AI Models Release Notes
Release notes for leading AI models, APIs and AI platforms
Products (16)
Latest AI Models Updates
- Jun 3, 2026
- Date parsed from source:Jun 3, 2026
- First seen by Releasebot:Jun 4, 2026
Introducing new capabilities to GPT-Rosalind
OpenAI releases an updated GPT-Rosalind for life sciences research, bringing stronger agentic coding, better drug-discovery and genomics performance, and new plugins for evidence retrieval and bioinformatics workflows. It also expands trusted-access research preview for eligible organizations worldwide.
Bringing greater intelligence grounded in real scientific workflows for the life sciences industry.
We’re introducing a new model update to our GPT‑Rosalind series purpose-built for life sciences research at enterprise scale. It combines GPT‑5.5’s agentic coding and tool-use capabilities with stronger model intelligence in core drug-discovery domains such as medicinal chemistry and genomics, while advancing performance across broader life sciences analysis, design, and experimental workflows.
Progress in life sciences depends on synthesizing data and evidence across scales and modalities: molecules, genes, pathways, and living systems. In our evaluations, the updated GPT‑Rosalind shows broad performance gains on research tasks from biology experts, complex medicinal chemistry queries, quantitative biology, and wet lab troubleshooting.
GPT‑Rosalind is now available in research preview to eligible organizations globally through our trusted-access deployment structure.
Improving performance on scientifically-valuable tasks
In order to measure and continuously improve the real-world impact of GPT‑Rosalind, we designed LifeSciBench, an externally expert-judged benchmark focused on foundational aspects in life sciences research. Unlike existing benchmarks that evaluate a single component of model performance or biological domain in isolation, LifeSciBench takes an end-to-end view of scientifically valuable work by drawing tasks from six workflow areas central to life sciences research: evidence handling, analysis, design and optimization, scientific reasoning, validation and operations, and translation and communication. We use this benchmark to align progress with the needs and realities of life sciences research.
GPT‑Rosalind leads performance across scientifically-valuable tasks identified by industry and academic experts.
Evidence Handling example and detailed candidate response with regulatory conclusion and rubric criteria & grades are included, highlighting key evaluation points and areas for improvement.
Stronger scientific reasoning
Medicinal chemistry
GPT‑Rosalind achieves industry-leading performance in medicinal chemistry, a field focused on turning molecules into useful drugs. We designed MedChemBench to reflect realistic medicinal chemistry workflows, evaluating multimodal chemical structure understanding; structure-activity relationship (SAR); prediction of drug potency, toxicity, and absorption, distribution, metabolism, excretion (ADME); multiparameter lead-optimization decision-making; and retrosynthesis. GPT‑Rosalind out-performs GPT‑5.5 at 27.5% vs. 25.1% on MedChemBench, while using 7.2% fewer tokens.
Genomics and quantitative biology
On GeneBench, our agentic evaluation on long horizon, end-to-end analysis in genomics and quantitative biology, GPT‑Rosalind uses 31% fewer tokens than GPT‑5.5 while achieving a higher accuracy of 21.6% vs. 20.4%. GeneBench assesses agentic performance on long-horizon quantitative tasks: based on realistic scientific data, can an agent plan valid analysis, QC, modeling, and corrections to arrive at decision-relative answers? Included problems span a variety of domains, including functional genomics, spatial transcriptomics, proteomics, epigenomics, and applied genetics.
Assisting real-world lab work
We introduce a new evaluation to test GPT‑Rosalind’s ability to help scientists conducting lab work in the real world. LabWorkBench tests the model's ability to link perturbations to experimental outcomes in real wet lab protocols used by scientists, for the purposes ranging from troubleshooting to optimization. The data used by LabWorkBench are proprietary and thus uncontaminated. GPT‑Rosalind scores 63.2% vs. GPT‑5.5 at 55.8%, while using 5.3% fewer tokens.
