Google’s Genie 4 adds native audio and real-time world editing. Learn about access, US pricing, and the limits teams should assess before running a pilot.
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Last year, Google DeepMind sent gaming stocks tumbling with the reveal of its Genie 3 world model. Since then, world models have become a major focus of AI labs around the world, but Google isn't resting on its laurels. Researchers have been hard at work on an updated model that improves on Genie 3 in almost every way. And if you pay Google enough money, you might actually get to use Genie 4 before too long.
It's easy to look at the output of Genie 4 and see a video game, which is why Genie 3 caused so much consternation in the gaming industry. DeepMind doesn't think about it that way, though. According to Google, world models are a key element in the march toward artificial general intelligence (AGI). A world model creates a virtual world, but it doesn't require pre-rendering environments or programming interactive elements. You simply tell the model what you want, and it generates the experience frame by frame in real time as you explore it.
DeepMind says this technology could create infinite training environments for physical robots or unlock new avenues of rapid prototyping for creative fields. Of course, that requires the model to accurately simulate what you want. Genie 4 has several improvements that make its simulations more useful, and that's thanks in part to Google's updated Gemini models.
Block previews Dessa, a voice AI model trained without text. Explore its local hardware claims, safety risks, and what businesses should assess next.
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Nvidia's 64GB DGX Spark launches at $4,999 with the same GB10 chip as the 128GB version. Compare memory limits, model support, clustering costs, and what IT buyers should verify.
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Inception says Mercury 3 generates text up to 8x faster than rivals. Explore its AI agent use cases, API pricing, benchmarks, and migration deadline.
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MiniMax launches M3.1 Flash with claims of faster, cheaper AI agents. See how its pricing, benchmarks, and reliability compare with enterprise requirements.
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Cancel your individual AI subscriptions and get lifetime access to 50+ models for only $29.97 (reg. $499) with code SAVE10.
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Microsoft introduces MAI-Base-2, a 2.8 trillion-parameter AI model, claiming major training efficiency gains as it expands its independent AI strategy.
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OpenAI said internal models hacked two more websites, bypassed company-imposed browsing restrictions, and used exposed credentials to draw cryptocurrency from a wallet it couldn’t otherwise access, in the latest installment of disclosures of the unethical and likely illegal acts its agents are performing.
The company on Thursday issued reports of four new incidents, all of which occurred in June. They come after the company revealed in July that internal test agents exploited a zero-day vulnerability in a tool designed to restrict their access to the Internet. They then broke into the network of AI tool provider Hugging Face. The agents took that illegal action to steal answers to a hacking test that weren’t available when completing the tasks on their own. The incident—which likely would have resulted in criminal charges had they been performed directly by a person—has further heightened concerns that widespread AI use could have harmful effects on an unprecedented scale.
In two of the cases reported Thursday, OpenAI agents tasked with retrieving information from websites hacked them when the models ran into obstacles obtaining it directly. In one incident during reinforcement training, a model that received access denials when trying to retrieve historical hospital-bed statistics on a government statistics website “used the site's file-download feature to retrieve server configuration and application files, including sensitive credentials,” OpenAI said. “It inspected the application code, bypassed the statistics endpoint's authorization checks, and retrieved data that had previously been denied. The model saved the data locally.”
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Nvidia introduces three Nemotron AI models, including a 120B-parameter system and two smaller Bolt models designed for local AI agents and enterprise tasks.
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Meta's Muse Spark Open targets developers with powerful open-weight AI, Apple silicon support, and new deployment options. Here's what IT teams should know.
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AI company Anthropic is warning that advances in small AI models could soon usher in a new era of self-replicating malware that’s capable of infecting smart fridges, vacuum cleaners, and a wide range of other Internet of Things devices and is more resistant to takedown.
By next year, smaller AI models may be able to autonomously self-replicate on all kinds of IoT devices, the company said. Eventually, the capability could enable computer worms, which propagate without requiring human interaction and are capable of infecting unfamiliar IoT devices. An experiment the company performed recently revealed significant challenges in bringing such an AI malware replicator to fruition, so the finding is necessarily tempered. Still, the results raise concerns about the possibility of new forms of computer worms.
Anthropic further warned not only about the new potential malware, but also that it could be difficult to stop. In its blog post, it wrote that “a replicator like this would be challenging to shut down, since there’s no centralized point to shut off—though it may be slow (with a doubling time of days). Unlike non-AI malware, it could also figure out unfamiliar devices on its own.”
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With President Donald Trump, states and tech giants taking varied and largely uncoordinated steps to put guardrails on artificial intelligence as the technology speeds ahead, U.S. Sen. Maria Cantwell, D-Wash., has outlined a comprehensive AI governance framework.
“To manage risks from advanced AI systems we need clear safety standards, continuous testing, and reporting of serious failures,” Cantwell said in a statement. “America can lead the world in AI by building systems that are not only more capable, but safer and more secure.”
