The Near Future of AI [Entire Talk] - Andrew Ng (AI Fund)

The seminar begins with an introduction by Ivy Balani, a lecturer at Stanford and director of Alchemist, an accelerator for enterprise startups. She welcomes Andrew, a renowned thought leader in AI, and provides a detailed account of his impressive background. Andrew's journey includes three bachelor's degrees from Carnegie Mellon, a master's and PhD in electrical engineering and computer science from MIT and Berkeley respectively, with a focus on artificial intelligence and reinforcement learning. He is known for co-founding Google Brain and being a former Chief Scientist at Baidu, where he built a substantial AI group. Andrew's dedication to education is highlighted by his role as an associate professor and director of the Stanford AI Lab, and his online AI education work, which has reached over 7 million people. His achievements also include being listed as one of Time magazine's 100 most influential people in 2013 and his current roles as managing director and partner at the AI Fund and founder of deeplearning.ai.

Andrew discusses the revolutionary impact of prompting in AI application development, drawing a comparison between AI and electricity as general-purpose technologies with diverse applications. He explains the traditional approach of using supervised learning to build AI systems and the lengthy timeline involved. However, with prompting, the development timeline has drastically shortened, allowing systems to be deployed in hours or days. Andrew expresses his excitement about the use of large language models as a developer tool, which significantly lowers the barrier to building applications and opens up new opportunities for startups. He shares a personal example of building an AI system with minimal code, emphasizing the rapid development times and the importance of responsible AI practices.

Andrew explores the opportunities in AI technologies, highlighting the value of different AI tools today. He explains that supervised learning has been effective for about a decade and has immense value, with millions of developers working on it. He predicts that generative AI, a relatively new entrance, will grow significantly in the next three years. Andrew emphasizes the importance of identifying concrete use cases for these technologies and the potential for growth in the application layer of AI. He also discusses the potential for long-term valuable businesses built on top of generative AI, comparing it to the early days of smartphones and the subsequent development of major apps like Uber and Airbnb.

Andrew delves into the AI stack, discussing the various layers from hardware to application development. He notes that while the hardware layer is valuable, it is capital-intensive and not his area of focus. He sees potential in the developer tooling layer, but only when there's a technological advantage. Andrew believes the application layer is the most valuable, with less competition and more opportunities for revenue generation. He shares an example of a startup applying AI to romantic relationship coaching, emphasizing the importance of combining AI expertise with domain-specific knowledge. Andrew also discusses his process for building startups, starting with many ideas and validating them through technical feasibility and market need, leading to the creation of successful ventures like Bearing AI, which uses AI for smart routing of ocean vessels.

Andrew offers advice to students interested in AI, emphasizing the importance of taking classes to master foundational skills. He suggests that coursework is a more efficient way to learn than jumping straight into project work. Once students have a strong grasp of AI technology, he encourages them to find exciting use cases across different disciplines. Andrew also stresses the importance of learning to code, as it increases the ability to accomplish tasks and leverage data. He concludes by emphasizing responsible AI and the importance of working on projects that move humanity forward, even if it means killing financially sound projects based on ethical grounds.

Andrew addresses concerns about the existential threat of AI, expressing his belief that AI does not pose such a threat to humanity. He compares AI to other powerful yet controllable entities like corporations and nation-states. Andrew argues that while AI can have significant impacts, humanity has the experience to manage and control these technologies responsibly. He also discusses the potential negative impact of the AI extinction narrative on students considering careers in AI, and the importance of responsible AI practices. Andrew shares his views on the next big technology shift in AI, predicting advancements in visual AI and the rise of edge AI, where applications run on local devices like laptops and cell phones. He also touches on the potential of reinforcement learning models in society and startups, despite current challenges in data availability.

Andrew discusses the concentration of AI talent in the San Francisco Bay Area and the rapid global development of skills in the application layer. He sees local opportunities for businesses to play in areas where their geography is strong. Andrew also addresses the issue of human dependence on technology, predicting that this dependence will continue to grow. He expresses uncertainty about the concept of technological singularity, viewing it as an exciting but vague science fiction notion. Andrew also shares his thoughts on the potential for AI to become conscious, acknowledging it as an important philosophical question but one that lacks a clear definition. He concludes by discussing the process of generating ideas for AI applications at the AI fund, emphasizing the value of working with subject matter experts who deeply understand their domain.