From reasoning to executed workflows
We built the Life Sciences Research and Life Sciences NGS Analysis plugins to extend the increased intelligence of GPT‑Rosalind with a practical execution layer for repeatable scientific workflows. Together, these plugins bring sourced evidence retrieval, biological interpretation, and bioinformatics execution into the same workspace, helping researchers connect external evidence with internal omics analyses while preserving artifacts and provenance. All users can now access both plugins through Codex. Qualified GPT‑Rosalind enterprise users can additionally use GPT‑Rosalind to power these plugins.
To better leverage Codex as a dynamic workbench for scientists, we added interactive viewers for biologically native file types. The initial set of sequence, alignment, and structure viewers are designed to keep scientists close to the evidence as GPT‑Rosalind reasons across a workflow and directly answer follow-up questions using the active viewer in-context.
The demo shows these capabilities in action, orchestrated by GPT‑Rosalind, following a scientist investigating a liquid tumor biopsy to identify mutations and molecular changes that could inform treatment.
Expanded access for trusted organizations
We are expanding access to the GPT‑Rosalind series to eligible organizations globally. GPT‑Rosalind will be available in research preview through our trusted-access deployment structure for organizations conducting legitimate scientific research with clear public benefit, strong governance and safety oversight, and controlled access with enterprise-grade security.
Novo Nordisk is leveraging frontier AI capabilities to help researchers analyze complex datasets, uncover useful patterns, and test hypotheses more quickly. GPT‑Rosalind’s stronger biological understanding will help teams connect evidence across literature, genomics, transcriptomics, sequence, structure, and experimental results, making it easier to move from data to clearer research decisions.
We are also now offering an OpenAI managed workspace for qualified organizations without an Enterprise account.
What’s next
The updated GPT‑Rosalind is the next step in our broader commitment to building AI systems that can help accelerate scientific discovery while ensuring that advanced biological capabilities are deployed with appropriate safeguards. We will continue improving the model’s biological reasoning, expanding support for tool-heavy and long-horizon research workflows, and working with qualified organizations across regions to evaluate real-world impact.
This also means applying life sciences AI to high-impact public-benefit work, from drug discovery and translational medicine to public health, preparedness, and biodefense. Through Rosalind Biodefense and our trusted-access deployment model, we aim to put frontier biological capabilities in the hands of the researchers, institutions, and defenders working to improve human health and strengthen societal resilience.
We will continue building GPT‑Rosalind to become a more capable partner across the full life cycle of scientific research, helping scientists move more quickly from the right questions to clearer evidence, better experiments, and ultimately new treatments for patients.
Original source - Jun 3, 2026
- Date parsed from source:Jun 3, 2026
- First seen by Releasebot:Jun 4, 2026
Grok Imagine 1.5 Preview
xAI releases grok-imagine-video-1.5-preview, a new image-to-video model available in the xAI API preview. It turns still images into cinematic video with natural-language motion control, supports up to 720p, and keeps the look and lighting of the source image.
grok-imagine-video-1.5-preview, our latest image-to-video model, is now available via the xAI API in preview.
Our latest image-to-video model, grok-imagine-video-1.5-preview, is now available via the xAI API in preview.
grok-imagine-video-1.5-preview turns a single still image into fluid, cinematic video. Give it a starting frame and a prompt describing the motion, and it animates the scene, including camera moves, atmosphere, and physics, while staying faithful to your source image. You can generate clips at up to 720p.
Direct the shot with natural-language prompts. Describe the camera move, the pacing, and the sound design, then set your resolution and clip length. The model holds detail and lighting from the input frame, so the result continues the original image rather than reinterpreting it.
The model also works well for sequences. Stage each frame, animate it, and chain the shots together into longer scenes that keep a consistent look across an entire project.
Animate an image in a few lines of code.
