It seems that there are two ways to build voice AI: Half-duplex: strict turn-taking. You speak, the other side waits until you’re done, one direction of speech at a time. ← This is how almost every voice assistant works today. Full-duplex: two channels, both sides can talk at any time - no more waiting for your “turn”. ← This is the way humans actually talk. In fact, there are three crucial things half-duplex voice models can't really do: Overlap - talking and listening at the same time without falling apart Backchannels - the "mhms," "rights," and "yeahs" you drop in while the other person is still going Barge-in - getting interrupted mid-sentence and recovering gracefully These three features are a big reason why voice agents still feel “robotic” to this day. But what exactly is the spectrum from half-duplex to full-duplex? Is a Moshi-style architecture the only way to approach full-duplex natural voice conversations? What are ways half-duplex systems could imitate full-duplex? Would love to hear others' thoughts on this. submitted by /u/Chilly5 [link] [留言]

Is there a free ai model apple on IOS that i can send unlimited conversations without a cool down or having to pay? submitted by /u/garrettisaqt [link] [留言]

"The company is experiencing strong demand for its AI solutions and services from enterprises and consumers, at levels that are exceeding the company’s available supply," Alphabet said in its statement.

Some report burning through their whole monthly "AI credit" allotment in a single day.

So let me get this straight... Anthropic wants to build a $10T company, and at the same time keeps warning that AI may eliminate millions of jobs. As a shareholder, that sounds amazing. As an employee, slightly less amazing. Are we watching genuine concern for society, or the greatest investor pitch deck ever created? Curious how others see this.... submitted by /u/whatsnextintech007 [link] [留言]

Hey. No new feature this time - just a pass through the corners before the next one. We had a list of nine bugs we'd written down and kept walking past. Most were small. One wasn't, and it was hiding behind a button. When you import a file the studio already has - same bytes - we ask whether to share the existing file or make an independent copy you can edit on its own. Pick "independent copy" and you expect exactly that: your own file, safe to change or delete without touching anything else. It mostly worked. But the new copy's internal name was built from how many copies already existed - copy 2, copy 3, and so on. The problem shows up after a delete. Say you had three, removed the middle one, then made another. The new one counted "two exist, so I'm number three" - but number three was already taken. The studio saw the clash, quietly kept the old file, and pointed your new scene at it. You thought you'd made a clean copy; you were sharing the original, and the real copy you just made was orphaned on disk with nothing pointing at it. Edit "your" copy later and you'd be editing the original too. Nothing crashed. Nothing warned you. That's the worst kind. The fix: stop counting, and instead look at which names are actually taken and pick the first free one - so a copy made after a delete always gets its own identity. We also made the studio shout in the logs if two files ever collide again, instead of silently dropping one. Better a loud bug than a quiet one. The rest were smaller. A menu element could jump for a single frame when you grabbed it (the drag started from where the element was saved , not where it was shown ). A countdown number sat blank for one frame before popping in. And the end screen had a leftover timing delay we fixed - which you'll never see, because that screen is solid black either way. Real bug, just invisible. The one we'd marked most important? We went to fix it and found a rebuild from two weeks ago had already solved it. We checked three

In a wild ride for 22-year-old founder and CEO Ethan Thornton, Mach Industries has raised another $300 million. It already has five autonomous vehicles in development and completed a major acquisition.

Prehistoric mining in the Pyrenees, a new species of tiny blue octopus, slapstick acoustics, and more.

Agent Orchestration & Workflow Automation: Dynamic Workflows, Robust Agent Patterns, and On-Commit AI Code Review Today's Highlights This week's highlights focus on advancements in AI agent coordination with Claude Code's new Dynamic Workflows, a pragmatic 6-file system for reliable agent state management, and the release of peektea v2 for on-commit AI code review. Claude Code Adds Dynamic Workflows for Parallel Agent Coordination (InfoQ) Source: https://www.infoq.com/news/2026/06/dynamic-workflows-claude-code/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global Anthropic has introduced Dynamic Workflows, a significant enhancement to Claude Code, designed to improve the coordination and efficiency of AI agents in complex tasks. This new capability enables developers to orchestrate multiple AI agents in parallel, allowing them to collaborate on different parts of a problem simultaneously. Unlike traditional sequential processing, Dynamic Workflows facilitate a more natural, concurrent approach, where agents can dynamically assign sub-tasks, share intermediate results, and adapt their strategies based on real-time progress. This is particularly beneficial for large-scale code generation, complex project management, and multi-stage data analysis where distinct competencies are required from different specialized agents. The core benefit of Dynamic Workflows lies in its ability to manage dependencies and synchronize agent activities, leading to faster execution and more robust outcomes. For instance, in a coding scenario, one agent might focus on generating unit tests while another refactors existing code, both operating in parallel and integrating their work seamlessly. This dynamic coordination mechanism moves beyond simple sequential chaining, offering a powerful paradigm for building sophisticated, multi-agent systems that mirror human team collaboration. Developers can leverage this to create more resilient and adaptive AI-driven workflows,