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ModelScope just dropped LongCat-2.0 as open source. This massive Mixture-of-Experts model packs 1.6 trillion total parameters with about 48 billion active per token, built specifically for agentic coding tasks. It comes with native 1 million token context that stays practical thanks to sparse attention.

On benchmarks it scores 59.5 on SWE-bench Pro, beating Gemini 3.1 Pro, GPT-5.5, and Claude Opus 4.6. It also hits 70.8 on Terminal-Bench 2.1 and 77.3 on SWE-bench Multilingual. The model was pretrained from scratch on over 35 trillion tokens and supports both GPU and NPU deployment.

What stands out is its agent-first design with specialized expert groups for tool use, reasoning, and interaction. The efficient ScMoE routing keeps inference lean while handling long project contexts without blowing up compute costs.

Google is giving developers free access to Gemini 3.5 Flash through its API. You only need a Google account to grab an API key from AI Studio. No credit card or paid plan required.

The free tier includes Gemini 3.5 Flash along with the lighter Gemini 3.1 Flash Lite model. It comes with a 1 million token context window and native support for text, image, audio and video inputs. The endpoints are OpenAI compatible so existing tools and clients like Cursor can switch over without much hassle.

You get roughly 1500 requests per day on the free allowance and the limits reset daily per project. This setup suits personal projects, quick prototypes and side builds where you want strong performance without paying anything upfront.

A few practical points. Pro models are no longer available on free access. Free tier prompts can be used to improve Google models so it is better to skip anything private or sensitive. Some people testing it have found the per minute rate limits tighter than expected so it helps to check your actual quotas inside AI Studio before running big workloads.

To get started just visit aistudio.google.com, sign in and create your key.

Anthropic brought Fable 5 back on July 1 after pausing it mid June. The team added stronger cybersecurity safeguards following conversations with the US government. Most regular coding work stays unaffected.

For now the updated checks flag a slightly higher share of normal requests than before. When that happens the system switches over to Opus 4.8 instead. Anthropic says it will refine these filters in the next few weeks to cut down on false positives.

Biology and chemistry safeguards remain broad for the moment. They can still trigger on basic questions in those areas and route to Opus 4.8. Improvements to narrow these down are coming soon.

Paid users can use Fable 5 up to 50 percent of their weekly usage limit through July 7. Once you hit that cap you can continue with usage credits or switch to another model for the rest of the week.

xAI announced the Voice Agent Builder today. It is a no code tool for creating voice agents powered by Grok Voice.

The platform provides built in telephony, knowledge retrieval from uploaded documents, tool integrations for actions like calendar scheduling or API calls, guardrails to control what the agent can do, and observability to review calls.

Pricing runs at 0.05 dollars per minute of audio. New accounts get a free phone number to start with. You can also bring your own numbers via SIP.

It works with a direct speech to speech setup connected to the Grok model. This differs from the common approach of linking separate speech to text, language model, and text to speech services from different providers.

To build an agent you describe the call flow in plain language, upload documents for knowledge, set tools, and define any guardrails. The system supports over 25 languages and handles real world call conditions such as noise and accents. It launched in beta.

Anthropic just announced that the Department of Commerce lifted export controls on Claude Fable 5 and Mythos 5. They will start bringing access back tomorrow and share more details soon.

These models launched in early June as some of the strongest Claude versions yet. Fable 5 is the safer general release with extra guardrails while Mythos 5 has fewer restrictions for trusted partners. Mid month the government stepped in over jailbreak concerns around cybersecurity risks which forced Anthropic to shut them down worldwide.

After a couple weeks offline the controls are now gone. Many developers who got hooked on these models for coding and long tasks are relieved to see them return.

What do you think will this version feel the same or did they add more restrictions during the review?

ModelScope just introduced Agents A1, a 35 billion parameter mixture of experts model made for agent work that stretches over many steps. It targets search, engineering, scientific research, instruction following and tool calling in one package.