Original sourceimport os import xai_sdk client = xai_sdk.Client(api_key = os.getenv("XAI_API_KEY")) response = client.video.generate( prompt = "Slow cinematic push-in as embers drift across the battlefield and the helmet's crest stirs in the wind", model = "grok-imagine-video-1.5-preview", image_url = "https://your-host.com/helmet.jpg", duration = 10, resolution = "720p", ) print(response.url) All of your release notes in one feed
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- Jun 2, 2026
- Date parsed from source:Jun 2, 2026
- First seen by Releasebot:Jun 3, 2026
June 2, 2026
ChatGPT introduces Active sessions, a new security feature that lets users review account sessions and sign out of ones they don’t recognize. It shows session details like device, location, sign-in time, trusted status, and current session info.
Active account session controls
We’re rolling out Active sessions, a new security feature in ChatGPT that helps users review sessions associated with their account and sign out of sessions they don’t recognize.
Users can now:
- Review first-party OpenAI sessions from Settings > Security > Active sessions, with available details such as device, app, approximate location, sign-in time, trusted-device status, and whether it is the current session
- Log out of individual sessions or all sessions from Active sessions
Active sessions shows sessions known through session management, including ChatGPT, Codex, and API Platform sessions where available. It does not manage third-party app sessions, connected apps, Sign in with ChatGPT sessions used only for third-party services, or Codex CLI sessions.
Learn more: Managing active sessions in ChatGPT
Original source - Jun 2, 2026
- Date parsed from source:Jun 2, 2026
- First seen by Releasebot:Jun 2, 2026
Codex for every role, tool, and workflow
OpenAI expands Codex with role-specific plugins, previewed Sites for sharing interactive workspace apps and websites, and annotations that let teams refine documents, spreadsheets, slides, and more in place.
New role-specific plugins, Sites, and annotations help teams do more with Codex.
More than 5 million people now use Codex every week. Codex started as a tool for software development, but it's increasingly useful for more kinds of work. Non-developers—including analysts, marketers, operators, designers, researchers, investors, and bankers—make up about 20% of overall Codex users and are growing more than 3x as fast as developers.
Today, we’re introducing new ways to do more of your work with Codex: plugins that adapt Codex to your role and tools, annotations that help you refine the result in place, and a preview of the ability to create interactive websites and apps you can share with your workspace using a URL.
Inside OpenAI, non-technical teams use Codex to build internal apps, prepare executive materials, create dashboards, and turn creative briefs into work that reflects brand and design constraints. At Zapier, teams use Codex to pull knowledge from tools like Slack, Google Docs, and Coda, then turn that context into postmortems, incident response plans, and feature tickets. At NVIDIA, researchers are using Codex to speed up experiment workflows, from finding research ideas to writing scripts for machine learning infrastructure.
Make Codex work the way your team does
Codex is most useful when it works the way your team does: connected to the tools you use and ready to create the materials you need.
Plugins help Codex work with the tools, context, and workflows your team already uses. Today, we’re launching six new role-specific plugins that make Codex useful for more kinds of knowledge work, no coding required:
- Each plugin bundles the relevant apps, skills, instructions, and workflows. Together, they include 62 popular apps and 110 skills.
- The data analytics plugin helps analysts and business teams answer questions with data. They can explore product and business data, explain why key metrics changed, and create reports and dashboards using tools like Snowflake, Databricks Genie, Hex, and Tableau, with more coming soon.
- The creative production plugin helps marketing and creative teams turn a brief into assets they can review. Teams can create campaign boards, make and refine display ad variations, and produce product lifestyle shots or ecommerce-ready image sets with tools like Figma, Canva, Shutterstock, Picsart, and Fal.
- The sales plugin helps sales teams bring customer context into the work that moves deals forward. Sales teams can find high-priority accounts and signals, prepare for customer meetings, complete follow-ups, update customer records, build close plans, and review deals at risk using tools like Salesforce, HubSpot, Slack, Outreach, Clay, Rox, and Actively.
- The product design plugin is built for turning early ideas into prototypes teams can review. Teams can explore product directions, audit user flows, prototype from a live URL, and make static screenshots interactive, with work that can be carried forward in tools like Figma and Canva.