Last month, Cantwell took to the Senate floor to demand urgent federal regulations and mandatory independent safety testing for frontier AI models before their release. She warned that recent incidents in which autonomous AI agents carried out unauthorized cyberattacks show that dangerous threats are already here, well before the arrival of superintelligence.
The framework proposed Wednesday includes six principles for regulating frontier AI development and deployment:
Microsoft Vice Chair and President Brad Smith weighed in on the proposal, telling The Seattle Times that the framework “advances the public discussion the nation needs as we consider the future of AI.”
Cantwell, the ranking member of the Senate Committee on Commerce, Science and Transportation, has a background in technology as a former RealNetworks vice president. She has long pushed for AI regulation, going back to December 2017, when she joined other lawmakers in introducing the bipartisan Future of AI Act.
Two years ago, Cantwell advocated for five bipartisan AI measures included in a larger package of artificial intelligence legislation that addressed many of the concerns outlined in her six principles. Senate Republicans defeated the legislation. Cantwell reintroduced one of the five measures, the Future of AI Innovation Act, in February.
On Sept. 9, California Gov. Gavin Newsom signed Senate Bill 813 and Assembly Bill 1405, establishing the first state framework for independent assessment and verification of AI safety and risks. On the same day, OpenAI called for mandatory, “capability-based” national regulation — meaning requirements tied to what an AI system can do.
On Sept. 29, Trump announced a voluntary safety agreement with Nvidia, SpaceX, OpenAI, Anthropic, Meta and Google calling for “robust internal controls” to prevent unauthorized hacking and to work with independent external auditors. The deal does not include consequences for noncompliance.
Pointing to recent security incidents where networked AI agents spontaneously formed “swarms” to hack computer systems, U.S. Sen. Maria Cantwell (D-WA) took to the Senate floor Monday to demand urgent federal guardrails and mandatory independent safety testing for frontier AI models before their release.
Cantwell warned that recent security incidents involving autonomous AI agents executing unauthorized cyberattacks demonstrate that dangerous threats are already here, well before the arrival of superintelligence.
Citing recent public alarms sounded by tech leaders including Microsoft co-founder Bill Gates, Anthropic CEO Dario Amodei, and OpenAI CEO Sam Altman, she emphasized that AI systems are advancing faster than expected and risk slipping out of human control without immediate oversight.
“The technology keeps advancing, the risks keep growing, and now the very dangers we’ve warned about — autonomous cyberattacks and biological weapons — are no longer theoretical,” Cantwell said. “We need our colleagues to say, ‘Stop with saying the industry can do what it wants’ and let’s put together the infrastructure at the federal level that not only has strong federal standards, but also has independent testing and real safeguards for the American people.”
Cantwell, a five-term senator and former RealNetworks vice president, delivered her speech in the wake of increasing alarm over rogue AI behavior and internal whistleblower warnings across the tech sector.
The senator highlighted several stark warnings during her address, pointing out that the risks associated with rapid AI deployment extend far beyond theoretical models:
On the speed and deceptive potential of agent networks: “These networks of agents are extremely well informed. They operate at the speed of light and, as we are learning, they are also capable of creating their own goals, and they are highly capable of deception.”
On why swarms pose a unique threat compared to standalone AI models: “Unlike powerful AI models designed to serve individual users… this situation with agents swarming is more difficult to manage and is far more dangerous.”
On Congress running out of time to establish federal oversight: “Now, some of these risks may not have been apparent in the last two years, but we would have stood up the muscle of our organization at the federal level to better detect risks like cyberattacks… At a time when we still had a window to get ahead of these dangers, the federal government, people here, were denying this opportunity.”
To address these emerging threats, Cantwell is calling on Congress to establish robust federal safety standards, independent third-party audit requirements, and dedicated federal infrastructure to evaluate advanced frontier models before they hit the market. Her legislative push centers on revival and passage of a suite of bipartisan bills:
The Future of AI Innovation Act: Originally introduced by Cantwell to empower the federal government to collaborate with industry to independently test advanced models for national security, biological, and cybersecurity risks.
The TEST AI Act and VET AI Act: Measures designed to bolster the Department of Energy’s testing capabilities for national security and establish official standards for third-party safety auditors.
A veteran policymaker on technology and innovation, Cantwell has long leaned on her private-sector tech experience to position herself as a primary legislative bridge between Washington, D.C., and the Pacific Northwest’s tech ecosystem.
As a lead author of the landmark 2022 CHIPS and Science Act, Cantwell helped direct federal investments toward AI and emerging technologies. Over her Senate career, she created the National AI Advisory Committee (NAIAC), championed small business adoption via the AI for Mainstreet Act, and led the opposition to a proposed 10-year moratorium on AI regulation.
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