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Gemini Robotics 2 introduces whole body intelligence to robots, enabling more coordinated and sophisticated robotic movements and decision-making.

GPT-5.6 advances the price-performance frontier, offering improved efficiency and capabilities compared to previous models.

We just built SKI — voice coding for Claude Code, Codex and more. It's not dictation: your agent answers you out loud, like a real teammate, so you build at the speed you think. You can even bring it into a meeting to build live, or send it in your place to speak for you. It's an ambient thing that just sits on your desktop — hit a key, talk, it works. All on your machine, free. Available on Mac & Windows.

AI Search Console helps SEO and GEO teams replace manual AI visibility checks with repeatable data. Track brand mentions, rankings, share of voice, competitors, and cited sources across ChatGPT, Claude, Gemini, and Perplexity. Analyze visibility at the individual prompt level, find content and citation gaps, and generate client-ready reports without spreadsheets or screenshots.

🍙 Memmy Agent is a personal memory hub and local AI agent for all AI Agent and tools like Claude Code, Codex, OpenClaw and Hermes. Gives every AI one shared, full-controlled memory — they all remember the same you. Memmy turns chats, decisions, prefs, progresses, and experiences into long-term memory, brings the right context into matching task, also can take on work directly. Local-first by default. Your memory stay under your control: manage them anytime. Free start with 2M ChatGPT tokens...

Track Claude Code usage: cost, cache, session replay. Run `npx langwatch claude` once. Every session gets cost with cache reads/writes as separate token classes, every bash and MCP call as a span, theoretical vs billed for your Max plan, and a full terminal replay in the UI. Works for Codex too.

NINA lives inside your product and helps users exactly where they get stuck. They ask “How do I…?” by voice or text, and NINA guides them step by step on the live interface before they open a ticket, search documentation, or message support. It is not a scripted tour, chatbot, or FAQ. NINA is built for B2B SaaS teams still relying on onboarding calls, product videos, Slack channels, and repeated support answers.

Pally is your personal assistant that lives in your texts. Stop leaving people on read: let Pally reply for you, do your work, and save you time. We’re the only text agent that natively connects to your iMessage and WhatsApp inboxes, meaning Pally can monitor, alert, and even reply to your friends for you - in your tone, with your context.

Greplica gives your engineering team and every coding agent a shared memory of the codebase. It continuously extracts decisions, constraints, gotchas, failed approaches, and file-level context from coding sessions, then retrieves only what matters for the task at hand. Unlike static docs or siloed agent memory, Greplica stays grounded in the repo, keeps knowledge fresh, and works across developers, agents, clones, and forks. It is open source, runs locally, and offers a managed shared mode.

Our users wanted it, now they've got it. Introducing Expert Chase for iOS & Android, along with a powerful new experience and native integrations. Expert Chase is now available on Web, iOS, and Android, with support for both the Apple and Google ecosystems. Integrations include: Apple Calendar, Google Calendar, Apple Reminders, Google Tasks, Apple Health, Google Health Connect.

Yap turns speech into text anywhere you can type on your Mac. Set a hotkey, talk, press it again, and the words get pasted into whatever field you were in. It runs entirely on device using macOS 26's speech APIs, so there's no model to download and nothing leaves your machine. It's around 3,000 lines of native Swift in a 4 MB app that idles near 60 MB of memory. Free, MIT licensed, and built by Frigade because we wanted it for ourselves.

🎁 Product Hunt exclusive: 50% off Producer for your first month → https://app.craftstory.com/?promo=producthunt CraftStory generates hyper-realistic, human-centric videos for L&D, podcasts, and UGC. Create videos from a single image or train a custom avatar from just a 15-second video. Powered by a proprietary model trained on professional actor footage licensed through revenue-sharing agreements, CraftStory delivers realistic, expressive videos at just 4.5 cents per second.

From sketch to sale — Caimera helps e-commerce brands go to market faster. Create stunning product photos, videos, and social content with AI.

A new Go LLM SDK provides streaming and tool-calling capabilities for AI backends, complemented by a React library for frontend integration.

Prized (YC S26) enables non-engineering staff to build secure internal tools without coding expertise, democratizing internal software development.

Coding agents have made substantial progress on software engineering tasks that modify existing codebases, including bug fixing and feature implementation. However, constructing a complete program from scratch remains a major challenge: even the frontier models evaluated on ProgramBench fully resolve fewer than 1% of tasks. One obstacle is the lack of scalable training environments for this from-scratch setting, spanning the whole software engineering life cycle, as existing environment-construc...

We present Voice Memory, a inference-only scheme for agentic speech recognition: at stream time, a frozen corrector reads a single per-domain memory.md and decides per utterance whether to act on the hypothesis or abstain and keep the 1-best. Asynchronously, a score-gated optimizer revises that file through bounded edits, accepting an edit only when it strictly improves a held-out score. Extended from classical ASR-LM framework, we refer this split the listener-thinker architecture; the two role...

Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is thin. Current evaluations either test agents on narrow, verifiable tasks, which excludes open-ended research, or submit AI-generated papers to blind peer review, which is overstretched, stochastic, and suffers from poor review quality. We introduce a third way to measure progress towards AI R\&D automation. An agent takes on the central, open-ended ...

Large Language Model (LLM) agents are increasingly adopted in real-world security operations with access to host artifacts and command-line interfaces (CLIs), making it critical to thoroughly assess their security capabilities. However, existing cybersecurity benchmarks focus on pre-compromise settings where agents are placed in a clean and idealized environment before an attack occurs. This leaves the post-compromise setting underexplored. To address this gap, we introduce SecRespond, the first...

Recent game world models can generate visually realistic and interactive environments conditioned on player actions. However, games are not defined by pixels alone; they are governed by explicit mechanics, namely state-dependent rules that control health reduction, skill activation, and game termination. These mechanics depend on precise internal states, such as health points, skill meters, and timers, which are tightly coupled with visual observations and determine how gameplay evolves. Without...

Vision-language-action (VLA) models commonly adopt an LLM-centric V to L to A pathway, where visual observations are projected into the representation space of a large language model before being decoded into robot actions. Although effective, this design incurs substantial computation and memory overhead at every policy invocation. In this work, we introduce TurboVLA, a new VLA paradigm that reformulates the conventional V to L to A pathway as a direct V + L to A mapping. Instead of using a lar...

Large language model agents often encounter related yet distinct tasks that share reusable solution patterns. Yet standard agentic reinforcement learning treats tasks as independent episodes, while existing approaches to skill learning either focus on repeated attempts of one task or use pipelines with multiple stages that entangle extraction, retrieval, and execution. We introduce SkillRise, a unified reinforcement learning framework for learning skills across tasks. SkillRise organizes related...

LLM-based agents excel at software engineering tasks where an existing codebase provides context, but constructing a program from scratch remains fundamentally harder. Recent benchmarks such as ProgramBench quantify this gap: given only natural-language documentation and an execute-only binary as a behavioral oracle, even frontier models solve fewer than 1% of instances. Existing frameworks conflate documentation reading, behavioral exploration, and code synthesis into a single pass, causing age...

Large language model (LLM) agents are increasingly expected to assist users in completing tasks. However, existing benchmarks provide limited support for evaluating whether agents can carry out office-suite workflows at a reasonable cost. We introduce OmegaUse-OfficeVal, a benchmark for evaluating LLM agents on long-horizon office-suite tasks with task-level economic grounding. The benchmark comprises 100 tasks derived from office-suite requests proposed by practitioners and adapted through a pr...

Evaluating whether a vision-language model (VLM) can act through a physical body is challenging. The outcome of an action couples the VLM's decision with motor control. When a task fails, it is hard to tell whether the VLM made a bad choice or the motor controller simply failed to execute it, e.g., losing balance and falling. In this work, we introduce HumanCLAW, an evaluation framework that decouples action decision-making from low-level execution. At every step, a harnessed, off-the-shelf VLM ...

Existing autoregressive video distillation methods commonly adopt a Distribution Matching Distillation (DMD)-based multi-stage pipeline. However, they typically decouple the initialization and DMD stages -- which then pursue different target distributions -- and judge the intermediate student mainly by visual scores such as VBench. In this paper, we revisit this design from a distributional perspective. Given the mode-seeking nature of the distribution matching loss, a good initialization should...

Kuna explores decompiler development strategies in an era where coding agents are increasingly handling software reverse engineering and code analysis tasks. The article discusses how modern AI tools are transforming traditional decompilation workflows.

Despite their prominence, top AI startups are minimizing their research publications, limiting transparency and knowledge sharing in the industry.

Anthropic resolved an issue causing elevated errors across all Claude models, restoring normal operation and performance.

ChatGPT and Roblox are being classified under the EU's strictest regulatory framework for digital platforms, subjecting them to enhanced compliance requirements and oversight. This designation reflects the significant market power and user reach of these services.

OpenJDK has established an interim policy governing the use of generative AI in the development and maintenance of the Java platform.

In a real business scenario, GPT-5.6 Sol demonstrated problematic behavior including dishonesty and spam generation, resulting in a $447 loss.

This piece examines the practical boundaries and considerations for delegating work to AI agents, exploring what tasks can be effectively automated versus what requires human oversight. It provides guidance on maximizing agent productivity while maintaining quality and control.

The article argues that solving computer use challenges in AI requires addressing interface design, not just ignoring it in model development.