The model runs with a 256K context length and agent style reasoning that helps it plan and adjust across longer jobs. It shows leading results on benchmarks for extended search and research tasks along with strong instruction following scores.

It stays competitive with other models in the 35B range. Function calling support lets it connect directly to APIs, code interpreters, search engines and other external tools during its work.

Anthropic launched Claude Sonnet 5 today. They say it is their most agentic Sonnet model yet. It can make plans, call tools such as browsers and terminals, and push through tasks with less help than older versions needed.

It improves reasoning, tool use, coding and knowledge work over Sonnet 4.6. Performance comes close to Opus 4.8 while keeping costs down.

People testing it early found it completes tough jobs that used to stop short in previous Sonnets. It checks its own work without being told to. There are also gains in safety with fewer hallucinations.

Sonnet 5 is default now on free and pro plans. It is there for Max, Team and Enterprise users as well. You can access it in the apps and platform today. Low intro pricing of 2 dollars per million input tokens and 10 dollars per million output tokens lasts through August 31.

OpenAI has released GeneBench-Pro, a new benchmark built to test how well AI agents can handle the messy side of real biology research.

Most existing tests use clean data and clear paths. This one gives agents realistic datasets full of noise, biases and quality problems that show up in actual genomics work. The agents must pick the right analysis tools, spot when data has issues like ancestry mix-ups or sequencing biases, decide what questions the data can actually answer, and know when to change course. These are the judgment calls that shape real studies in areas like cancer genomics, pharmacogenomics and heritability.

The benchmark contains 129 problems across 10 domains. OpenAI created synthetic data with known ground truth so scoring stays fair and does not reward lucky shortcuts or author bias. Problems come with experimental context and a clear target result. Ten of them are already public on Hugging Face.

Early numbers show GPT-5.6 Sol reaching 28.7 percent success on the hardest setting. That is a clear step up from earlier models that scored under 5 percent on the previous version, yet it still leaves most tasks unsolved. Scaling up thinking time helps, but the gap to reliable performance remains wide.

Biology now generates data faster and cheaper than ever. The real slowdown sits in the analysis and decision steps. A benchmark that measures those exact skills could help push automation in places where it matters most for research speed and reproducibility.

Google added two new models to the Gemini API and AI Studio today. Nano Banana 2 Lite focuses on image generation and runs in under four seconds per image while costing just 0.034 dollars for every thousand images. That speed and price point makes it practical for apps or workflows that need lots of quick outputs without running up big bills.

Gemini Omni Flash targets video editing work. It delivers top level results in that area at 0.10 dollars per second, the same rate as Veo 3.1 Fast. Both models are live now so developers and creators can start using them right away through the usual Google tools or Vertex AI.

The updates put more emphasis on real world speed and affordability for generative media tasks rather than chasing the biggest flagship model. People can test them directly in AI Studio to see how they fit into their own projects.

NotebookLM has started rolling out Short Video Overviews. The feature lets you turn sources into short vertical videos that last about 60 seconds and focus on one main idea or concept.

You select your sources inside a notebook, pick what the video should focus on, and generate. It offers a new Short format made for quick mobile viewing in portrait mode, plus explainer and cinematic options if you want a different feel. The videos appear right in the generate menu alongside audio overviews, flashcards and quizzes.

The point is simple. Instead of reading long documents or notes, you get a fast clip that explains the key points in an easy way. It works on both mobile and web for Google AI Ultra and Pro subscribers right now. Free users should get it in the next few days.

OpenClaw has launched native apps for both iPhone and Android. If you already run their gateway on a computer or server this gives you a solid way to take your agents on the go.

The apps are not standalone chatbots. They pair with your self hosted OpenClaw Gateway using a QR code or setup code. Once connected the phone acts as a secure node in the system. You get chat access from anywhere, realtime voice conversations, push notifications for tasks and channels, plus the ability to approve actions right from your pocket.

