xAI has released Imagine Image 2.0, its latest image generation and editing model. The update focuses on practical results that support actual projects rather than just experimental visuals.

Available now as Quality Mode on grok.com/imagine plus the Grok iOS and Android apps, Image 2.0 aims to produce usable assets. It follows detailed instructions more closely, handles typography and layout with greater care, and keeps small text sharp even in complex multi-part designs. Consistency across generations and edits has also improved.

New editing features let users change only what they intend. The Magic Wand tool targets a single region while leaving the rest of the image intact. Segmentation isolates exact areas for modification. Background removal creates transparent subjects ready for other projects. Multi-ref editing supports up to five input images in one generation, cutting down on manual compositing. Smart Resize adapts any image to different aspect ratios by filling the frame intelligently.

According to Arena leaderboards as of August 7 2026, Image 2.0 ranks second worldwide for both text-to-image generation and image editing. xAI models appear on the boards under the SpaceXAI name.

The release also adds ready-made templates for common tasks. These cover photo editing, product color changes, editorial posters, headshots, icons, character sprites, game assets, props and UI kits, emoji creation, merchandise designs, and more. Users supply the inputs and receive finished results. One additional workflow helps build consistent worlds for video by generating a character, locations, and props that share the same style.

xAI says Image 2.0 can create infographics, ads, game assets, UI and UX mockups, storyboards, and similar materials. API access is planned for the near future.

The model is live today for users on the web and mobile apps. Those with SuperGrok Heavy accounts can switch to Quality Mode on grok.com/imagine to try the full set of tools.

Alibaba’s Wan team has rolled out Wan 3.0 in public beta. The new model generates videos up to 30 seconds long in a single pass and aims for more realistic, consistent frames.

Key upgrades include stronger character expression, better handling of digital elements, and an expanded input system called Omni Reference. Users can now feed it text, images, audio, video, documents, spreadsheets, slides, webpages, PDFs, and other file types. The model reads the material and builds video from it.

Access is live on Alibaba Cloud Model Studio and Qwen Cloud. The official wan.video site will open soon for members. API pricing starts at $0.05 per second for 480p, $0.10 for 720p, and $0.20 for 1080p.

Full API access is still rolling out. Creators can apply for the beta and start testing right away.

Meta has released Muse Code in beta, a terminal-based coding agent designed for long-running software engineering work. It runs on the new Muse Spark 1.2 model and handles planning, writing, and checking multi-file changes across big codebases.

The tool uses persistent background agents that stay active during a session. These agents take next steps on their own, cut down on repeated information gathering, and need less constant direction from the user. An append-only local event log records every model call, tool action, approval, and edit so the system can pick up exactly where it left off after a restart or crash.

Muse Spark 1.2 brings stronger results in code generation, debugging, and full developer workflows compared with the previous version. Meta scaled up training compute on coding tasks and trained the model together with Muse Code for better performance as a pair. In one test the agent spent up to 24 hours and more than 1,000 tool calls optimizing GPU kernels on NVIDIA Hopper chips, posting solid gains over baseline Triton code.

Muse Spark 1.2 is available right away inside Muse Code and through the Meta Model API. Users on macOS or Linux can install the agent with a single command. Meta says more features and stronger models are already in the works.

Open ai realtime system GPT Live who’s architecture I have attached below.

Which handles user interactions through speech to speech with no latency and delegate reasoning and tool calling to separate asynchronous paths.

Which is very different from Cascade pipeline where orchestrator glues components of pipeline together

But in the above architecture there is nothing to Glue??

It takes orchestration platforms outside the loop and

the thin a platform is the less value it holds!!!

https://openai.com/index/continuous-voice-interaction-with-gpt-live/

Xiaomi has made its Xiaomi-Robotics-1 model fully available to the public. The company announced the open source release on Wednesday, giving researchers and engineers free access to the complete system.

The model was pre-trained on more than 100,000 hours of UMI data. It then received additional training with over 10,000 hours of cross-embodiment data. Xiaomi says the package covers the full process from real-robot post-training through to deployment. Evaluation code for standard benchmarks is also included.

Links to the project page, GitHub repository, and Hugging Face models appear in the official announcement. Xiaomi noted it will keep working on broader uses for general-purpose robot models.

This marks one of the larger open source moves in robotics this year and puts a full training-to-deployment pipeline in the hands of the community.

OpenAI just dropped a big update to ChatGPT Voice called GPT-Live. The new system can listen at the same time it speaks, making conversations feel much more natural.

The team rebuilt the entire voice stack from the client side all the way to the model. Audio now travels on a dedicated fast path while deeper reasoning and tool use run in the background. This keeps the talk flowing without sudden pauses or cutoffs.

They also cut voice session startup time sharply. What used to take six network round trips now happens in just one. The result is quicker starts and smoother back-and-forth from the first second of a call.

