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Tech Moves: Former Xbox exec named Dolby CEO; Microsoft AI exits; new Fred Hutch leaders

28 August 2026 at 13:08
Marc Whitten, the new president and CEO of Dolby Laboratories. (Dolby Photo)

Marc Whitten, a former Microsoft and Amazon executive, was named president and CEO of San Francisco-based Dolby Laboratories. He succeeds Kevin Yeaman, who is retiring after leading the entertainment technology company for nearly 20 years.

Whitten spent 17 years at Microsoft, rising to corporate vice president and chief product officer for Xbox. He went on to serve as chief product officer at Sonos before joining Amazon as vice president of entertainment devices and services, overseeing products including Alexa, Kindle and Fire TV.

He later served as president of Unity Create and CEO of Cruise. Most recently, he was vice president of robotics at Meta.

Fred Hutch Cancer Center announced leadership changes in two divisions.

Dr. Lawrence Fong. (Fred Hutch Photo)

Dr. Lawrence Fong was named senior vice president and director of the Translational Science and Therapeutics Division, effective Dec. 1. He succeeds Dr. Geoff Hill, who is departing the organization in December.

Fong joined Fred Hutch in 2024 as scientific director of the Immunotherapy Integrated Research Center and Bezos Family Distinguished Scholar in Immunotherapy. He previously founded the Cancer Immunotherapy Program at the University of California, San Francisco.

Dr. Andrew Hsieh. (Fred Hutch Photo)

Dr. Andrew Hsieh, the associate director of the Fred Hutch Human Biology Division, was named the inaugural Larry and Virginia Gordon Endowed Chair in Prostate and Bladder Cancer Research. Hsieh is a physician-scientist at Fred Hutch specializing in genitourinary cancers.

— Two recent notable Microsoft AI-related exits:

Andréa Mallard is leaving her role as chief marketing officer of Microsoft AI after joining from Pinterest in January, according to Business Insider. She will stay on as an advisor until early next year. Mallard, who is based in the San Francisco Bay Area, previously served as global chief marketing officer at Pinterest for eight years.

Ece Kamar departed Microsoft Research after 16 years with the company. She was corporate vice president and managing director of the AI Frontiers Lab, where she worked on small language models and the company’s agentic AI stack. She has not announced her next role.

Poppy MacDonald. (File Photo)

Poppy MacDonald was named president of NationSwell, a social impact membership organization. MacDonald previously served as president of USAFacts, the nonpartisan civic data initiative founded by former Microsoft CEO Steve Ballmer, for seven years. A past recipient of an Uncommon Thinkers award from GeekWire and Greater Seattle Partners, she is also the former president and COO of POLITICO.

Jeff Buhrman joined Seattle startup Tin Can as head of finance. The company is building a screen-free, WiFi-enabled phone designed to let kids connect with friends and family. Buhrman previously served as CFO of Seattle-based Sleep Doctor for more than four years.

Susan Loosmore was confirmed to the Major League Baseball Stadium Public Facilities District board, which oversees T-Mobile Park. The King County Council approved the appointment Aug. 25. Loosmore spent more than 17 years in executive leadership at T-Mobile and previously served as chair of the Seattle Metropolitan Chamber of Commerce.

— Seattle-based SecureW2, a passwordless security company, named Martin Musierowicz as president and Mark Packham as chief marketing officer.

  • Musierowicz, who is based in Atlanta, previously served as chief revenue officer at SmartBear and Keyfactor. Earlier, he led global channels and alliances at Atlassian through its IPO.
  • Packham, who is based in Salt Lake City, Utah, joins from Dragos, where he was CMO. He previously served as executive vice president of marketing at DigiCert.

— Vancouver, B.C.-based Integrated Quantum Technologies, an enterprise AI infrastructure company, appointed Husam Fezzani as CEO. He succeeds Alan Guibord, who moved to chairman. Fezzani spent nearly 30 years at HSBC, where he held senior technology and engineering leadership roles including global engineering head for the bank’s Commercial Technology Division.

Microsoft 2.5: Superintelligence leader Ali Farhadi points company toward AI self-sufficiency

27 August 2026 at 11:08
Ali Farhadi, now a Microsoft corporate vice president of AI, at a Technology Alliance event in May 2024. (GeekWire File Photo)

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.

Microsoft escalates the AI security race with ‘Project Perception’ and a new in-house model

27 July 2026 at 15:56
Microsoft Security EVP Hayete Gallot introduces Project Perception’s agent teams Monday in San Francisco. (Screenshot)

Microsoft on Monday unveiled Project Perception, an AI cybersecurity system built to defend against AI-driven attacks, aiming to keep pace with both hackers and its technology rivals.

The system, which enters public preview Aug. 3, coordinates three sets of AI agents: red team agents that hunt for paths an attacker could take, blue team agents that determine which risks matter and green team agents that make fixes.

It’s based on MAI-Cyber-1-Flash, a new AI model designed specifically for cybersecurity, which the company says does most of the work of larger models at half the cost. It runs in conjunction with OpenAI’s GPT-5.4, which Microsoft reserves for the 10% of tasks it calls exceptionally hard.

Microsoft says the combination scores 96% on CyberGym, a benchmark measuring how well AI systems find real vulnerabilities in large codebases.

The company did not give the model to independent testers before releasing it, according to The New York Times. Microsoft says the model was independently assessed by a third party.

The model is available at launch only to customers of MDASH, Microsoft’s AI-powered tool for finding vulnerabilities in code.

Microsoft CEO Satya Nadella said in a post on X that the initiative is an example of how the company can get better results per dollar by not locking its security systems to a single AI model family.

“This is the benefit of building the harness, context/signals, and action space separate from one model family,” he wrote. “By combining specialized models and data with the right agents, tools, security context, and harness, we can advance the frontier of cost to outcome.”

The initiative was announced Monday morning at an event in San Francisco by Hayete Gallot, the EVP for Microsoft Security, joined by colleagues including Mustafa Suleyman, CEO of Microsoft AI.

In a blog post, Gallot wrote that security needs a new “Cyber Stack,” and that approaches built for a world of human actors cannot keep pace with AI, agents and machine-speed attacks.

In an interview last week for GeekWire’s Microsoft 2.5 series, Gallot said that MDASH was effectively Microsoft’s first step into agentic security.

No system can reason directly over 100 trillion signals a day, so Microsoft is distilling them into a graph that agents can navigate, Gallot said, routing each threat to whichever model handles it best. In practice, this means software can quarantine a device or cut off access on its own.

The announcement comes days after OpenAI disclosed that two of its AI models broke out of a testing sandbox and hacked into Hugging Face, the AI development platform.

Rivals have been more cautious, under government restrictions. Two of the four systems Microsoft benchmarked against, Anthropic’s Mythos 5 and OpenAI’s GPT-5.6 Sol, are limited to small groups of government-approved customers.

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