- The public equity investing plugin helps investors make sense of market and company information. They can review earnings, compare companies, track signals, and assess whether an investment thesis is strengthening or weakening using information from Moody’s, Daloopa, Datasite, FactSet, LSEG, S&P, PitchBook, and Hebbia.
- The investment banking plugin helps bankers turn research and diligence into client-ready materials. They can prepare pitch materials, analyze comparable companies and transactions, and turn diligence into recommendations using trusted data.
Plugins work out of the box. Teams can also adapt them to their workflows or build and share custom plugins for their own systems and processes.
More role-specific plugins are coming soon, including Corporate Finance, Private Equity Investing, Marketing Strategy, Strategy Consulting, and Legal. And this is just the start: we’re building toward an open ecosystem where partners can create and deploy their own plugins directly in Codex and ChatGPT.
Share your work with sites
Starting in preview for business and enterprise customers, Codex can now create and share interactive, hosted websites and apps.
Sites are a new kind of canvas for your ideas. Codex can take your ideas, analysis, and plans and turn them into dashboards, planners, review workspaces, project boards, galleries, and lightweight tools. Today, sites can be shared with anyone in your workspace via URL, giving teams a shared place to explore work, contribute input, track progress, and make decisions together.
Ask Codex to create a site for an upcoming customer review, and it’ll generate an interactive webpage with the relevant product updates, open questions, usage trends, and next steps for that account. Ask it to build a scenario planner from a financial model, so leaders can compare assumptions instead of reading through tabs in a doc. Ask it to turn launch materials into a living hub where teams can find the latest messaging, milestones, owners, and decisions. Then ask Codex to keep the site up to date as details change.
Instead of adapting work to the limits of a single tool or file, teams can create sites that fit the work. And sites aren’t static. They can also help track progress for a major project, help guide customer service reps, or act as a repository for your team’s creative briefs.
We’re also working with early partners including Vercel, Wix, Base44, Replit, Lovable, Figma, Webflow, and Emergent as we build towards a sites partner ecosystem.
Refine your work with annotations
Developers already use annotations in Codex to refine code, Markdown files, and websites Codex creates. With annotations, you point to the exact part you want to refine and tell Codex what needs to change. That way of working now extends to content you create, like documents, spreadsheets, and slides.
Select the navigation bar in a site and ask Codex to update the font. Highlight a claim in an investment thesis and ask Codex where it came from. Mark a chart on a slide and ask for a clearer label. Codex focuses the update on the part you selected, so you can refine your work without starting over or reworking the parts you already like. Annotations make Codex more useful after the first draft, when the work needs judgment, feedback, and iteration.
Availability and getting started
Role-specific plugins are rolling out in Codex in supported regions. You can install them from the Codex plugin directory and Codex will help get you set up. Codex can also help you customize a plugin. For Business and Enterprise workspaces, admins can control (opens in a new window) underlying app permissions in workspace settings.
Sites are rolling out in preview for Business and Enterprise teams through the Codex app. Enterprise admins can enable sites (opens in a new window) in admin settings.
Explore more stories about how teams use Codex, or get in touch with our team to get started.
Original source - Jun 2, 2026
- Date parsed from source:Jun 2, 2026
- First seen by Releasebot:Jun 2, 2026
Expanding Project Glasswing
Anthropic expands Project Glasswing, extending Claude Mythos Preview access to about 150 new organizations and adding Claude Security for codebase scans and patch suggestions. It also plans to share vulnerability-finding tools with trusted security teams to strengthen cyberdefenses.
The role of Project Glasswing
Project Glasswing is our collaborative effort to secure the world’s most important software. In early April, we announced that roughly 50 initial partners had access to Claude Mythos Preview, and since then, they’ve been deploying the model to scan their codebases for vulnerabilities. We recently described how these partners have so far found more than 10,000 high- or critical-severity security flaws.
