Search: “vibevoice”

Google Releases Gemini 3.8 Live and 3.8 Live Extended Thinking for Production Grade Voice Agents

Google launches Gemini 3.8 Live and Extended Thinking speech-to-speech models for production voice agents, topping speech-to-speech benchmarks.

Google released Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, native speech-to-speech models for real-time voice agents, available hosted via the Gemini Live API and AI Studio. Extended Thinking ranks #1 on Artificial Analysis' Speech-to-Speech Quality Index with 82.6, scores 68.6% on τ-Voice, 35.1% on Sierra's τ-Voice-banking, and 97.7% on Big Bench Audio. The models support asynchronous function calling, near-real-time visual context, alphanumeric precision, and 97 languages, priced at $0.005/min audio input and $0.018/min audio output. All generated audio carries Google DeepMind's imperceptible SynthID watermark.

MarkTechPost·Sep 15, 20:53 UTC · 19h agoModel release 3 sources

microsoft/VibeVoice-ASR-Streaming-7B — new model trending #27 on Hugging Face

Microsoft released VibeVoice-ASR-Streaming-7B, an open streaming ASR model with speaker attribution, custom hotwords, and support for 10 languages under MIT license.

Microsoft Research released VibeVoice-ASR-Streaming-7B on Hugging Face, a unified streaming speech recognition model that continuously transcribes who said what as speech arrives. The 7B model supports customized hotwords for domain-specific terms and 10 languages including Chinese, English, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish. Code is available at github.com/microsoft/VibeVoice with a live demo, and a technical report is on arXiv (2609.02812). The model is licensed under MIT.

Hugging Face trending models·Sep 2, 15:46 UTC · 14d agoModel release1

Comfy-Org/YuE2 — new model trending #30 on Hugging Face

m-a-p's YuE2-3B music generation model and SheetSage2 audio encoder are repackaged in bf16 for ComfyUI and trending #30 on Hugging Face.

Comfy-Org published repackaged bf16 safetensors files for m-a-p's YuE2-3B model and its SheetSage2 audio encoder, organized into ComfyUI checkpoints and audio encoder folders. The repository links to the original m-a-p/YuE2-3B and m-a-p/SheetSage2 model pages and is currently trending #30 on Hugging Face.

Hugging Face trending models·updated Sep 12, 05:56 UTC · 4d ago·first Sep 11, 03:35 UTC · 5d agoModel release 7 sources

My business partner sent a 5K vibe-coded PR that he didn't even test

A developer's business partner shipped a 5,236-line untested vibe-coded payments backend PR whose endpoints failed basic testing.

The author describes reviewing a pull request with 5,236 additions for a payments backend that a business partner generated largely with AI in a single day without testing. The PR's AI-written documentation included redundant boilerplate (e.g., 'returns 400 on error') but omitted operational details like where to obtain API keys, and the endpoints failed when tested. The post is a critical opinion piece on vibe coding and perceived skill atrophy among developers who rely on AI for everything.

Hacker News · security·Sep 8, 01:48 UTC · 8d agoAI industryHN 46↑ · 75 comments1

When Vibe Hacking Turns AI into the Junior Hacker Every Adversary Always Wanted

The Hacker News·Aug 4, 11:30 UTC · Aug 4, 2026Vulnerability

ChatGPT can now connect to your personal apps to mimic writing style

OpenAI is testing ChatGPT Writing Style, which mimics a user's voice using writing samples from connected Gmail, Slack, and Drive accounts.

OpenAI confirmed it is testing a Writing Style feature for ChatGPT that learns a user's voice from writing samples in connected apps. The onboarding flow references Messaging (Slack), Documents (Google Drive and Notion), and Email (Gmail) as example sources. It resembles Anthropic's Styles personalization feature but draws on existing writing inside connected services rather than uploaded samples. The feature is available to a small group of users with no announced general rollout date.

BleepingComputer·Sep 7, 10:36 UTC · 9d agoAI industry

BreezeBlue/Breeze-TTS-2 — new model trending #19 on Hugging Face

BreezeBlue open-weights Breeze TTS 2, a bilingual text-to-speech model it ranks #1 among open-weight models on the Artificial Analysis TTS leaderboard.

BreezeBlue released open weights and Apache 2.0-licensed PyTorch inference code for Breeze TTS 2 on 2026-08-25. The text-to-speech model supports English and Chinese, voice cloning, reference-free voice design, voice direction, and inline vocal events like (laugh) and (sigh). Reported performance includes #1 open-weight ranking on the Artificial Analysis Elo leaderboard, under 40 ms time-to-first-audio, a 0.32 real-time factor on an NVIDIA H100, and about 7.7 GiB GPU memory for eager inference.

