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Google has launched Google AI Edge Foresight, a free experimental note-taking app for Macs with Apple Silicon.

The app records meetings through system audio and the microphone, then creates full transcripts on the device itself. Users can type short bullet points during a call, and the software expands them into detailed notes using the live transcript.

All processing happens locally with EmbeddingGemma 2 and related Gemma models. No internet connection is required after the initial setup, and nothing is sent to the cloud. Meeting audio, notes, and linked files remain on the user’s computer. The app also lets people connect local folders so its assistant can answer questions based on their own documents.

Google made the app available for free download on its developer site. It remains experimental and currently supports only Apple Silicon Macs. Early feedback highlights the strong local performance and lack of any subscription fees.

Anthropic just kicked off a fresh research project called Anthropic Interviewer. They want to hear straight from people about real experiences with AI, the role it should play in daily life and society, and what users expect from the companies building these systems.

Back in December, more than 81,000 people shared their hopes and worries in what became the largest qualitative study of its kind. This round gives participants the choice to make their answers public so the wider community can see the feedback too, not just the company.

The study is open from September 29 through October 6. Anyone using Claude or Claude Code on the Free, Pro, or Max plans can join. Responses will help shape work at The Anthropic Institute and feed into the decisions the company makes going forward.

Making answers public stays completely optional. Anthropic posted more details on the benefits and possible downsides on their research page if you want the full picture before deciding.

OpenAI just launched dots, a new set of always-on agents built on GPT-6 Astra. These agents sit ready to handle everyday tasks or bigger projects without constant prompting.

A dot can book a table, manage workflows, or act like a high-agency engineer or chief of staff. It runs on its own computer and connects to more than 4,000 apps through ChatGPT using the plugins you already have. It picks up on what you need and starts working in the background around the clock.

You stay in charge the whole time. Set clear limits on what it can do alone, when it should check with you first, and what stays off-limits. Safety comes built in. You pick which apps to link, and the agent works from its own cloud setup so connecting your personal computer stays optional.

Dots are rolling out now in ChatGPT on web, mobile, and desktop for Pro, Business Premium, and Enterprise users in eligible markets. Head to the ChatGPT desktop app or browser, create your first dot, connect the apps you want, and let it introduce itself.

LTX just dropped Native Resolution as the opening move in their VFX Week series. This feature lets the model handle AI edits directly on 4K and 8K footage, including longer shots, by breaking the frame into overlapping tiles so fine detail stays intact. Everything runs on a single GPU.

Alongside it come two new IC-LoRAs. Refine works on footage you have already upscaled. Push an HD shot to 8K and a regular resize often leaves it soft. Refine fills in the missing fine detail while staying true to the original look. Restore targets archival material. Take a soft 540p clip up to 4K and it boosts color and sharpness so the result feels closer to modern digital camera output. Refine keeps fidelity. Restore deliberately updates the look.

The Native Resolution ComfyUI workflow and docs sit on the LTX VFX page. Refine and Restore weights are available on Hugging Face.

Meta today introduced Muse for Small Business, an expansion of its personal AI agent aimed at helping owners manage daily work more efficiently.

Muse already acts as a personal AI helper. The new version brings a range of added skills and connectors that let it support core business tasks. These updates allow Muse to work with the tools and platforms small business owners already rely on.

Meta described Muse as one of the most significant products it has built for the era of personal superintelligence. By adding these business focused features, the company wants to give entrepreneurs a practical AI partner that steps in on real work rather than simply answering questions.

The launch marks another step by Meta to bring advanced AI into the tools people use every day for running their companies.

Tencent Hunyuan released the preview version of Hy Image3.5 on Tuesday. The new model delivers professional-grade results and scores a 30 percent higher win rate in human evaluations compared with Hy Image3.0.

Users can generate images from text prompts or edit existing ones. Output reaches up to 2K resolution with improved consistency between generations. The model runs through the Tencent Cloud API at $0.024 per image. Reference images used for edits carry no extra charge.

OnSolo and Miora platforms offer two weeks of free access. The team invites feedback on any remaining weak spots.

Amazon has blocked Meta’s new AI tool Muse from accessing its online store. The move came after Meta refused a request to take the bot offline for Amazon shoppers.

Muse rolled out earlier this month. It aims to handle everyday tasks like buying products and scheduling appointments for users. Amazon does not allow outside automated tools to shop on its platform. The block started late Sunday. People trying to use Muse now get repeated pop-ups warning that the tool breaks Amazon’s terms of service.