We’re now expanding Project Glasswing. Following several weeks of close collaboration with our Project Glasswing partners, the security industry, open-source software maintainers, and the US government, we’re extending the partnership to approximately 150 new organizations. Each one will need to meet our security requirements before they gain access.
The organizations in this new group are based in more than 15 countries, and most provide critical infrastructure to many more. (In the future, we intend to expand our geographical reach much further.) The group covers several industries that weren’t well represented in our initial cohort, such as power, water, healthcare, communications, and hardware. And many of the new partners are vendors—companies or nonprofits that maintain codebases that are relied upon by lots of other organizations around the world, including governments.
What each partner has in common is that a successful attack on their codebase could be catastrophic. For most partners, we estimate that a major attack could affect more than 100 million people, with important ramifications for both global and national security.
This expansion is the next step toward our long-term goals: for AI to make all software more secure, and for us to help the industry adjust to how AI could change many of the core assumptions of cybersecurity.
Supporting cyberdefenders
Project Glasswing and the capabilities of Claude Mythos Preview have sparked broad conversations—both within the software industry and with governments—about how AI is changing cybersecurity. These conversations have informed how we’ve expanded the program. They’ve also shaped our thinking about the very purpose of Project Glasswing.
Cheap, fast AI models with powerful cyber capabilities are around the corner. We want Project Glasswing to spur institutions toward operating norms that reflect this reality.
Mythos Preview continues a long-term trend that we’ve been warning about for some time: within 6 to 12 months, we expect that many other AI companies will have Mythos-class models, and they could release them without safeguards that prevent misuse. In that world, cyberattacks could occur much more often, and in much more unpredictable forms. It’s imperative that cyberdefenders adapt to maintain pace.
We see our role as twofold. First, to help the software industry adapt by safely providing wide access to better models, tools, and common infrastructure. Second, to steadily shift the support we provide, from finding vulnerabilities to disclosing, fixing, and deploying patched software. We’ll now discuss each of these in turn.
So far, companies, nonprofits, maintainers, and researchers have acted quickly. Within the first weeks of Project Glasswing, each member began using Mythos Preview at large scale, sharing information and best practices with other partners, and working with third parties to triage the model’s findings. These organizations’ methods for adapting to new tools can, and should, be replicated widely across the millions of organizations and developers who are vulnerable to cyberattacks.
To support this, we recently released Claude Security, a product that uses our latest public frontier models, like Claude Opus 4.8, to scan codebases and suggest patches. We're also releasing—on request, to trusted security teams—the tools we developed to help Project Glasswing’s partners find vulnerabilities more quickly.
We intend to go much further: our longer-term aim is to support the industry in creating new initiatives, standards, and infrastructure for the era of powerful cyber models.
Accelerating patching and the rest of security
As we’ve previously discussed, the bottleneck in cybersecurity is now verifying, disclosing, and patching the large numbers of vulnerabilities that Mythos-class models can surface.
Mythos Preview itself can help. Many of Project Glasswing’s partners now use the model to write patches, as well as for pre-release checks that prevent vulnerabilities from appearing in the first place. Models like Mythos Preview can also be used for penetration testing (simulating a cyberattack to identify how vulnerabilities might be exploited), automating threat detection and response, and rebuilding legacy codebases in memory-safe languages, among many other defensive tasks.
We’re in discussions with third parties about how we might substantially scale up the reviewing and patching of vulnerabilities in open-source software. We’re also working on sharing ideas and best practices for disclosing vulnerabilities to open-source maintainers, with the intent of making these reports easier to triage and to act upon.
The path ahead
To address the scale of this coming challenge, hundreds of thousands of organizations, researchers, and maintainers will likely need access to the most advanced cyber capabilities and tools available.
We’re working as quickly as we can to safely release Mythos-level capabilities in general access. To do so, we’ll need highly robust safeguards that prevent the model’s cyber capabilities from being misused—safeguards that we (and, to our knowledge, all other AI developers) have yet to develop. Because cybersecurity has both helpful and destructive uses, making safeguards that are both strong and precise enough is a major challenge.
