Aurora Mobile announces GPTBots.ai integration of Genie 3 by Google DeepMind
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TechCrunch
3 hours ago
- TechCrunch
Anthropic takes aim at OpenAI, offers Claude to ‘all three branches of government' for $1
Just a week after OpenAI announced it would offer ChatGPT Enterprise to the entire federal executive branch workforce at $1 per year per agency, Anthropic has raised the stakes. The AI giant said Tuesday it would also offer its Claude models to government agencies for just $1 – but not only to the executive branch. Anthropic is targeting 'all three branches' of the U.S. government, including the legislative and judiciary branches. The move comes after OpenAI, Anthropic, and Google DeepMind were added to the General Services Administration's list of approved AI vendors that can sell their services to civilian federal agencies. TechCrunch has reached out to Google to see if it plans to respond to Anthropic's and OpenAI's challenges in kind. Anthropic's escalation – a response to OpenAI's attempt to undercut the competition – is a strategic play meant to broaden the company's foothold in federal AI usage. 'We believe the U.S. public sector should have access to the most advanced AI capabilities to tackle complex challenges, from scientific research to constituent services,' Anthropic said in a statement. 'By combining broad accessibility with uncompromising security standards, we're helping ensure AI serves the public interest.' Anthropic will offer both Claude for Enterprise and Claude for Government. The latter supports FedRAMP High workloads so that federal workers can use Claude for handling sensitive unclassified work, according to the company. FedRAMP High is a stringent security baseline within the Federal Risk and Authorization Management Program (FedRAMP) for handling unclassified sensitive government data. Anthropic will also provide technical support to help agencies integrate AI tools into their workflows, according to the company. Techcrunch event Tech and VC heavyweights join the Disrupt 2025 agenda Netflix, ElevenLabs, Wayve, Sequoia Capital, Elad Gil — just a few of the heavy hitters joining the Disrupt 2025 agenda. They're here to deliver the insights that fuel startup growth and sharpen your edge. Don't miss the 20th anniversary of TechCrunch Disrupt, and a chance to learn from the top voices in tech — grab your ticket now and save up to $600+ before prices rise. Tech and VC heavyweights join the Disrupt 2025 agenda Netflix, ElevenLabs, Wayve, Sequoia Capital — just a few of the heavy hitters joining the Disrupt 2025 agenda. They're here to deliver the insights that fuel startup growth and sharpen your edge. Don't miss the 20th anniversary of TechCrunch Disrupt, and a chance to learn from the top voices in tech — grab your ticket now and save up to $675 before prices rise. San Francisco | REGISTER NOW Anthropic, along with OpenAI, xAI, and Google, has been granted up to $200 million by the Department of Defense to leverage AI for national security, but the AI firm clearly hopes to integrate into a broader array of government work, including science research and health services. Anthropic noted in its press release that Claude is already being used at Lawrence Livermore National Laboratory to accelerate scientific discoveries, and also by the District of Columbia Department of Health to help residents access health services in multiple languages. Anthropic says it is able to make such deployments because Claude 'meets the government's highest security standards.' Aside from being certified for FedRAMP High, customers can access Claude through their existing secure infrastructure via partnerships with AWS, Google Cloud, and Palantir, giving them more control over their data. Anthropic's multi-cloud access could give it an edge in the competition with OpenAI, whose current official FedRAMP High offering is tied to Azure Government Cloud only. While Azure is widely adopted in government, some government agencies and security teams might prioritize data sovereignty, infrastructure control, and the operational flexibility a multi-cloud strategy offers. OpenAI is, however, actively working to reduce its reliance on Azure so it can embrace a more diversified infrastructure approach.
