Satya Nadella – How Microsoft thinks about AGI

Satya Nadella, alongside Dylan Patel of SemiAnalysis, discusses Microsoft's strategic focus on building scalable AI infrastructure and the challenges of adapting to rapid technological advancements. Touring Microsoft's new Fairwater 2 data center, Nadella highlights the importance of expanding training capacity and the balance between training and monetization. He emphasizes Microsoft's commitment to innovation, leveraging partnerships like that with OpenAI, and adapting to global demands for data sovereignty. The conversation also touches on AI's potential to revolutionize industries and the geopolitical implications of AI development, stressing the need for trust in American technology.

• Microsoft is significantly expanding its data center capabilities with the Fairwater 2 data center, aiming for a 10x increase in training capacity every 18 to 24 months.
• The new data center is designed to handle large training jobs by aggregating flops across sites and will be used for various workloads, including training, data generation, and inference.
• The construction of Fairwater 4 and the AI WAN connection to Milwaukee will enable high-rate linking between data centers, enhancing model and data parallelism.

"We've tried to 10x the training capacity every 18 to 24 months."

• Microsoft is focused on rapidly increasing its data processing capabilities to accommodate future demands.

"The goal is to be able to aggregate these flops for a large training job and then put these things together across sites."

• The infrastructure is designed to support large-scale training jobs by combining resources from multiple locations.

• Technological revolutions, such as the Industrial Revolution, have historically sped up from discovery to economic impact.
• Many believe the current AI revolution could be the final major technological transition, with rapid market shifts and economic implications.
• Satya Nadella views AI as a cognitive amplifier and a guardian angel, emphasizing its utility in enhancing human capabilities.

"I start with the excitement that I also feel for the idea that maybe after the Industrial Revolution this is the biggest thing."

• Nadella acknowledges the potential of AI as a significant technological shift akin to the Industrial Revolution.

"Ultimately, what is its human utility? It is going to be a cognitive amplifier and a guardian angel."

• Nadella sees AI as a tool to enhance human abilities and provide support, similar to a guardian angel.

• Economic growth from technological advancements can take decades, as seen with the Industrial Revolution.
• The transition to AI involves changes in business models, especially for software-as-a-service companies, due to high costs of AI operations.
• Microsoft is adapting its business model to accommodate AI's higher cost structure, focusing on subscriptions, consumption, and other revenue streams.

"Even if the tech is diffusing fast this time around, for true economic growth to appear it has to diffuse to a point where the work, the work artifact, and the workflow has to change."

• Real economic growth requires widespread adoption and integration of new technologies into workflows.

"Software-as-a-service has incredibly low incremental cost per user... the COGS of AI is just so high, and that just completely breaks how these business models work."

• The high cost of AI operations challenges traditional SaaS business models, necessitating adaptation.

• Microsoft is leveraging its existing platforms like GitHub and VS Code to expand into AI-driven markets, focusing on coding assistants and AI agents.
• The company aims to maintain a competitive edge by innovating and expanding its market share in new, rapidly growing AI categories.
• Microsoft's strategy involves creating an ecosystem where multiple AI agents can operate, providing users with diverse tools and capabilities.

"The primitives of GitHub, starting with Git, to issues, to actions, these are powerful, lovely things because they kind of are all built around your repo."

• Microsoft is building on its existing platforms to create new opportunities and services in the AI space.

"We said Agent HQ was the conceptual thing that we said we're going to build out... I think that's going to be one of the biggest places of innovation."

• Microsoft's Agent HQ is a strategic initiative to innovate and offer a comprehensive suite of AI tools.

• The AI coding assistant market is rapidly expanding, with new competitors emerging and challenging Microsoft's dominance.
• Microsoft is focused on maintaining its leadership by innovating and leveraging its existing platforms to capture a significant share of the growing market.
• The company's approach is to ensure competitiveness while fostering an ecosystem where multiple players can coexist and thrive.

"We're going to have tough competition. That's your point, which is a great one. But I'm glad we have parlayed what we had into this and now we have to compete."

• Microsoft acknowledges the competitive landscape and is committed to innovating to maintain its position.

"GitHub will keep growing regardless of whose coding agent wins."

• Microsoft's GitHub platform is positioned to grow independently of individual successes in the AI coding assistant market.

• The conversation explores the evolving landscape of AI models, particularly focusing on the role of open-source models and the potential commoditization of AI models.
• The discussion highlights the importance of scaffolding and data liquidity in leveraging AI models effectively, suggesting that the real competitive advantage lies in integrating models with data and application infrastructure.
• The debate centers on whether the value lies in the models themselves or in the scaffolding that enables their use, with some arguing that models are becoming commodities while the scaffolding becomes the differentiator.

"In fact, I buy a subscription and the auto one will start picking and optimizing for what I am asking it to do. It could even be fully autonomous."

• This quote emphasizes the potential for AI to autonomously optimize tasks, highlighting the shift towards more intelligent, automated systems.

