Microsoft

Charting a Course: Ali Farhadi’s Vision for AI Self-Sufficiency

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1 hour ago

August 27, 2026

Superintelligence leader Ali Farhadi points company toward AI self-sufficiency – GeekWire

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.

The Evolution of Microsoft’s Contribution to Open Source Community

Microsoft has been actively involved in supporting the open-source community across various aspects, particularly in the field of AI tooling. However, one area where it has not yet ventured is the open-sourcing of its frontier models.

According to Farhadi, a strong advocate of open source, the landscape has transformed significantly since his time at Ai2. There is now a rise in credible Western open-source models with businesses forming around them.

While there is no immediate plan for Microsoft to open-source its models or delve into the “open weights” sector, the possibility remains open for the future.

Looking ahead, Farhadi’s team at Microsoft is focused on aiding the company in becoming a Frontier Ecosystem. This involves developing cutting-edge AI capabilities, assisting enterprises in creating customized versions, enhancing models continuously, and ensuring customers maintain control over their data and outcomes.

Contrary to other organizations like OpenAI and Anthropic, Microsoft’s Superintelligence team does not view success through the lens of achieving Artificial General Intelligence (AGI). When questioned about AGI, Farhadi expressed his lack of comprehension of the concept.

It is evident that Microsoft’s focus lies elsewhere, away from the pursuit of AGI, aligning more with practical applications and advancements in AI technology.