Microsoft AI Hires DeepMind Co-Founder Mustafa Suleyman to Lead New Superintelligence Team

Mustafa Suleyman

Microsoft hired Mustafa Suleyman and Karen Simonyan, co-founders of high-profile AI startup Inflection AI, and several of their colleagues in March 2024. Suleyman, also a co-founder of DeepMind, which Google bought in 2014 to bolster its own AI efforts, heads Microsoft’s consumer AI unit, called Microsoft AI. In November last year, Microsoft said that the company is forming a team that will be tasked with performing advanced artificial intelligence research. Suleyman, CEO of the Microsoft AI group that includes Bing and the Copilot assistant, announced the formation of the MAI Superintelligence Team, and said in a blog post that he will be leading it. The term Superintelligence typically refers to machines deemed more intelligent than the smartest people. “We are doing this to solve real concrete problems and do it in such a way that it remains grounded and controllable,” Suleyman wrote. “We are not building an ill-defined and ethereal superintelligence; we are building a practical technology explicitly designed only to serve humanity,” he added. Announcement from Microsoft came months after Facebook parent Meta spent billions to hire talent for its new Meta Superintelligence Labs unit that’s working on research and products. Sharing a hiring post on Twitter recently, Suleyman stressed on the importance of culture at Microsoft. "Shaping our culture at Microsoft AI is one of the most important responsibilities I have. Keeping our team lean and talent dense is critical to our success. It's something I've thought very carefully about over the years," he wrote. He followed this with as many as eleven principles that he wrote Microsoft asks "everyone in the team to sign up to".

Microsoft AI CEO Mustafa Suleyman's full post

Shaping our culture at Microsoft AI is one of the most important responsibilities I have. Keeping our team lean and talent dense is critical to our success. It's something I've thought very carefully about over the years. I thought I'd share a few of the principles we ask everyone in the team to sign up to. Everything below flows from one conviction: a disciplined, evidence-based, careful methodology compounds faster than heroic and chaotic improvisation. We don't always get it right but this is what we strive for: - Scientific rigor above all else. We set hypotheses, rigorously ablate, and make data-driven decisions. - Constantly think simple. Simple methods scale best. No recipe changes unless deeply justified. - Know your data. Data is our lifeblood. No data black boxes. Every person is responsible for every token they add to the model. - Know your evals. No narratives without numbers. Production evals and trust internal metrics, over academic benchmarks. - Don't celebrate results prematurely. Maintain healthy skepticism. Check for reward hacking. Never cherry pick results. - Always document everything. Positive and negative results are equally critical. Label every plot and axes. Summarize hypotheses and conclusions. Don't use jargon. - Be precise and use neutral language. Describe situations accurately without unnecessary emotional charge. - Retrospectives drive everything. The culture and process flywheel is critical to our hill climbing machine. We constantly run Retros to iterate and improve. - We’re an IC-first team. Management is a service, not the goal. We’re here to empower, unblock and accelerate the exceptional work of our world class ICs. - User focus. We build our models for end users. Developing user empathy begins with us. We always strive to use our own models first so we can hill climb for our users. - Take ownership for execution. Report issues, provide logs for debugging. First try to fix things yourself. And see it right through to completion. The quality of our thinking determines the quality of our models.