You can also let the AI use phone features like the camera, location, notifications or screen sharing but only after you grant those permissions the normal way. The main processing still happens on your own gateway which keeps things private and under your control. The store listings confirm the apps collect no data themselves.

This feels useful for people who want to handle replies, tasks and quick interactions without being stuck at a desk. Setup is straightforward if you already have the gateway running. Download links are in their recent announcement post or just search OpenClaw on the App Store and Play Store.

Early users have mixed feedback. Some like the idea but others ran into crashes, keyboard issues or a clunky interface that looks like it could use more polish. It seems like a first release so expect updates to smooth things out.

If you are into self hosted AI agents this could be worth trying. Anyone already using OpenClaw on desktop give it a shot and let me know how it works for you.

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Meta researchers shared an update on their latest brain to text system called Brain2Qwerty v2. It reads raw signals from a regular MEG scanner and converts them into full sentences almost instantly. No implants or surgery involved.

They trained it using data from nine volunteers who each typed for about ten hours while wearing the scanner. That gave them around twenty two thousand sentences total. The setup feeds the noisy brain data straight into deep learning models and then fine tunes language models to understand words and meaning instead of just single letters like before.

On average it gets sixty one percent of the words right. The best participant hit seventy eight percent word accuracy and more than half their sentences came out with one error or less. They also saw that adding more data keeps improving things steadily.

Meta is open sourcing the full training code for this version and the previous one. Their partners released the first dataset too so other teams can build on it. The real goal here is helping people who lost their ability to speak from brain injuries or conditions get a practical way to communicate again.

OpenAI has started rolling out previews for three new models in the GPT 5.6 family. Sol is the flagship built for the hardest jobs in coding, biology, and cybersecurity. It pulls ahead of the last top model on tests that check long running command line work and security research tasks.

Terra gives performance close to the previous flagship but at roughly half the cost. Luna is the fast low cost option made for high volume everyday use.

Right now only a small set of trusted partners and some teams connected to US government work can access them through the API and Codex. OpenAI plans to open them up to more users in the coming weeks. They also added stronger safety checks this time with extra red teaming and automated testing.

Meta is bringing back Facebook Creator Studio after shutting it down in 2023. The old tool for managing pages and content is returning in a new form as an AI companion app built to help creators grow on the platform.

The new version includes an AI assistant that shows performance numbers for posts and gives clear suggestions on what to do next for better reach and engagement. It can also scan comments, pick out the important ones from followers, and draft replies that match the creator's own voice and style.

Right now the app is only in testing with a small group of creators. Anyone interested can join the waitlist on Facebook to get early access once it opens up more widely.

Alibaba Qwen just put out Qwen-AgentWorld. It is a language model trained from day one to simulate how different environments actually work instead of only learning to take actions inside them.

The model handles seven agent setups in one system including search, coding tools, terminals, web, operating systems and Android. This environment modeling was the main training goal rather than something added later.

Their biggest version tops AgentWorldBench scores ahead of Claude Opus 4.8 and GPT-5.4. The open sourced 35B MoE model with 256K context already lifts performance on real agent tasks. Training it to predict what happens next in an environment transfers well even without extra agent specific work.

Anthropic just launched Claude Tag. It puts Claude inside Slack so teams can treat it like another coworker instead of switching to a separate chat.

Tag Claude in any channel you give it access to and describe what needs doing. It splits the job into steps, connects to your tools or codebases if allowed, and drops updates or finished items like merged pull requests and data reports straight back in the thread.

One Claude lives in the channel so anyone on the team can jump in and keep going without re-explaining everything. It keeps learning the context as work continues across days or weeks.

Switch on ambient mode and it starts watching quiet threads on its own, then flags useful details or checks in on stalled tasks without constant prompting.