Associated Press
10 hours ago
- Associated Press
Matrix-Game 2.0 Launches as a Powerful Open-Source Alternative to Genie 3
SINGAPORE, Aug. 12, 2025 /PRNewswire/ -- The SkyWork AI Technology Release Week officially kicked off on August 11. From August 11 to August 15, a new model will be unveiled each day, covering cutting-edge models for core multimodal AI scenarios. A week ago, DeepMind released a major update to its interactive world model—Genie 3—enabling real-time, long-sequence generation. This advancement has drawn significant attention to world models. However, Genie 3 was not open-sourced, leaving the community to speculate about its implementation. On August 12, Skywork unveiled an upgraded version of the self-developed Matrix series' interactive world model—Matrix-Game 2.0. It also delivers interactive, real-time, long-sequence generation in general scenarios. To drive progress in interactive world modeling, Matrix-Game 2.0 has been fully open-sourced, marking the industry's first open-source solution for real-time, long-sequence, interactive generation in general scenarios. Matrix-Game 2.0 open source addresses: Matrix-Game 2.0 achieves a breakthrough in real-time generation and long-sequence handling. Compared to its predecessor, the 2.0 version prioritizes low-latency, high-frame-rate performance for extended interactions, enabling stable 25 FPS continuous video generation across complex scenes. Its generation length scales to minute-long sequences, drastically improving temporal coherence and real-world usability. While delivering a significant boost in inference speed, Matrix-Game 2.0 maintains precise comprehension of physical laws and scene semantics. It enables users to freely explore, manipulate, and construct virtual environments in real time through simple instructions—yielding well-structured, detail-rich, and logically coherent virtual spaces. With these capabilities, Matrix-Game 2.0 not only breaks down the barriers between content generation and interaction but also unlocks new possibilities for cutting-edge applications such as virtual humans, game engines, and embodied AI. It provides a robust technical foundation for building a universal virtual world. Currently, Matrix-Game 2.0 boasts three core advantages: High-frame-rate, real-time long-sequence generation: The model supports fluid movement (forward/backward, left/right) and camera/view rotation. Users can intuitively control characters in the scene via simple commands. The system generates seamless footage in real time at 25 FPS, enabling minute-long interactive sequences in a single session. Character movements are lifelike, smooth, and precisely responsive. Cross-scenario generalization capability: The model demonstrates exceptional cross-domain adaptability. It is not only suitable for specific task scenarios but also supports simulations of diverse styles and environments—including urban, wilderness, and other spatial types, as well as realistic, oil-painting, and various visual styles. Enhanced physical consistency: The model demonstrates a deeper understanding of physical rules. Characters generated by the model exhibit physically plausible movements when navigating complex terrains such as steps and obstacles, which improves immersion and controllability. The open-source release of Matrix-Game for interactive video generation underscores Skywork's strategic foresight in AI development. This initiative will accelerate development across Skywork's multi-model AI ecosystem. Moving forward, Skywork remains committed to pioneering and open-sourcing advanced AI solutions. By collaborating with global developers and users, we aim to build next-generation platforms that accelerate the global advancement of AGI. View original content to download multimedia: SOURCE Skywork AI pte ltd
Business Insider
13 hours ago
- Business Insider
The CEO of Google DeepMind says one flaw is holding AI back from reaching full AGI
The one thing keeping AI from full AGI? Consistency. On an episode of the "Google for Developers" podcast published Tuesday, Google DeepMind CEO Demis Hassabis said that advanced models like Google's Gemini still stumble over problems most schoolkids could solve. "It shouldn't be that easy for the average person to just find a trivial flaw in the system," he said. He pointed to Gemini models enhanced with DeepThink — a reasoning-boosting technique — that can win gold medals at the International Mathematical Olympiad, the world's most prestigious math competition. But those same systems can "still make simple mistakes in high school maths," he said, calling them "uneven intelligences" or "jagged intelligences." "Some dimensions, they're really good; other dimensions, their weaknesses can be exposed quite easily," he added. Hassabis's position aligns with Google CEO Sundar Pichai, who has dubbed the current stage of development "AJI" — artificial jagged intelligence. Pichai used the term on an episode of Lex Fridman's podcast that aired in June to describe systems that excel in some areas but fail in others. Hassabis said solving AI's issues with inconsistency will take more than scaling up data and computing. "Some missing capabilities in reasoning and planning in memory" still need to be cracked, he added. He said the industry also needs better testing and "new, harder benchmarks" to determine precisely what the models excel at, and what they don't. Hassabis and Google did not respond to a request for comment from Business Insider. Big Tech hasn't cracked AGI Big Tech players like Google and OpenAI are working toward achieving AGI, a theoretical threshold where AI can reason like humans. Hassabis said in April that AGI will arrive "in the next five to 10 years." AI systems remain prone to hallucinations, misinformation, and basic errors. OpenAI CEO Sam Altman had a similar take ahead of the launch of GPT-5 last week. While calling his firm's model a significant advancement, he told reporters it still falls short of true AGI. "This is clearly a model that is generally intelligent, although I think in the way that most of us define AGI, we're still missing something quite important, or many things quite important," Altman said during a press call. Altman added that one of those missing elements is the model's ability to learn independently. "One big one is, you know, this is not a model that continuously learns as it's deployed from the new things it finds, which is something that to me feels like AGI. But the level of intelligence here, the level of capability, it feels like a huge improvement," he said.
