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.

GeekWire is profiling over the next few weeks some of the people and teams that are shaping the evolution of Microsoft in what we’re calling its “Microsoft 2.5” era.

From AI Frontier Lab to Frontier Ecosystem: Microsoft got a foothold in AI thanks largely to its partnership with OpenAI. But that’s not the way it is planning to continue growing its AI business.

Inside Microsoft AI (MAI), the Microsoft Superintelligence team is focused almost entirely on building its own frontier-level models. That team already has developed a handful of home-grown offerings, including MAI-Code-Flash for writing code faster; MAI-Cyber-Flash, a cybersecurity model; and MAI-Image, a model for creating images.

The head of the Superintelligence team is Ali Farhadi, corporate vice president of AI. Farhadi, who joined Microsoft five months ago, is also a professor at the University of Washington, where he has worked for nearly 15 years. He was previously CEO of the Allen Institute for AI (Ai2) and before that was an AI and machine learning leader at Apple for more than three years, after it acquired his startup, Xnor.ai.

When he joined Microsoft, Farhadi said in a LinkedIn post that he believed “Microsoft has all the pieces to win in this AI race: data, search, coding, infrastructure, agents, software and the world’s biggest Fortune 500 companies taking dependencies on Microsoft every day.”

Farhadi elaborated on that in an interview with GeekWire this week. AI is shifting from a “Frontier Lab” era to a “Frontier Ecosystem” era, he said. It’s no longer just about training models; it’s about integrating the models with enterprise data, platforms, distribution systems and customers in a trusted way.

The next battlegrounds in AI will be around cost, reliability, specialization, and deployment at scale, rather than simply building larger models that beat others in benchmark scores, he said.

“If you look around, there are not that many places to have all these missing pieces together at scale, especially if you add the element of trust to it,” Farhadi said.

Cutting through the AI noise: Farhadi said his management philosophy is grounded in the importance of personal relationships, which are especially key in big organizations. People need to understand your rationale and to trust you can deliver on what you’re tasked to do, he said — an approach that has served him inside both Microsoft and Apple.

Staying on top of the flow of information while filtering out the AI noise makes prioritizing crucial. The team has “a long list of things that we believe we should be doing,” he said, but much of it stays on the back burner to maintain a “laser focus on delivering on the main mission.”

The priority is building high-quality models, both generalist and domain-specific. On the domain-specific front, Microsoft is working with the Mayo Clinic on a healthcare-specific model based on Mayo’s own clinical data, as well as Microsoft’s cybersecurity and coding models.

The thinking: For a lot of enterprise work, a narrower model beats a bigger one.

“If you can do something at [the same] quality or better quality at a fraction of a cost, it’s just a no-brainer. And having a way to specialize to domains, to industries, to enterprises is one way,” he said.

Microsoft execs have referred to this approach as a “hill-climbing machine,” meaning the ability of a model to scale and continuously improve within a specific domain. Microsoft is coupling the hill-climbing with “frontier tuning,” like it is doing with the Mayo Clinic. Frontier tuning includes customizing frontier models; keeping proprietary data private, preserving institutional know-how; and avoiding leaking intellectual property (IP) into shared models.

“We all thought that IP is your data,” Farhadi said. “But we learned that IP is also how you work.” And that’s why safeguarding these elements is so crucial.

Open all the things? Farhadi led an expansion of open-source AI development at Ai2, the Seattle-based institute founded in 2014 by the late Microsoft co-founder Paul Allen. While Microsoft has contributed to the open-source community on various fronts, including AI tooling, it hasn’t open-sourced its frontier models.

Farhadi said he personally remains “a big advocate of open source,” but noted that the industry has changed since his Ai2 days as there are now more credible Western open-source models and businesses forming around them.

He didn’t rule out Microsoft doing something in open-source models, or the somewhat less-open “open weights” area, but there’s seemingly nothing happening on that front in the near term.

In the coming months and beyond, the focus of Farhadi’s team is helping Microsoft turn into a Frontier Ecosystem by building cutting-edge AI capabilities; helping enterprises create their own tuned versions of them; continuously improving models; and making sure customers keep control of their own destinies and data.

Success for Microsoft’s Superintelligence team has nothing to do with the idea of Artificial General Intelligence (AGI) which OpenAI, Anthropic and others have positioned as their ultimate goal over the years. In fact, when I asked Farhadi about AGI, he said, “I don’t understand what that means.”

Don’t worry, Ali. You’re not the only one.