Jia  shares the kinds of AI courses she teaches at Stanford, how students are receiving machine learning education, and the impact of AI agents, as well as understanding technical boundaries, being realistic about the limitations of AI agents, and the importance of interdisciplinary collaboration. We also delve into how Jia prioritizes latency at LiveX before finding out how machine learning has changed the way people interact with agents; both human and AI. Key Points From This Episode:The AI courses that Jia teaches at Stanford. Jia’s perspective on the future of AI. What the potential impact of AI agents is. The importance of understanding technical boundaries. Why interdisciplinary collaboration is imperative. How Jia is empowering other businesses through LiveX AI. Why she prioritizes latency and believes that it’s crucial. How AI has changed people’s expectations and level of courtesy.A glimpse into Jia’s vision for the future of AI agents. Why she is not satisfied with the multi-model AI models out there. Challenges associated with data in multi-model machine learning. Quotes:“[The field of AI] is advancing so fast every day.” — Jia Li [0:03:05]“It is very important to have more sharing and collaboration within the [AI field].” — Jia Li [0:12:40]“Having an efficient algorithm [and] having efficient hardware and software optimization is really valuable.” — Jia Li [0:14:42]Links Mentioned in Today’s Episode:Jia Li on LinkedInLiveX AIHow AI HappensSama