Hugging Face trending models·Aug 25, 16:39 UTC · 21d agoModel release

Intelligent transcription with Gemini 3.5 Transcribe

Google DeepMind launched Gemini 3.5 Transcribe, a speech-to-text model offering more intelligent transcription as part of the Gemini family.

Google DeepMind announced Gemini 3.5 Transcribe, a new speech-to-text model described as delivering more intelligent transcription. The blog post provides limited technical detail in the available text, with no benchmarks or model sizes given. The release adds a dedicated audio transcription model to the Gemini family.

Google DeepMind·Aug 26, 17:01 UTC · 20d agoModel release

Gemini Live audio

Google released Gemini 3.8 Live speech-to-speech models; Simon Willison built a library-free browser web UI for real-time voice conversations with them.

Google released Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, two new speech-to-speech models comparable in shape to OpenAI's GPT-Live family. Simon Willison had GPT-6 Astra Extra High build him a web UI for testing the models, supporting model and voice preset selection, optional system prompts, and interrupting the model mid-speech. The implementation uses no libraries and talks directly to Google's wss://generativelanguage.googleapis.com BidiGenerateContent WebSocket endpoint.

Simon Willison·Sep 15, 22:47 UTC · 17h agoModel release

Legit Security VibeGuard 2.0 brings endpoint security and real-time guardrails to AI coding agents

Help Net Security·Aug 4, 00:00 UTC · Aug 4, 2026AI safety & security

Enabling Creative Exploration for Vibe Design Agents

Separating design-direction exploration from code generation via structured specifications broadens UI alternatives without destabilizing output.

The paper proposes an inference architecture for vibe design agents that makes design direction an explicit intermediate decision: a Verbalized Sampling-inspired pre-pass proposes structured design specifications with typicality scores, an external selector samples one, and a downstream generator realizes it under fixed settings. Across 168 prompts with 1,255 paired comparisons per temperature, theme sampling broadens selection coverage and screenshot variation, with LLM-judge preferences varying across interventions and prompt complexity. An online experiment with over 300,000 tasks found the code-export increase statistically uncertain, though negative feedback events decreased alongside modest operational costs.

Hugging Face daily papers·Sep 13, 20:00 UTC · 2d agoAI research

StepAudio 3 Gen Technical Report

StepAudio 3 Gen unifies TTS, voice design, music, and sound effects via discrete autoregressive modeling over RVQ tokens.

StepAudio 3 Gen is a general-purpose audio generation model covering zero-shot TTS, voice design, vocal generation, sound effects, music, vibe speech, and mixed audio in one framework. It uses discrete autoregressive modeling over residual vector quantization (RVQ) tokens rather than the diffusion Transformer paradigm, with a StepAudio Tokenizer representing audio at 12.5 Hz in a shared 16x2048 residual code space. Key design principles include interference-aware progressive pretraining, an RVQ Adaptor for multi-codebook acoustic representations, and shared discrete autoregressive modeling. The model reports state-of-the-art performance on TTS and voice design while retaining strong generation across speech, vocals, sound effects, and music.

Hugging Face daily papers·Sep 10, 20:00 UTC · 5d agoAI research

Google launches Gemini 3.8 Live to take on OpenAI's GPT-Live-1 at a fraction of the cost

Google DeepMind launches Gemini 3.8 Live speech-to-speech models, topping Artificial Analysis leaderboard at 82.6% with much cheaper pricing than OpenAI.

Google DeepMind released Gemini 3.8 Live and 3.8 Live Extended Thinking, audio models for voice agents available through the Gemini API and Google AI Studio, supporting over 97 languages plus background API calls and visual input. The Extended Thinking variant ranks first on the Artificial Analysis Speech-to-Speech Leaderboard with 82.6%, ahead of OpenAI's GPT-Live-1 models. Google charges $0.005 per minute for audio input and $0.018 for output, versus OpenAI's $0.05 per minute, though OpenAI retains full-duplex conversation quality advantages.

The Decoder·Sep 15, 18:23 UTC · 21h agoModel release1

The Machines Are Calling: Measuring Automated and Synthetic Voices in Unwanted Inbound Calls

Voice honeypot measurement finds at least 26.9% of unwanted US inbound calls open with machine voices, 13.1% with fresh synthetic speech.

An interactive voice honeypot using language-model personas on real US numbers recorded 10,987 calls over 66 days, following the FCC's February 2024 ruling that AI-generated voices fall under the TCPA. Of 7,233 greeted calls, 13.8% opened with recordings replayed from other calls and 13.1% with fresh audio labeled synthetic, with replays making up 45% of the detector's flagged rate. Synthetic openings concentrated in lead-generation spam (33.8%) rather than fraud (21.1%), and only 0.44% of calls disclosed automation. Prevalence tracked how long a bait number had circulated, and campaigns outlasted their numbers, with one synthetic voice serving nine campaigns.

arXiv cs.CR·Sep 10, 06:28 UTC · 6d agoResearch

Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

Paper proposes Generative Marketing Mix Modeling to causally estimate Generative Engine Optimization and Marketing effects on business outcomes.

