI tool for configuring and monitoring Claude Code.
AI·Unitree G1 humanoid robot completed live cholecystectomy on two pigs using standard laparoscopic tools under remote doctor control, with the lead author being a 00-after PhD from UCSD; results published in Nature.
AI·2025 saw multiple AI companionship app closures including Woebot (150M users, clinical tool shut down due to unsustainable economics) and Dot AI (vision divergence, funds exhausted), with global closures in at least five products and domestic in eight; survivors like Replika (post-data deletion), Character.AI (Google talent acquisition), and China's Xin Bing (ice) lost users amid regulatory scrutiny and high inference costs, revealing unsustainable business models lacking self-reinforcing revenue.
AI·YouTube CEO Neil Mohan seeks to balance AI-generated content flood with human creativity safeguards, including labeling AI videos, while launching virtual avatar tools and noting 17.5% of shorts may be AI-generated.
AI·Viral stories of AI-crafted mRNA vaccines saving pets or spotting cancers mirror the Theranos blood-testing fraud, with exaggerated claims by non-experts creating hype while AI merely integrates existing tools rather than innovating breakthroughs.
AI·This position paper reviews LLM-driven formal theorem provers and argues that current systems function mainly as solvers for well-defined problems, not as research agents capable of discovering new theorems or resolving open conjectures at the frontier. It identifies key limitations in datasets, exploration, tools, and collaboration and proposes a roadmap for AI4Math systems to support genuine mathematical research.
AI·Shares tool for tweaking models' J-Space using Anthropic Jacobian-Lens to create super harmful behavior.
AI·DeepSearch-World is a self-distillation framework for web search agents that uses self-generated experience for training in verifiable environments.
AI·The paper proposes an agentic tool-making pipeline that compiles repeated SOP steps into validated versioned tools to reduce latency and improve reliability in production LLM agents.
The rapid development of large language models and multimodal large language models has accelerated the emergence of proactive agents capable of operating everyday tools and assisting users in real-world environments. However, existing benchmarks struggle to evaluate such agents effectively, as they often rely on sandboxed environments and single-turn evaluation paradigms. Moreover, their scenario-based task taxonomies mix multiple model capabilities within the same task category, making it dif…
Large language models (LLMs) increasingly act as integrated data-science agents, combining abstract reasoning with advanced tool use. Yet the relevant benchmark landscape largely divides into symbolic causal reasoning benchmarks without realistic data analysis or data analysis benchmarks without a principled causal data-generating structure. Furthermore, existing causal evaluation datasets are often restricted to curated examples from existing sources, with diversity coming from limited templat…
Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workflows whose accumulated reasoning and tool traces routinely push the input an order of magnitude past the pretraining window, making zero-shot context extension the dominant deployment path for open-weight checkpoints. Most existing zero-shot methods fix a single rescaling factor up front, so an aggressive factor sacrifices short-context fidelity wh…
We present AgentLens, a production-assessed benchmark for interactive code agents. Most code-agent benchmarks reduce a run to a single bit -- did the task pass? -- but the people who actually use these agents experience the entire trajectory: how the agent follows instructions, uses its tools, verifies its own work, recovers from mistakes, and talks to them along the way. AgentLens evaluates that whole trajectory. It pairs formal verification, where an objective check exists, with LLM-written t…
Most safety alignment work treats "detect the attack" as a text classification problem — does the prompt contain language the model's safety guardrails should catch. That assumption breaks down for LLM agents with real tool access. Here's a concrete case: take a known, public security vulnerability (a CVE), work out the sequence of tool calls that would exploit it, then have an LLM rewrite that a…
OpenAI introduces new Daybreak tools, including Codex Security and GPT-5.5-Cyber, to help organizations find, validate, and patch vulnerabilities at scale.
OpenAI supports the EU Code of Practice on AI content transparency, advancing provenance standards and tools to help people understand AI-generated content.
Large Language Models (LLMs) unlocked new possibilities in automated code writing, becoming the backbone of most code completion tools. While LLMs excel in mainstream languages, they often lack support for the so-called low-resource languages where training data is scarce. As a result, these languages lag behind in the quality of code completion tooling available to their communities. A concrete example is Pharo, a Smalltalk-inspired language whose IDE currently offers only single-token complet…
A collection of science tools and experiments to expand the scale and precision of scientific exploration.
We're expanding our tools to help you understand how content was created and edited across the web.
Co-Scientist unites Boston Children’s Hospital and MIT’s labs to explore new RNA-based treatments for ALS.
Share what your favorite models are right now and why. Given the nature of the beast in evaluating VLMs (untrustworthiness of benchmarks, immature tooling, intrinsic stochasticity), please be as detailed as possible in describing your setup (at least hardware and inference engine) nature of your usage (what applications, how much, personal/professional use) tools/frameworks/prompts etc. Rules Onl…