In the meantime, we plan to expand Project Glasswing even further—prioritizing additional essential infrastructure providers, maintainers of critical open-source software, and safety testers. We intend for future expansions to cover organizations in the US and overseas, just as this one does. We also intend to scale up our Cyber Verification Program, which would grant Mythos-class capabilities to many more organizations for specific cyberdefense tasks.
In the future, frontier model releases will become increasingly high-stakes. Capabilities will continue to improve across all domains, including many that—like cybersecurity—can empower attackers and defenders alike. This will not be the last time we need to confront a challenge like this one. But Project Glasswing has taught us a great deal about how to respond when models cross important capability thresholds. If we’re successful, we hope to enable a permanent advantage for defenders.
Original source - Jun 1, 2026
- Date parsed from source:Jun 1, 2026
- First seen by Releasebot:Jun 2, 2026
OpenAI frontier models and Codex are now available on AWS
OpenAI launches frontier models and Codex on AWS, now generally available through Amazon Bedrock for commercial and GovCloud regions. The release gives enterprises a faster path to production with AWS-native security, governance, procurement, billing, and compliance controls.
Today, OpenAI frontier models and Codex are generally available on AWS, opening a new path for millions of AWS customers to build with OpenAI through the platform they already use to run their business.
For enterprises, this removes one of the biggest barriers to AI adoption: getting frontier AI into production through existing security, compliance, procurement, billing, and governance workflows. Customers can now bring OpenAI capabilities into AWS environments with the controls their teams already trust, helping them move faster from evaluation to real deployment.
Bringing OpenAI capabilities into AWS environments
OpenAI on AWS gives enterprises access to OpenAI frontier capabilities, a familiar AWS operating model, and a faster path to production. They are available in two ways:
OpenAI models on Amazon Bedrock (opens in a new window) allows teams to build AI applications using AWS-native security and governance controls.
Codex on Amazon Bedrock (opens in a new window) brings OpenAI’s leading software engineering agent - used by more than 5 million people every week - into AWS, helping teams write, review, debug, and modernize code in the environments where they already build and ship.
Together, these offerings help customers adopt OpenAI with less friction and ship with the best models available right in AWS, in both Commercial and GovCloud regions.
Helping customers move from interest to implementation
As customers begin using these capabilities, the AWS path helps reduce friction around procurement, security review, and production readiness. By making OpenAI capabilities available within familiar AWS environments, organizations can spend less time navigating operational barriers and more time building.
“At Amgen, we’re focused on applying advanced AI in ways that may help accelerate the delivery of potential new therapies while equipping our teams with advanced tools. OpenAI’s GPT‑5.5 and frontier models offer compelling advances in capability, quality, and consistency that matter in a field where the questions are complex and the standards for scientific accuracy and decision quality are exceptionally high. Making these models available on AWS gives us an important new path to explore and scale those capabilities within the responsible AI framework, including security, governance, and operational frameworks across the enterprise.”
— Sean Bruich, Senior Vice President, Chief Technology Officer at Amgen“Autodesk is the technology platform for the people who design and make the world around us. Workflows like building design are highly iterative, requiring precision, coordination, and continuous refinement across teams. With OpenAI models and Codex now generally available on Amazon Bedrock, our teams are evaluating how frontier AI capabilities and AI-powered development tools on scalable, secure AWS infrastructure can help accelerate development workflows and support more informed decision-making for our customers.”
— Ritesh Bansal, VP of Analytics Data, Agentic AI and AI/ML Platform at AutodeskWhat’s next, including cyber availability
OpenAI on AWS is the start of a broader path for customers to bring frontier AI into the environments where they already build, govern, and ship. We’ll continue expanding the OpenAI capabilities available through AWS so teams can move from evaluation to production with less friction and more confidence.