"There are enough and more checkpoints that are going to be available. That's the other thing. Structurally, I think there will always be an open-source model that will be fairly capable in the world that you could then use, as long as you have something that you can use that with, which is data and a scaffolding."

• It underscores the availability of open-source models and the necessity of having data and scaffolding to utilize these models effectively.

• The conversation discusses how AI is integrated into business applications, using Microsoft Office 365 and Excel Agent as examples.
• It highlights the shift from UI-level wrappers to deeper integration of AI models within business applications, enabling more sophisticated functionalities.
• The discussion touches on the potential for AI to transform traditional business logic by embedding cognitive capabilities into applications.

"Excel Agent is not a UI-level wrapper. It's actually a model that is in the middle tier."

• This quote illustrates the deeper integration of AI into business applications beyond simple user interface enhancements.

"You're taking the Excel business logic in the traditional sense and wrapping essentially a cognitive layer to it, using this model which knows how to use the tool."

• It highlights the transformation of business logic through the integration of cognitive AI capabilities.

• The conversation explores the potential future of AI agents, including fully autonomous agents that operate independently of human users.
• It discusses the shift from end-user tools to an infrastructure business model that supports AI agents, emphasizing the need for new infrastructure to support autonomous AI operations.
• The conversation also touches on the potential for AI to drive value through migration and optimization tasks, transforming traditional software ecosystems.

"In fact, all the stuff we built underneath M365 still is going to be very relevant."

• This quote emphasizes the ongoing relevance of existing infrastructure in supporting the future of AI agents.

"The way to frame it—at least the way I currently think about it and I’d like to hear your view—is that these model companies are all building environments to train their models to use Excel or Amazon shopping or whatever it is, book flights."

• It highlights the focus on training AI models to perform practical tasks, driving value through automation and optimization.

• The conversation discusses Microsoft's strategy in the AI space, including its partnership with OpenAI and efforts to build its own world-class AI models.
• It emphasizes the importance of leveraging existing AI models while also investing in new research and development to create leading AI capabilities.
• The discussion highlights the need for a strong talent pool and infrastructure to support AI model development and deployment.

"We have access to OpenAI models for seven more years, which we will innovate on top of."

• This quote underscores Microsoft's strategic partnership with OpenAI and its plans to build upon existing models.

"We're going to build a world-class team. In fact, later this week even, Mustafa will publish something with a little more clarity on what our lab is going to go do."

• It indicates Microsoft's commitment to assembling a top-tier team to drive AI innovation and development.

• The distinction between training and inference in AI models is becoming less significant.
• Future AI models are expected to achieve human-level intelligence with the capability to learn continuously, akin to human experience accumulation over time.
• Continuous learning models will create an exponential feedback loop, potentially leading to an intelligence explosion.

"If you think about your last 30 years, what makes Satya tokens so valuable? It's the last 30 years of wisdom and experience you've gained in Microsoft."

• This quote highlights the importance of continuous learning and experience accumulation in enhancing value, similar to how future AI models might operate.

"We will eventually have models, if they get to human level, which will have this ability to continuously learn on the job."

• Future AI models will likely have the ability to learn continuously, enhancing their utility and adaptability.

• Despite the potential for a dominant AI model, multiple models are currently being deployed for various use cases, similar to different types of databases.
• Network effects and data liquidity will influence the success of AI models, but it won't be uniform across all domains, geographies, or segments.

"There is not one model that is getting deployed broadly. There are multiple models that are getting deployed."

• This quote underscores the current diversity in AI model deployment, with no single model dominating the market entirely.

"I think that there are going to be some network effects of continual learning—I call it data liquidity—that any one model has."

• Data liquidity and network effects will play a role in the success of AI models, but their impact will vary across different areas.

• Building infrastructure optimized for a single model can be risky if that model becomes outdated.
• Infrastructure should support multiple families and lineages of models to ensure flexibility and adaptability.

"You kind of need to build an infrastructure that's capable of supporting multiple families and lineages of models."

• Infrastructure should be flexible to support various models, ensuring long-term viability and adaptability.

"If you're serious about the hyperscale business, you've got to be serious about that."

• This quote emphasizes the importance of building adaptable infrastructure to succeed in the hyperscale business.

• The industry structure will force companies to specialize, with companies like Microsoft competing based on merit at each layer.
• A vertically integrated approach is not feasible; companies must enable an ecosystem where others can build on top of their models.

"Therefore the industry structure is such that it will really force people to specialize."

• Specialization will be necessary for companies to succeed in the evolving industry landscape.

"You won't have an API business and that, by definition, will mean you'll never be a platform company that's successfully deployed everywhere."

• Companies must focus on enabling an ecosystem to become successful platform companies.

• Microsoft paused certain infrastructure expansion projects to focus on building a flexible and balanced hyperscale business.
• The decision was influenced by the need to support various models and ensure monetization aligns with infrastructure investment.

