AI Coding Live News

On Oct 28 Meta announced that Muse, its personal AI agent, is now available in Singapore on iOS, Android and muse.ai. Beyond Gmail, Google Calendar and Instagram, the first local connector partners are Shopee, Grab, Singapore Airlines, Agoda, ShopBack, Klook, Trip.com and Lazada, spanning shopping, groceries, dining and travel, with some connector features rolling out after launch. Muse runs on Muse Secure VM, a dedicated cloud computer that keeps passwords and payment methods out of the agent's view, and it asks before sensitive actions such as sending an email or making a purchase. It is free for most uses, with paid subscription plans.

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On Oct 27 the official ChatGPT account announced that iCloud Mail and iCloud Calendar plugins are available in ChatGPT on all plans across web, desktop and iOS, rolling out globally. Users can ask ChatGPT to find an email, catch up on their inbox, check what is next or update a calendar event. The two plugins are installed separately, both connect with an Apple app-specific password, and both include read-only contact lookup; standalone Contacts and Reminders plugins are not part of this launch.

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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 2026-10-13 Fish Audio launched Drama 3, a TTS model directed with plain-language bracket tags, open weights on Hugging Face, and API header model: drama-3. The backbone is a ~35B MoE (~3B active per token, initialized from Qwen3.5-35B-A3B's language tower) with a codebook-MTP audio decoder and preference-model RL. Independent Artificial Analysis Pronunciation Robustness: 93.2% vs 88.1% for S2.1 Pro; 83 languages and up to 16 speakers; Community License free for commercial use under US$500k annual revenue. Launch promo through Nov 12: about $10 per million characters on the API.

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Rendering dense, legible, and spatially accurate text within generated images is critical for commercial graphic design, advertising posters, and e-commerce visuals. However, existing benchmarks predominantly test isolated words or simplistic English phrases, failing to capture the complexity of rendering multi-region, bilingual text layouts. LINs-lab introduces UltraText Bench (arXiv:2610.09823, code: github.com/LINs-lab/UltraText_Bench), a comprehensive bilingual benchmark designed to stress-test prompt-only dense visual text rendering. The suite contains 432 human-reviewed prompts distributed equally between English and Chinese across 24 real-world categories and three difficulty tiers (L1 to L3), with each prompt prescribing exact text for 4 to 12 distinct visual regions. Utilizing the Q-Judger multimodal evaluation model, UltraText Bench assesses 24 state-of-the-art model configurations across text fidelity, text clarity, spatial layout, and scene aesthetics. Empirical results expose key architectural trade-offs: Turbo distilled variants gain 3.81 clarity points but sacrifice 14.76 fidelity points, while flagship models like Qwen-Image exhibit steep performance degradation under L3 dense workloads (dropping from 86.50 to 42.86), with code and evaluation suites fully open-sourced.

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On Oct 5 OpenAI described its response to the EU AI Act's machine-readable text requirement: API customers worldwide can now opt in to text watermarking for select models (off by default), and in the coming weeks eligible ChatGPT and Codex text output in the EU will carry an invisible watermark across all plans. The technique, textGrain, embeds a statistical signal in word choices; OpenAI says it matched or beat SynthID for text and plans to open-source it. The detector is limited to approved researchers. At 1% false-positive rate, detection is ~80% on 200-token and ~95% on 400-token passages, falling to 17% after 25% synonym replacement; Astra benchmarks show no meaningful quality change.

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Anthropic shipped Claude Code 2.1.286 on 2026-09-30 (npm @anthropic-ai/[email protected]): permission prompts show stacked counts like "2 of 5"; --resume/--continue no longer drop turns after parallel tool-call crashes; broader secret/Bearer/URL-password redaction; one same-tier prior-model retry when the API refuses the default/alias; Remote Control disconnects when org policy disables it; Agent SDK TS 0.3.286 / Python 0.2.163 parity.

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Unsloth shipped v0.1.900-beta on 2026-09-28 (PyPI unsloth 2026.9.12): Desktop runs Laya Decision models locally via a Jev-compatible /v1/systemone endpoint, adds a Skills CRUD editor and Library viewers for PDF/Office, and improves Apple Silicon with batched serving, structured outputs, and TurboQuant KV. Media pipelines claim ~4.5× LTX-2.3 clips, 1.7–6.3× VAE decode, and up to ~1 minute faster MiniMax-H3 first render with 25–29 GiB lower peak VRAM.

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Pipecat v1.12.0 (2026-09-26) adds TTSService.pronunciation_transform_ipa() for reusable word→IPA maps across Cartesia/ElevenLabs/Inworld/Deepgram, client-mode MOQTransport reconnect with session-ending markers, Pipecat Classifiers + LLMClassifier, frame-level interruptible, and response_schema on LLM run_inference. PyPI pipecat-ai 1.12.0 is live.

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