An Amazon spokesperson said third-party apps that buy on behalf of customers need to work openly and follow the rules set by the store they visit. The company has asked Meta to drop Amazon from the Muse experience. Meta has not yet commented.

This fits a wider pattern. Amazon builds its own shopping helpers but stops rival bots from browsing and buying from its catalog. Last year the company sued Perplexity AI over similar automated agents. Amazon CEO Andy Jassy has said these tools still struggle with accurate prices and product details.

For now most people use AI bots mainly for research rather than actual purchases. If that changes Amazon risks losing sales and ad money when the bots steer users elsewhere.

Xiaomi just launched MiMo-V2.6 with two new models Pro and Flash. Both handle text images video and more in one system trained with scaled reinforcement learning.

Pro matches Claude Opus 5 and GPT-5.6 Sol on most agent tests and leads open source models with a 46 score on the Artificial Analysis Intelligence Index. It shows clear gains in coding computer use 3D reasoning and creative work.

Pricing stays the same as V2.5. Pro delivers strong results at a fraction of the cost of top international models often 20 to 60 times cheaper for similar performance.

The models support turning text or video into playable 3D scenes controlling robot arms in simulation building interfaces slides and even composing music. Xiaomi also released the full model weights technical report RL environments and training code so anyone can test and build on them.

A new open-weight model called Hemmingway-1 has landed on Hugging Face, and early attention is growing fast. Built on the Qwen3.8-27B base, this 27-billion-parameter model focuses on one clear goal: producing text that reads like it came from a real person.

The team behind it trained Hemmingway-1 specifically for the kind of writing people do every day. Think short messages, emails, awkward notes to a colleague, or the reply you keep putting off. In their tests the model often skips the usual AI preamble and just hands over the finished text.

On their own blind evaluations it ranked higher than several much larger systems for everyday correspondence. It also placed third on the public EQ-Bench 4 emotional-intelligence leaderboard, sitting ahead of several well-known frontier models. Story writing is solid too, though the creators note it is weaker on longer hostile or complex narrative turns.

The model carries an Apache-2.0 license, so anyone can download, run, and use it commercially. Context length reaches 262k tokens. You can serve it with vLLM or load it through the Transformers library. A free web and desktop app is also available if you prefer not to host it yourself.

English is the primary language. The developers openly state that math, code, and factual accuracy stay at base-model level, so it is best treated as a specialist for natural writing rather than a general-purpose assistant.

BytePlus has introduced Dramagic, an enterprise-grade all-in-one platform designed for short dramas and cinematic video production.

The tool supports a full workflow that starts with script analysis, moves through asset setup and storyboard creation, and ends with video preview. Teams get built-in consistency checks for characters and scenes, editor-level control, and multi-user collaboration features to keep projects aligned from start to finish.

Dramagic is currently available in beta through a whitelist. Production teams can request access by filling out the form on the BytePlus website or contacting their sales representative.

Google DeepMind just released Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking, calling them their strongest conversational AI models yet.

These models can talk, reason through problems, and run tasks in the background while keeping the conversation smooth. Key upgrades include stronger reasoning, near real-time visual understanding, automatic support for 97 languages, and the ability to call tools without interrupting the chat.

The Extended Thinking version goes further. It delivers higher performance and precision on tough tasks and narrates progress so you stay in the loop. In one demo, it worked as a programming tutor, walking through steps clearly.

You can try both models right now in Gemini Live inside the Gemini app. Developers can also access them through the Gemini API in Google AI Studio.

A new open source model called PhysBrain 1.5 has taken the lead in embodied AI performance. The 8 billion parameter system handles scene understanding, robot action planning, and future frame prediction all through a single token based approach.

It scored 72.5 across a set of 28 benchmarks and currently outperforms every other publicly available model in the category. The team behind it has released two model checkpoints on Hugging Face along with a live demo so researchers and developers can try it immediately.

The paper, model files, and interactive demo are all available now, giving the robotics and AI communities a stronger open baseline for systems that need to see their surroundings and decide what to do next.

Tencent researchers just released SAS, a new sparse attention method that cuts the high cost of running long context language models.

Attention in Transformers normally scales with the square of the sequence length. That makes million token contexts extremely expensive and often wastes compute on irrelevant tokens.

Most previous trainable sparse methods train a selector to copy the dense attention patterns of the original model, then apply hard top k selection. This ranking does not always match what actually helps the final prediction when the attention budget is limited.

SAS fixes that by training the selector end to end with the language modeling loss. Continuous scores from the selector get injected into the attention logits. Gradients flow straight through, so the model learns which context units truly matter for the task.