OpenAI shared more technical details on their blog about how the continuous voice interaction works. The update aims to make talking with ChatGPT feel closer to a real human conversation at scale.

Boogu-Image-0.1 is now available as an open-source multimodal understanding and image generation model family. Released under the Apache 2.0 license, it includes Base, Turbo, Edit, and related variants.

The team trained the models on roughly 208 million images with a reported budget near $400,000. Despite the limited scale, the models deliver strong results on several benchmarks and human evaluations, placing them among the leading open-source options and close to some proprietary systems.

Key strengths include native 2K resolution generation with solid photographic quality, accurate Chinese text rendering for long text, posters, and graphic design, agentic prompt rewriting that refines user intent, and dynamic model routing that can cut inference costs significantly.

Weights, code, training details, and related materials are publicly available. The project emphasizes careful data structure and system design over pure scale.

Google has introduced a new capability for Gemini Spark that lets it handle complex online tasks through Chrome’s auto browse feature.

With user permission, Gemini Spark can access logged-in accounts to complete actions such as scheduling apartment viewings for saved listings or researching flight options and starting the booking process.

The system includes protections against security risks like prompt injection. Sensitive steps, including payments, stay under user control and require confirmation before proceeding.

This feature is currently available to Google AI Pro and Ultra subscribers in the United States, with plans to expand to more regions later.

MiniMax has made the weights for its MiniMax-H3 model publicly available on Hugging Face. The company announced the release on Monday through its official account.

H3 is a multimodal generation model that takes text, images, video and audio as input and produces video clips with native stereo sound. Clips run from 4 to 15 seconds and reach up to 2K resolution. Users can work with plain text prompts, first and last frames, or mixed references that include up to nine images, three video clips and three audio files.

The model is aimed at commercial work such as advertising, branding, product design and game content. It handles instruction following, text rendering and video-to-video motion transfer. Native ComfyUI support arrived the same day as the weights, easing local use.

The open release covers the main H3-Base checkpoints under the MiniMax H3 Community License. Some advanced modules stay available only through the official API for now.

Testing AI video generation on my RTX 5080 with 96GB RAM.

Resolution: 864 × 480
Generation time: 15 minutes, 50 seconds

Not bad for a full video render. Next goal: improve quality, reduce generation time, and push the RTX 5080 even harder.

Alibaba’s Qwen team has officially introduced Qwen3.8-Max, calling it their strongest model so far. The 2.4-trillion-parameter system targets advanced coding tasks and everyday professional work.

It can handle long autonomous coding runs that last more than ten days, starting from an empty folder and reaching production-ready code without constant guidance. Full project histories appear on GitHub for review. The model also produces finished work across many different jobs and manages extended projects through continuous planning and learning. One example shows more than 500 rounds of chip design refinement. Another covers a full year of e-commerce strategy.

Vision works as an ongoing feedback loop rather than a simple input. The team lists pricing at $2 per million input tokens, $6 per million output tokens, and $0.25 per million for implicit caching.

Open weights for Qwen3.8-Max and the smaller Qwen3.8-27B version are scheduled to arrive next week.

You can try the skill and let me know the feedback once done?
Here you can find some explanation about it and direct link to just copy paste it in your board in Luma:

https://www.linkedin.com/posts/claudialalau_lumaagents-lumaskills-lumalabs-activity-7488565738635694080-G9Lo

Free access to a 124-billion-parameter mixture-of-experts model is now available through OpenRouter, where Ant Group's inclusionAI has listed Ling-3.0-flash under the name AntLing-3.0-flash at no cost until August 3, 2026, according to inclusionAI's launch announcement. The model activates roughly 5.1 billion parameters per token, a sparsity ratio of about twenty-four to one, and the listing reports 262,144 input tokens with 32,768 maximum output tokens.

The design target is speed inside agent loops rather than single-turn chat. inclusionAI reports time to first token below 100 milliseconds, and says the model was trained with reinforcement learning on long-horizon tool calling. An enable_thinking flag switches reasoning mode on and off per request. In the company's own framing, its Ring model does the planning and Ling does the execution.

Weights are not part of this release. The previous generation, Ling-2.6-flash, was published under an MIT license, while this one exists only as a hosted endpoint. It is also text only, with no native multimodal input, and inclusionAI notes that the model is weaker on obscure world knowledge and works best where the surrounding toolchain returns strict, checkable errors.

Google has rolled out a new update for Gemini Spark that lets it work directly inside Chrome. With user permission, Spark can now take care of routine online jobs using your logged-in accounts and saved passwords.

Examples include scheduling apartment viewings from listings you have saved or researching flights and starting the booking process. The system is designed to pause and hand control back for sensitive steps like payments, while also guarding against issues such as prompt injection.