The authors develop GMMM, a causal inference framework for measuring how often users see and notice a firm's name in generated answers, which standard marketing data ignore. For GEO it combines repeated generated answers with question counts, shares of generative-system usage and notice probabilities; for GEM it uses sponsored placement records with notice probabilities. The framework compares expected business responses under alternative treatment sequences, establishes identification conditions, and is evaluated on simulated product-recommendation answers in English and Japanese.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:57 UTC · 5d agoAI research

Building and Evaluating Fixed-Voice Thai TTS from Synthetic Speech

Researchers distill a compact 82M-parameter Thai TTS from synthetic OmniVoice data, enabling on-device fixed-voice synthesis without reference audio.

The paper uses a large voice-cloning model (OmniVoice) as a synthetic data source to train Wayu-Paxa-TTS-Edge, an 82M-parameter fixed-voice Thai TTS student. The model achieves 68.2% Challenge-Set Keyword Accuracy (85.5% of Gemini 3.1), 91.4% pause precision, and CERs of 3.7% on Thai and 1.1% on English. It outperforms its teacher on pause placement and is open-sourced with its evaluation framework.

Hugging Face daily papers·Sep 2, 20:00 UTC · 13d agoAI research

Product showcase: AI Paper Trail shows the privacy cost of talking to AI

Proton launched AI Paper Trail, a free tool that analyzes ChatGPT or Claude exports and reports what personal data can be inferred from AI conversations.

Proton released AI Paper Trail, a free web tool that analyzes the 200 most recent prompts from exported ChatGPT or Claude conversation histories and generates a privacy report with an AI Exposure Score, inferred personal data categories, and an estimated advertising value. In a hands-on test it identified 47 data points, returned a 58/100 exposure score, estimated $185 in advertising value, and flagged five red flags spanning location, interests, finances, and relationships. Proton states that uploaded data is deleted after analysis and is not stored on its Lumo servers.

Help Net Security·Aug 24, 00:00 UTC · 23d agoAI industry

StepAudio 3 Realtime Technical Report

StepAudio 3 Realtime debuts an audio-language model with Think-While-Speaking reasoning, delivering full-duplex voice dialogue with top benchmark results.

StepAudio 3 Realtime is an audio-language foundation model built around a continuous listen-converse-think-act loop for real-time spoken interaction. Think-While-Speaking runs private reasoning in parallel with speech, reaching a 73.0 macro average on StepAudioChat in reasoning mode. The model reports 90.6 on MMSU, 98.9 overall on the Artificial Analysis Full-Duplex Bench, and 56.0% macro task success on tau-Voice. An integrated Voice Agent handles asynchronous tool execution without disrupting dialogue flow.

Hugging Face daily papers·Sep 11, 20:00 UTC · 4d agoAI research

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face Blog·Aug 18, 00:00 UTC · 29d agoAI tools & infra1

Slack can now vibe-code interactive charts and reports inside chats

Slack launched Slackforce Surfaces, letting Slackbot build interactive dashboards, reports, and microsites directly inside chat channels.

Slackforce Surfaces uses AI to gather context from conversations and connected apps such as Google Drive and Salesforce to generate shareable interactive reports, polls, dashboards, and presentations. Surfaces can be pinned to channels where colleagues can view, interact, and comment. The feature is available to all customers, including free users, with Slackbot enabled, and live data support starts in October.

The Verge · AI·Sep 10, 21:25 UTC · 5d agoAI industry1

Introducing ChatGPT Images 2.5

OpenAI released ChatGPT Images 2.5, improving generation of personalized, polished images from ideas, sketches, and reference photos.

OpenAI announced ChatGPT Images 2.5, a new version of its image generation capability in ChatGPT. The update is designed to turn ideas, sketches, and reference photos into more personalized and polished images that better reflect user intent. No benchmark numbers, model sizes, or technical architecture details were disclosed in the announcement.

OpenAI News·Sep 8, 11:30 UTC · 8d agoModel release

Gradium Launches Voice Design: Write a Prompt, Get a Brand New Synthetic Voice in Seconds

Gradium, a Kyutai spinout, launched Voice Design, generating custom synthetic voices from text descriptions in seconds across five languages.

