Multidisciplinary research will be crucial in the next decade, combining expertise in areas like AI or machine learning with fields such as biology, chemistry, or mathematics.

There's significant potential for breakthroughs by merging different subject areas, and I've always aimed to be multidisciplinary in my own work, integrating neuroscience, machine learning, and computer science.

The convergence of reasoning models and multimodal models will lead to a new kind of computer interface that can reason, generate real-time video, and provide personalized experiences.

The diffusion of general-purpose tools, like PCs and AI assistants, transforms workflows and enhances collaboration across teams.

The exponential growth of technology is mind-boggling, and it fundamentally changes how we perceive advancements in computing and AI.

Computer use represents a significant advancement for AI, allowing models to adapt to tools rather than requiring developers to create custom environments for each task.

The transition to new computing architectures is ongoing, and we are in the early stages of blending different types of software for future applications.

The advancements in AI depend significantly on the amount of computing power we allocate and the timing of unpredictable breakthroughs.

The future of human-computer interaction will be more seamless, with advancements in AR and voice interfaces reducing the need for users to adapt to technology.