That includes future availability for Daybreak, OpenAI’s vision for changing how software is built and defended. Daybreak, which includes cyber models and Codex Security, is designed to help cyber defenders see risk earlier, act sooner, and make software more resilient by design by bringing secure code review, threat modeling, patch validation, dependency risk analysis, detection, and remediation guidance into the everyday development loop.
As specialized capabilities like Daybreak become available to customers, AWS can provide an important path for security teams to adopt them using the security, governance, procurement, and operational frameworks they already use.
Together, OpenAI and AWS can help more organizations put advanced AI to work in production.
Original source - Jun 1, 2026
- Date parsed from source:Jun 1, 2026
- First seen by Releasebot:Jun 2, 2026
Composer 2.5
xAI adds Composer 2.5 to Grok Build for SuperGrok and X Premium+ users, with strong long-running task and instruction following.
Composer 2.5 is now available in Grok Build. Try it from the /models menu.
Available to SuperGrok and X Premium+
Composer 2.5 is now available in Grok Build. Composer 2.5 is a fast, state-of-the-art model that excels on long-running tasks and following complex instructions.
Try it by typing /model and then selecting Composer 2.5 in the menu.
Original source - Jun 1, 2026
- Date parsed from source:Jun 1, 2026
- First seen by Releasebot:Jun 1, 2026
June 1, 2026
ChatGPT adds live job search and resume formatting, helping users find relevant roles and tailor resumes for specific opportunities. It surfaces personalized listings and freelance opportunities from across the web and lets users upload, create, and download polished resumes.
Find live jobs and format your resume in ChatGPT
ChatGPT can now help with more of the job search process, from finding relevant live roles to tailoring a resume for a specific opportunity.
When you search for jobs, ChatGPT can surface live listings and freelance opportunities from sources like Indeed, Upwork, Appcast, and across the web. Results are personalized using your experience, skills, and goals to highlight roles that may be a strong fit. You can follow links to apply directly on the source sites.
You can now also upload or create a resume in ChatGPT, tailor it to a specific role, and download it in a polished, professional format.
Availability:
- Job search: Available to users in the U.S. on Free, Go, Plus, and Pro plans
- Resume formatting: Available in English globally on the web for all plans
- May 31, 2026
- Date parsed from source:May 31, 2026
- First seen by Releasebot:Jun 1, 2026
Qwen3.7-Plus: Multimodal Agent Intelligence
Qwen introduces Qwen3.7-Plus, a multimodal agent model that unifies vision and language for a versatile upgrade.
Today we introduce Qwen3.7-Plus — a multimodal agent model that unifies vision and language into a single, versatile agent foundation. Building on Qwen3.7's strong text backbone, Qwen3.7-Plus delivers a comprehensive upgrade in vision-language...
Original source - May 29, 2026
- Date parsed from source:May 29, 2026
- First seen by Releasebot:May 31, 2026
9 demos of Gemini Omni and Gemini 3.5 in action
Gemini introduces Gemini Omni and Gemini 3.5 Flash, bringing video generation and conversational video editing plus faster agentic coding and multi-step workflow execution. The rollout also expands availability across the Gemini app, Search, Workspace, AI Studio and enterprise tools.
Gemini Omni
With Gemini Omni, Gemini’s ability to reason meets the ability to create, while Gemini 3.5 is built to help you execute complex, agentic workflows.
At Google I/O 2026, we announced our latest models: Gemini Omni and the Gemini 3.5 family of models.
Gemini Omni is our new model that can create anything from any input, starting with video. With Omni, you can combine images, audio, video and text as input and generate high-quality videos grounded in Gemini's real-world knowledge. You can also easily edit your videos through conversation.
Then there’s Gemini 3.5, our latest family of models combining frontier intelligence with action. This represents a major leap forward in building more capable, intelligent agents. We’re kicking off the series by releasing 3.5 Flash. It delivers frontier performance for agents and coding, excelling at complex long-horizon tasks that deliver real-world utility.