Gradium, a Paris-based voice AI company spun out of Kyutai, launched Voice Design, which generates new synthetic voices from 1-500 character text descriptions in seconds without needing reference audio or speaker consent. The feature is live in the Gradium API and Studio, free on every plan including the free tier, and kept voices run on the standard streaming TTS endpoint at the same latency as catalog voices. Vendor-run blind pairwise listening tests across 7,627 comparisons report a 72.6% win rate, 13.6 points ahead of ElevenLabs at 59.0%, placing first in all five tested languages, with the largest margins on regional accents such as Quebecois French (97%).

MarkTechPost·Sep 9, 07:29 UTC · 7d agoAI industry

Google's new AI model predicts the future from sales data, weather, and discount schedules

Google Research released TimesFM-3, a 330M-parameter multivariate time series forecasting model that tops Gift-Eval, FEV-Bench, and Time benchmarks and is on Hugging Face.

Google Research released TimesFM-3, a 330-million-parameter Transformer-based time series forecasting model trained on more than one trillion real and synthetic data points. It works zero-shot and adds multivariate support, ingesting related series, historical-only covariates, and known future events such as discount schedules and weather forecasts, while filling all future time steps in a single one-shot pass. Google reports first place among pretrained forecasting models on Gift-Eval, FEV-Bench, and Time, ahead of Amazon's Chronos-2, the Toto-2.0 family, and its own TimesFM-2.5. Weights are available on GitHub and Hugging Face, with BigQuery integration planned in the coming weeks.

The Decoder·Sep 12, 09:26 UTC · 4d agoModel release2

Google’s Gemini Spark can now manage your Google Photos library

Google's Gemini Spark agent can now edit images, curate albums, and create calendar events in Google Photos for eligible US subscribers.

Google announced that its personal agent, Gemini Spark, can now manage Google Photos libraries, including editing images, curating albums, creating shared albums, converting concert flyer photos into calendar appointments, and running workflows. Google Photos lead Shimrit Ben-Yair said the capabilities roll out over the next few weeks to eligible Gemini AI Pro and Ultra subscribers in the US, in English, with no international timeline given. The move illustrates the industry's push to demonstrate consumer AI value amid criticism that labs have poorly communicated AI's benefits.

TechCrunch · AI·Sep 4, 14:47 UTC · 12d agoAI industry

Hugging Face's new ML Intern lets anyone run machine learning experiments through a simple chat

Hugging Face launched ML Intern, a chat-based agent that autonomously selects models, trains, and ships demos within user-approved compute budgets.

Hugging Face's ML Intern lets users describe a project in chat, then finds models, datasets, and tools on the Hub, GitHub, and the web before estimating compute costs and enforcing an approved budget. It autonomously creates datasets, trains models, monitors jobs, uploads results, writes reports, and builds demos, each with its own tracking dashboard. A demo training run took about six hours and cost under $0.50. The launch comes as Hugging Face is being acquired by Nvidia, whose CEO Jensen Huang has pledged to keep the platform open and hardware-neutral.

The Decoder·Sep 9, 10:38 UTC · 7d agoAI industry1

ChatGPT claws back web traffic share to 55.5 percent as Gemini's brief comeback fades

Similarweb data shows ChatGPT regaining chatbot web traffic share to 55.5% while Gemini slipped to 25.6% and Claude grew to 9.3%.

Similarweb figures show ChatGPT's share of AI chatbot website traffic rising from 52.7% three months ago to 55.5%, though it remains far below its 73.3% share a year ago. Google Gemini declined from 27.8% to 25.6% after a brief comeback, while Anthropic's Claude grew from 1.9% to 9.3% year-over-year. DeepSeek (3.4%), Grok (2.4%), Copilot (1.6%), and Perplexity (0.9%) trail the leaders. The data covers website traffic only and excludes mobile and desktop app usage.

The Decoder·Sep 7, 16:54 UTC · 8d agoAI industry

Inside ‘Project Lily’: The Humans Reading Your ChatGPT Chats

404 Media reveals OpenAI's 'Project Lily' has hundreds of contractors reading real ChatGPT user prompts, exposing sensitive personal data despite privacy filters.

404 Media reports that OpenAI employs hundreds of contractors who read real ChatGPT user prompts, including whole conversations, to rate and critique the chatbot's responses across a user base of over 900 million. Prompts are anonymized and run through OpenAI's Privacy Filter model, but the company acknowledged sensitive personal details can still reach reviewers, and 'user memories summaries' may reveal a user's location and personal context. The review work includes training ChatGPT to be less sycophantic and to stop anthropomorphizing itself, following lawsuits linking the sycophantic 4o model to multiple suicides. Anthropic confirmed it also uses human review to improve its models, and OpenAI's 'improve the model for everyone' data-sharing setting is on by default for free, Plus, and Pro users.

404 Media·Sep 14, 14:22 UTC · 2d agoAI safety & security