AI Coding Live News

On November 10 (02:02 on November 11 Singapore time) Fish Audio released Live 3, a full-duplex voice model that keeps listening while it speaks. It can acknowledge with short cues such as "mm-hmm" or "okay" while leaving the floor to the user, tell a backchannel apart from a real interruption, and wait while a caller corrects themselves. Fish Audio says these behaviors were learned from real human conversations rather than hand-written rules and thresholds, and that Live 3 can decide to respond in as little as 186 milliseconds. Live 3 speaks English only for now, is available on the Fish Agent Platform and via API, and can be deployed on-premises by enterprises; voice agents are priced at a limited-time $0.035 per minute (list $0.07, offer ends December 31, 2026). No standardized benchmark has been published.

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Seattle startup Nuance Labs released Nuplex 1.0 (Nuance Full-duplex) on November 9, a full-duplex audiovisual foundation model that listens and speaks at the same time, along with Emma, the first AI persona built on it. Emma nods, smiles and uses gaze to signal turn-taking while the user is still speaking instead of waiting for them to finish. On 1,785 questions drawn from recordings of real conversations, the company says Nuplex reply timing overlaps the original human speaker 89% of the time, versus 35% for the next closest system. Emma can be tried in a browser with no sign-up, and the Nuplex Beta API is open, though deliberately restricted: no cloning of real people, watermarked video, English only, adults only, and no healthcare or under-18 use for now.

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On November 8, Adventists AI released the Sophon-Realtime v1 family of full-duplex voice models on GitHub, Hugging Face, ModelScope and PyPI, with Apache 2.0 code and weights that allow commercial use. All three builds share one 32B brain, adapted from Qwen3-VL-32B-Instruct, that listens continuously, decides turns and writes the reply; they differ only in how the reply becomes sound. The recommended Tag build is the most expressive, Flash reaches first audio in 0.31 s with up to 40 concurrent users per GPU, and E2E is a research preview that needs two 80 GB GPUs. Vendor-reported scores are VoiceBench 82.8 and Big Bench Audio 81.8%, first among open full-duplex models; all benchmarks are self-run by the team.

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On 2026-11-05 Boson AI (the team of Mu Li and Alex Smola) released a research preview of Higgs Realtime Duplex: a 45B MoE front model that slices voice, video, and tool results into 160 ms chunks so it can listen, watch, speak, and render its own face at once, while thinking, calling tools, or delegating hard questions to a larger backend model without pausing. Vendor-reported scores include Big Bench Audio 98.9, tau-Voice 69.8, and Full-Duplex-Bench v1.5 75.5. The API is waitlist-only for now; the earlier Higgs Realtime is available today.

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On 2026-10-23 (16:53 UTC) the official @blocks account unveiled Dessa, and Jack Dorsey called it the most authentic full-duplex speech model ever built. The official page block.xyz/dessa says Dessa is a true speech-to-speech model trained only on recordings of human conversation, with no text and no pretrained models. It is full-duplex, so it listens and talks at the same time, cuts in and backchannels naturally, runs faster than real time, and runs locally on a MacBook Pro M4 Max or better. Block says it was trained on a single NVIDIA GB200 NVL72 and learned language from hundreds of times fewer words than LLMs. There is no public API or weights yet; a small group of AI safety researchers is getting early access.

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On Oct 15 OpenAI rolled out GPT-Live-1.1 (successor to GPT-Live-1) and GPT-Live-1.1 Quip (successor to GPT-Live-1 mini), full-duplex voice models that become the default voice for Plus-and-up users in ChatGPT Voice, Codex and dots. New voices cover French, German, Hindi, Japanese, Korean and Mexican Spanish, accents are more natural and the constant 'checking...' filler is reduced. Rolling out to all users; API coming soon. The system card reports statistically significant regressions in four synthetic safety categories.

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Mainstream LLM agents strictly follow sequential interaction loops: read, think, reply, call tools, and block until completion. Real-world applications—including full-duplex voice assistants, robotic manipulation, and continuous infrastructure monitoring—are inherently asynchronous, receiving incoming observations while the agent is actively deliberating or waiting on tool I/O. Researchers introduce a general asynchronous LLM framework that abstracts model inference into non-blocking coroutines with overlapping memory states. Without requiring task-specific fine-tuning or architectural alterations, foundation models like Qwen 3.x exhibit native asynchronous competency, effortlessly handling live video feeds, real-time gaming, and continuous systems monitoring.

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