With industry dominating large-scale compute, academia's function is no longer to train the biggest models. Instead, its value lies in pursuing unconventional, high-risk research in areas like new algorithms, architectures, and theoretical underpinnings that commercial labs, focused on scaling, might overlook.

Stanford's business school uses an improv game where students rapidly list items in a category, prioritizing speed over accuracy. This exercise demonstrates that generating a high volume of ideas, even imperfect ones, is the most effective path to finding the best idea, as the best concepts often emerge late in the process.

Corporate creativity follows a bell curve. Early-stage companies and those facing catastrophic failure (the tails) are forced to innovate. Most established companies exist in the middle, where repeating proven playbooks and playing it safe stifles true risk-taking.

Conventional innovation starts with a well-defined problem. Afeyan argues this is limiting. A more powerful approach is to search for new value pools by exploring problems and potential solutions in parallel, allowing for unexpected discoveries that problem-first thinking would miss.

With industry dominating large-scale model training, academic labs can no longer compete on compute. Their new strategic advantage lies in pursuing unconventional, high-risk ideas, new algorithms, and theoretical underpinnings that large commercial labs might overlook.

Breakthrough creativity, like that behind Disney's *Frozen* or behavioral economics, is often "innovation brokerage." It doesn't come from a blank slate but from combining established concepts from disparate fields—like mixing psychology with economics—to create something new and powerful.

Frances Arnold, an engineer by training, reframed biological evolution as a powerful optimization algorithm. Instead of a purely biological concept, she saw it as a process for iterative design that could be harnessed in the lab to build new enzymes far more effectively than traditional methods.

The GSB enhances the traditional case study method by first having students analyze a case, like DoorDash. Then, the actual protagonist—the founder and key investors—are brought into the classroom. This allows students to directly challenge their assumptions and engage with the real-world complexities behind the decisions.

The GSB's enduring value lies in its resistance to offering 'one size fits all war stories.' Instead, it focuses on teaching analytical instrumentation and fundamental social science. This approach equips leaders to solve novel future problems, like harnessing AI, rather than just applying solutions from the past.