567 summarised stories about AI Automation, each linking back to the original source. Browse all topics →
Product Hunt 2 months ago 11 ● 9 sources
AgentOne Desktop is a free, extensible desktop AI agent designed to automate routine tasks on computers. The tool is open-source and available for download with no licensing fees. Users can extend its functionality through plugins to handle specific workflows and reduce manual work.
Trending Topics 2 months ago 10 ● 2 sources
Hadrian, a US defense and aerospace manufacturing company, raised $1.37 billion in Series D funding at an $8 billion valuation. The company operates nearly 3 million square feet of production space across four sites and produces precision parts for clients including Lockheed Martin, RTX, and the U.S. Navy, combining human workers with AI, automation, and proprietary software. The funding reflects growing investor interest in American manufacturing capacity as geopolitical tensions drive demand for faster munitions and weapons production.
The GitHub Blog 2 months ago 27
The Aspire team at Microsoft implemented GitHub Agentic Workflows to automatically generate documentation pull requests whenever product features ship, with an AI agent drafting docs and the original engineer reviewing them. For Aspire versions 13.3 and 13.4, the workflow created 82 documentation pull requests that merged within a median of 44.8 hours, with a 100% merge rate and zero failed automations. Documentation now ships concurrently with features instead of weeks later, freeing technical writers to focus on narrative content rather than reverse-engineering diffs.
openworker.com 2 months ago 45
OpenWorker is an open-source desktop application that uses AI models of your choice to automate multi-step work tasks across everyday tools like Slack, email, and calendars. It operates locally-first with privacy controls, integrates with cloud or local models including OpenAI, Anthropic, and open-weight options, and requires user approval before taking consequential actions like sending emails or posting messages. Users pay only to their chosen model provider and maintain full control over tokens and API keys stored locally on their device.
GitHub 2 months ago 28 ● 5 sources
Microsoft's Webwright system converts successful AI agent solutions into reusable, executable code skills that run standalone without models in roughly 40 seconds with zero tokens. Skills are verified twice—first by checking the original solve was correct, then by replaying the distilled code independently—and grow through parameter extraction when multiple verified runs of the same task are aligned. This shifts web automation from repeated model inference to a library of verified programs that can be composed, versioned, and scheduled like traditional software.
discoveryloop.com 2 months ago 11 ● 18 sources
Discovery Loop, founded by Google AI veterans Jeff Dean, Sanjay Ghemawat, Quoc Le, and Oriol Vinyals, launched as an independent company to automate scientific and engineering discovery loops using AI and computational infrastructure. The team will initially focus on automating machine learning research before expanding to other domains, with the goal of enabling rapid parallel execution of thousands of experiments to compress iteration time. The automation of experimental loops could accelerate progress across domains from drug discovery to clean energy by reducing the manual, sequential nature of current scientific work.
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19 October 2026
Amazon’s biggest push against Nvidia this year landed today in the form of TorchNeuron, an AWS development tool designed to let PyTorch-based AI apps run on its Trainium chips with a one-line configuration change instead of a code rewrite. AWS says roughly 85% of AI apps use PyTorch, and that number matters because it turns the usual “porting tax” into a packaging decision: keep writing in PyTorch, switch the backend, move on. The company also plans upstream PyTorch changes to make the framework more hardware-agnostic, aiming to loosen the gravity that keeps developers clustered around specific accelerator ecosystems—an underappreciated lever in enterprise spending, where platform lock-in often lasts longer than model lifecycles.
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