To give you a clearer understanding of Gemini Omni and Gemini 3.5 Flash, here are 9 demos of what they can help you do.
Gemini Omni
Edit your videos through conversation. One capability that makes Omni special is that it gives you an easier way to edit video — with natural language. Every instruction builds on the last. Your characters stay consistent, the physics hold up and the scene remembers what came before. That means you can transform the world around you. Change specific things, or change everything. Your video becomes the starting point for something you never could have filmed yourself.
Reimagine the action. Take a video you shot and just ask Omni to change what’s happening. Edit the action, add in new characters or objects or transform a moment into something unexpected.
Refine your videos across multiple turns. Change the environment, angle, style or even specific details, without ever losing the thread of your original scene. Scroll through the carousel to see how edits build on each other.
Gemini 3.5 Flash
Take on agentic tasks at scale. 3.5 Flash delivers intelligence that rivals large flagship models on multiple dimensions, at the speeds you have come to expect from the Flash series. This balance of speed and performance makes 3.5 Flash ideal for tackling long-horizon agentic tasks. Here, powered by Antigravity, 3.5 Flash executes multi-step workflows to automatically rename and categorize unstructured assets based on dynamic criteria.
When coupled with the updated Antigravity harness, 3.5 Flash becomes a powerful engine for deploying collaborative subagents to tackle problems at scale for the most demanding use cases. Under supervision, it can reliably execute multi-step workflows and coding tasks while sustaining frontier performance.
Create richer, more interactive web UIs and graphics with 3.5 Flash. 3.5 Flash builds on the strong multimodal foundation of Gemini 3. Watch as 3.5 Flash generates different UX approaches for a checkout flow in just 60 seconds on AI Studio.
Try personal AI agents and new intelligent experiences. 3.5 Flash is now the default model for the Gemini app and AI Mode in Search globally. Its agentic capabilities are powering new features to bring frontier-level intelligence to your daily life.
The enhanced agentic coding capabilities of 3.5 Flash are delivering even more intelligent experiences in Search, like our new information agents. Operating in the background, 24/7, these agents intelligently reason across information to find exactly what you need at exactly the right moment. They will send a comprehensive update along with links to the web to dive deeper, so you can take action. Information agents will launch first for Google AI Pro & Ultra subscribers this summer.
Now that we’re bringing the power of Google Antigravity and agentic coding capabilities of Gemini 3.5 Flash right into Search, Search can build the ideal response, in the right format for your question — completely on the fly. So you can get custom generative UI, including visual tools and simulations, tailored precisely to your needs. These generative UI capabilities will be available for everyone in Search this summer, free of charge.
For your ongoing tasks like planning a wedding or establishing a new fitness routine, Search will also build you custom experiences – like dashboards, trackers or mini apps – that you can keep coming back to. You’ll be able to create your own custom experiences with Antigravity right in Search in the coming months, starting first for Google AI Pro and Ultra subscribers in the U.S.
Then there’s the new Gemini Spark, your personal AI agent, which runs on Gemini 3.5 and uses the Antigravity harness. It runs 24/7, helping you navigate your digital life, taking action on your behalf while under your direction. It’s deeply integrated with the Workspace tools you rely on daily, like Gmail, Docs, Slides and more. Gemini Spark is now available to all Google AI Ultra subscribers in the U.S.
Gemini Omni Flash is rolling out to all Google AI Plus, Pro and Ultra subscribers globally through the Gemini app and Google Flow. It’s also rolling out at no cost to users on YouTube Shorts and YouTube Create App. In the coming weeks, we'll also be rolling it out to developers and enterprise customers via APIs.
Gemini 3.5 Flash is generally available via Google Antigravity, the Gemini API in Google AI Studio and Android Studio, Gemini Enterprise Agent Platform and Gemini Enterprise. It’s also available for everyone in AI Mode in Search and now rolling out to everyone globally in the Gemini app.
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