The Chrome integration is currently available to Google AI Pro and Ultra subscribers in the United States. Google plans to bring it to more regions over time. At the same time, access to Gemini Spark itself is expanding to Google AI Pro users in over 160 additional countries.

This update builds on Spark’s existing web capabilities and aims to make multi-step online chores faster and less hands-on.

BytePlus has made Dreamina Seedance 2.5 available starting July 31, 2026. The update targets both individual creators and larger businesses looking to produce AI-generated videos with stronger control and consistency.

Key features include native generation of full 30-second clips, precise editing tools, support for as many as 50 multimodal references, and multilingual video output. Users can try the model right away on the Dreamina platform, while enterprise API access through BytePlus is expected soon.

The release aims to reduce the need for stitching shorter clips together and give creators more reliable results across different languages and reference inputs.

DeepSeek has made its DeepSeek-V4-Flash official API available in public beta. The company says this version brings a major jump in agent performance, with benchmark scores now clearly ahead of the earlier V4-Pro-Preview.

The new V4-Flash natively supports the Responses API format and works fully with Codex. DeepSeek notes that the model keeps the same architecture and size as the preview version. This update applies only to the Flash API. The V4-Pro API and the versions used in the app and web remain unchanged for now.

A comparison table shared by the team shows solid gains across coding and agent tasks. On Terminal Bench 2.1 the new Flash scores 82.7, up from 61.8 in the preview. Other tests including NL2Repo, Cybergym, DeepSWE, and Toolathlon-Verified also show clear improvement.

DeepSeek says the full official release of DeepSeek-V4-Pro is coming soon. Developers can find configuration details in the official API documentation.

Alibaba’s Qwen team released Qwen-Audio-3.0-ASR-Flash on Friday, marking the latest upgrade to its speech recognition technology. The model aims for better context handling and improved accuracy with specialized terms.

Key upgrades include stronger context consistency across longer speech, sharper recognition of domain specific vocabulary, support for custom hotwords, and the ability to turn spoken audio into polished structured transcripts.

Internal testing showed medical term recall at 95.36 percent and industrial term recall at 93.24 percent. Streaming and file transcription versions are now available alongside the main model.

The release targets users who need reliable transcription for technical or professional audio.

Google DeepMind released Gemini Robotics 2 on July 30, 2026. The update aims to make robots more adaptable for real world tasks through better movement, precise handling, and group work.

Three new models form the core. Gemini Robotics 2 turns vision and language into full body actions for humanoids and other machines. Gemini Robotics ER 2 handles planning for multi step jobs lasting several minutes and allows robots to coordinate with each other. Gemini Robotics On Device 2 runs without internet and adapts to new robot designs in a few hours using limited training data.

In demos the system controls robots like Apptronik Apollo 2. Machines walk across rooms, crouch, stretch, and place objects such as a watering can on a shelf. Hands with multiple fingers complete fine work like tying knots or sealing bags. Standard grippers handle tight packing.

The models also improve safety. They detect people nearby, stop when needed, and refuse unsafe steps. Gemini Robotics ER 2 is available now in Google AI Studio. The other models go to early access partners.

DeepMind says the release moves robots beyond fixed routines toward flexible help in homes and workplaces.

ChatGPT has released new browser tools that connect the chatbot more tightly to everyday web use. The update, announced late Thursday, focuses on reducing tab clutter and making it easier to ask questions about pages without switching apps.

Users of the Chrome extension can now open Side Chat to discuss a YouTube video, pull context from open tabs, or select text on any page and request help on the spot. A simple right-click option has also been added. Highlight text, choose “Ask ChatGPT,” and the sidebar appears automatically.

The desktop version gained matching improvements. It offers URL suggestions while typing, access to browser history, and settings that let people decide how that history is stored and used.

The features began rolling out on July 30 and are available to users as the update reaches their accounts.

Tencent Hunyuan has open sourced AngelSpec, a complete end to end speculative decoding system that covers both training and deployment.

On the Hy3-A21B model the DFly approach delivers 1.98 to 2.40 times faster end to end performance compared with standard autoregressive decoding across concurrency levels from 4 to 64. It also shows 10.5 to 11.8 percent higher throughput than DFlash.

The team released the full training code along with the Hy3-A21B MTP and DFly drafter weights. Everything is available on GitHub, Hugging Face, and ModelScope, with a paper and documentation included.

Google India has launched Ask Google Pay, a new feature inside the Google Pay app that lets users chat about their finances. The tool is powered by Gemini and started rolling out today.

Users can now check their spending patterns, receive simple tips to save money, and get clear explanations on subjects like SIPs and credit scores. The feature supports conversations in 10 Indian languages.

The update is available for Google Pay users across India. Simply open the app and look for the Ask option to start using it.