2024 Congressional Bootcamp: Day 1 Agenda

Stanford HAI staff will welcome congressional staffers to campus and provide an overview of why the boot camp was created and what Stanford HAI hopes for participants to gain.

This session will cover the basic concepts of AI, including compute power, neural networks, narrow vs. general AI, gradient descent, and more. It will also provide a bird’s-eye view of the AI landscape, covering different AI techniques such as deep learning, computer vision, natural language processing, and supervised and unsupervised learning. Participants will walk away with a greater understanding of the primary aspects of AI and be better prepared for the boot camp.

The consequences of deploying robust AI and decision-making technologies in safety-critical systems such as driverless vehicles and autonomous aircraft are enormous. Challenges for AI developers range from biased inputs, constantly evolving conditions, and explainability issues, among others. This session will discuss the obstacles developers face as well as the difficult—and often politically fraught—decisions they make around operational efficiency and how they define acceptable risk parameters.

15-minute break 

Contemporary AI technologies run on data, but AI developers face significant obstacles in acquiring and cleaning data. In addition, developers must do their best to ensure data’s inherent biases (and their non-obvious proxies) are accounted for in their AI systems. Moreover, different social values around privacy, data ownership, and data creation impact what AI technologies are possible. This session will dive into how the data policies developed today will shape the technologies of tomorrow.

This session highlights how computational power directly influences the capabilities and efficiency of AI systems, impacting everything from machine learning model training times to the sophistication of AI applications. Policymakers are introduced to key concepts such as the high-performance computing chips, trade-offs between computational demands and energy consumption, and the strategic importance of compute in national competitiveness in AI.

15-minute break 

Recently, a paradigm for building AI systems has emerged: train one model on a huge amount of data and adapt it to numerous applications. We have deemed such a model a foundation model (such as ChatGPT). This session unpacks how foundation models were created and deployed, the requirements to build one, expected and unexpected consequences of these models, and other hot topics surrounding the use of large AI models. 

The rapid advancements in AI in recent years have shocked the world. From models generating realistic images from scratch to ambient technologies that enhance the human condition, the possibilities of what AI can do for humanity are endless. Understanding today’s cutting-edge AI will help steer tomorrow’s innovation. This session will dive into what is on the horizon of AI advancements and how these technologies can be leveraged to benefit society.