"One of the key decisions we made was that if we're going to build out Azure to be fantastic for all stages of AI—from training to mid-training to data gen to inference—we just need fungibility of the fleet."

• This quote highlights the importance of infrastructure flexibility to support diverse AI stages and models.

"The rate of monetization is what will then allow us to keep funding."

• Ensuring that infrastructure investments align with monetization is crucial for sustainable growth.

• The location of data centers and the capacity they provide must be strategically planned to meet regulatory needs and demand.
• Microsoft aims to build capacity globally, considering factors like data sovereignty and workload diversity.

"The topology as we build out will have to evolve. One, for tokens per dollar per watt. What are the economics? Overlay that with, what is the usage pattern?"

• The quote emphasizes the need to consider economic and usage patterns in planning data center topology.

"We've got to build all over the world. First of all, stateside capacity is super important, and we want to build everything."

• Building capacity globally is essential to meet diverse regulatory and demand needs.

• Microsoft is open to leasing capacity and collaborating with neoclouds to meet demand and enhance its marketplace.
• Partnerships with companies like Iris Energy, Nebius, and Lambda Labs reflect this strategic approach.

"We will take leases, we will take build-to-suit, we'll even take GPUs-as-a-service where we don't have capacity but we need capacity and someone else has that."

• Microsoft is leveraging partnerships to enhance capacity and meet demand efficiently.

"I would even sort of welcome every neocloud to just be part of our marketplace."

• Collaboration with neoclouds is viewed as beneficial for expanding Microsoft's marketplace and meeting customer needs.

• Microsoft's internal chip development is focused on overall TCO and scaling, rather than competing directly with Nvidia's previous generation.
• The company has experience in building its own silicon, as demonstrated by its work with Intel, AMD, and Cobalt.

"The thing that is the biggest competitor for any new accelerator is kind of even the previous generation of Nvidia."

• Internal chip development is focused on achieving competitive total cost of ownership rather than directly competing with established players.

"We have good existence proof of, at least in core compute, how to build your own silicon."

• Microsoft has experience and success in developing its own silicon, which informs its current strategy.

• Companies like Google and Amazon are investing heavily in Nvidia due to its innovation and general-purpose utility for AI models.
• The integration of custom silicon with AI models is essential for companies to maintain control and scalability.
• Microsoft is leveraging its access to OpenAI's program to enhance its AI capabilities and infrastructure.

"The way we are going to do it is to have a close loop between our own MAI models and our silicon, because I feel like that's what gives you the birthright to do your own silicon."

• This quote highlights the strategic approach of integrating AI models with custom silicon to maintain control and innovate efficiently.

• Microsoft has exclusive rights to certain API calls from OpenAI, which are essential for their strategic operations.
• The partnership allows flexibility for OpenAI while ensuring Microsoft retains exclusivity in certain areas.

"The strategic decision we made, and also accommodating for the flexibility OpenAI needed in order to be able to procure compute for… Essentially think of OpenAI having a PaaS business and a SaaS business."

• This quote explains the dual nature of OpenAI's business model and Microsoft's strategic role in it.

• Microsoft is transitioning from a software-centric to an industrial business with significant capital expenditure.
• The company's growth in capex reflects its adaptation to a capital and knowledge-intensive business model.

"I describe it as we are now a capital-intensive business and a knowledge-intensive business."

• This quote underscores Microsoft's shift in business strategy to accommodate the growing demands of AI and infrastructure.

• The geopolitical landscape is influencing AI deployment, with countries seeking sovereignty over AI technologies.
• Microsoft is navigating these challenges by building trust and ensuring compliance with local regulations.

"The key, key priority for the US tech sector and the US government is to ensure that we not only do leading innovative work, but that we also collectively build trust around the world on our tech stack."

• This quote emphasizes the importance of trust and compliance in the global expansion of AI technologies.

• Countries are pursuing sovereign AI to mitigate risks associated with concentration and dependency on single models.
• Open source and multiple models are seen as solutions to ensure continuity and reduce concentration risk.

"Concentration risk and sovereignty, which is really agency, those are the two things that will drive the market structure."

• This quote highlights the driving factors behind the demand for sovereign AI and diverse model availability.

• The need for resilience in global supply chains is recognized, with countries aiming for self-sufficiency in critical sectors.
• Companies like Microsoft must respect and adapt to the policy interests of different nations.

"But there's such a thing called resilience, and we want resilience. So therefore that feature will get built."

• This quote reflects the shift towards building resilient supply chains and the role of multinational companies in this process.

• Trust in American technology and institutions is crucial for maintaining a competitive edge globally.
• The ability to be a reliable long-term supplier may be more important than just technological capabilities.

"It is, 'can I trust you, the company, can I trust you, your country, and its institutions to be a long-term supplier?' That may be the thing that wins the world."

• This quote highlights the significance of trust in American tech companies in the face of global competition.