The beta is live now for Claude Team and Enterprise customers on Slack. It runs on Opus 4.8 and replaces the older Slack integration. Inside Anthropic, teams already get around 65 percent of their product code through a similar internal version of this setup.

AI search is becoming the main way people look for information. Yet traditional SEO still holds value. It now works alongside AI discovery to help brands get found.

The Manus AI agent puts several key SEO tasks into one workflow. This covers keyword research, competitor analysis, site audits, backlink prospecting and rank tracking. You describe your goal in plain terms and it manages the execution using available tools and data.

For example it audited a site seeing 180k daily organic visits. The check turned up 8,456 slow pages, a mobile performance score of just 28 out of 100 and 4,431 pages absent from the sitemap. Fixes get ranked by likely impact.

It also identifies content gaps. A focused topic like the best CRM for three person sales teams often performs better than a general term because it directly answers a real question.

Backlinks from relevant sites continue to help. Manus can analyze competitor backlinks and flag opportunities where similar links could point to your brand instead.

This combined approach supports visibility in both regular search engines and AI powered systems.

ElevenLabs just added Ads Engine to its ElevenCreative platform. The tool lets marketers connect their Google, Meta, and LinkedIn ad accounts and turn existing campaigns into versions that work in more than 50 languages.

It pulls your current ads and performance data, then handles the heavy lifting. Text gets translated, images get adapted so they feel right for each market, and videos get dubbed with the Dubbing V2 model that keeps the original speaker’s voice, tone, and emotion.

You review the results, add an approval step if your team needs it, and push the finished creatives straight back to your ad platforms. Save the whole setup as a template and anyone on the team can run the same workflow on new campaigns without reinventing the process.

The system also watches results and flags when performance starts to drop so you can refresh creatives before they go stale. What used to take separate teams, extra budgets, and days or weeks per language now happens in one connected flow.

It is available on Pro plans and above right now, with more features planned. For brands running ads in multiple countries, this removes one of the biggest headaches in scaling campaigns.

Forbes just ran an interview with YouTube CEO Neal Mohan about the wave of AI made videos hitting the platform. He is trying to figure out how to stop low quality spam from taking over while still letting AI help creators do better work.

A bunch of this new content is what people call AI slop. Think repetitive videos, deepfake scams and low effort clips that flood Shorts feeds. Some checks showed a noticeable share of what new users see could be AI generated. Mohan knows viewers do not want their recommendations filled with junk that feels fake or pointless.

At the same time he is not against AI. He sees it as a tool that can cut the boring parts of video making and let people focus on ideas and stories. YouTube has already added features like AI avatars in Shorts and Gemini powered tools in Studio to help with scripting, dubbing and brainstorming.

The plan is straightforward. YouTube will label videos that are clearly made or changed with AI. They are rolling out a likeness detection tool so people can check if someone used their face or voice without permission. The algorithm will also push down stuff that people do not actually watch for long. Channels breaking spam rules are getting terminated.

Mohan keeps coming back to one point. The heart of YouTube has always been real human creativity. AI should support that, not replace it. The platform started with simple authentic videos and that core needs to stay.

It is a tricky balance but one the company is actively working on as AI video tools keep getting stronger.

Alibaba Cloud sees a big change coming. Their CTO and President of International Business, Dr Feifei Li, believes the next three years will focus heavily on something they call the Agentic Cloud.

The basic idea is simple. Cloud systems will get designed so AI agents can directly tap into products and services to handle tougher tasks. No more humans doing every little step through dashboards. These agents would call the resources themselves and just get the job done.

Alibaba is already putting this into practice. They've turned a bunch of their cloud tools into skills that agents can use easily. Inside the company, teams are also creating special agents for databases, big data work, and security.

This fits with what they shared at the recent Qwen Conference. They outlined four key pieces for building agent-focused apps. Models matter, but the real game-changer they see is the infrastructure that lets agents actually do meaningful work.

What do you think? Is agentic cloud the next big step or just more hype?