Key design choices include placing the gate inside the softmax in log form, normalizing the gates, and keeping continuous scores during training. The team also built a memory efficient Triton kernel that works with FlashAttention style computation.

Tests on reasoning, long context understanding, and agentic tasks show SAS beats earlier trainable sparse attention methods. Gains are especially large when the attention budget is tight.

A new fully open foundation model called ZGCM-1 has arrived. Built at 7B parameters, it uses efficient FP8 training and hybrid attention to punch well above its size.

The model stands out on math benchmarks and agentic search tasks, matching or beating much larger systems in those areas. Everything is open, with the paper on arXiv and the full code available on GitHub.

This release gives researchers and builders a practical, lightweight option for math reasoning and tool-using agents without the usual heavy compute demands.

Meta just launched Meta One, a new paid subscription that works across Facebook, Instagram, WhatsApp, and Meta AI. It unlocks extra AI tools, more ways to express yourself, and practical features aimed at creators and businesses.

The free versions of the apps stay the same. Meta One is for people who want higher limits on AI image and video generation, more Restyle options on Instagram Stories, custom fonts, extra chat themes, and professional tools like enhanced profiles, scheduling, analytics, and greater access to Meta Business Agent for customer replies.

Plans start at $2.99 a month for single-app options like WhatsApp Plus. Bundle plans for regular users begin at $7.99, while creator and business tiers start at $14.99 and go higher depending on the features needed. More than 50 features are available at launch, with more planned for tools like Edits and AI glasses later.

Meta says the service is rolling out gradually worldwide. You can check what’s available in your account by starting the subscription flow or visiting the Meta One page.

Google just dropped a handy new feature for Gemini users. Deep Research now works with Gemini Live, so you can dig into any topic using just your voice.

Here’s how it works. Open the Gemini app and ask it to run a Deep Research report on whatever you want to explore. Once you start it, you can close the chat, lock your phone, or switch to something else. Gemini keeps working in the background and pings you when the full report is ready.

After that, you jump back in and talk through the findings, ask more questions, or tweak the details. It’s built for people who want solid research without staring at the screen the whole time.

ElevenLabs has launched Music v2.5, its latest update to the AI music generation tools. The new version delivers richer melodies, instruments that feel closer to live recordings, and greater depth in arrangements. All training data is licensed and the output is cleared for commercial use.

Users can turn a simple idea, sound, or loop into a complete track. Features include long-form compositions, mid-song genre shifts, rap, lyrics, and vocals that match the user’s language. The tools work inside ElevenMusic for everyday creation and ElevenCreative for scoring ads, branded videos, and other content. A Music API also supports reference-based generation, inpainting, and long-form composition through code.

Every track belongs to the creator from the moment it is made. The Free plan allows five downloads per day with commercial use permitted as long as ElevenMusic is credited. Pro users receive 400 lossless downloads each month. Previous tracks keep their rights even if a plan is cancelled or changed.

Google has released the Gemini app for Windows users across the globe. The app works on both Windows 10 and Windows 11 systems.

Users can open it instantly with the Alt + Space keyboard shortcut. This lets people polish drafts, summarize long documents, brainstorm ideas, and create custom images or videos while staying inside their regular apps.

The move brings Gemini’s tools directly into everyday Windows workflows without needing to switch programs. Full details appear on Google’s official blog.

Cognition has launched Fusion in the Devin CLI. The update pairs a frontier model for planning with a lower cost model for execution. Early tests show 39 percent cheaper runs across coding benchmarks while holding onto top performance.

The company worked with Artificial Analysis and Vals AI to measure the gains. Results stayed strong on multiple agent benchmarks. Fusion differs from simple model routing. The lead model stays in control, reviews the cheaper model’s output, flags issues, and takes over when needed.

Developers can start using Fusion today through the Devin CLI. Full details appear on the Cognition blog.

Cognition just rolled out Devin Voice, a new way to work with their AI software engineer. You can now talk to Devin instead of typing everything out. Say what you need and it starts building.

The feature runs on GPT-Live together with Cognition’s new SWE-2 model. SWE-2 matches the performance of recent top models on key coding benchmarks while costing up to 70% less. The team scaled reinforcement learning across trillions of parameters to hit that balance of capability and price.

Devin Voice is available right now inside the Devin app. Docs are live too if you want the full walkthrough on how to use it.

This update makes Devin feel more natural for quick tasks, bug fixes, or kicking off larger projects without switching to a keyboard.