Renowned AI pioneer Fei-Fei Li, known for her groundbreaking work in artificial intelligence, has recently emphasized the critical need for enhanced public investment and a robust “moonshot” mentality to drive progress in the field. In a recent meeting with President Joe Biden, Li stressed the urgency of aggressive funding for AI research and public projects, citing the current inadequacy of resources in the United States to keep pace with the rapid advancements in AI technology, as reported by Bloomberg.
Li, who serves as a computer science professor and co-directs the human-centered AI program at Stanford University, underscored the indispensable role of the public sector in shaping the future of AI. Despite the substantial resources available to private sector entities, Li highlighted the challenges faced by universities and public institutions in securing the necessary funding for AI research. Notably, she highlighted that no university in the U.S. possesses the capability to train models equivalent to ChatGPT, emphasizing the dearth of computational resources and data, with an increasing proportion of talented individuals gravitating toward private sector opportunities.
Financial discrepancies and implications for AI advancements
Highlighting the significant funding gap between private and public AI initiatives, Li’s stance aligns with the earlier statement by OpenAI’s co-founder and CEO Sam Altman, who estimated the development cost of the GPT-4 model to exceed $100 million. The discrepancy in financial resources underscores Li’s assertion and the critical need for bolstered financial support for public AI endeavors.
President Biden’s response and Li’s Stance on AGI risks
When asked about President Biden’s response during the meeting, Li revealed that while the President did not immediately issue an executive order, he expressed thoughtful consideration on the matter. Furthermore, addressing concerns regarding the potential risks associated with Artificial General Intelligence (AGI), Li emphasized the significance of prioritizing immediate safety issues over speculation on distant existential threats. While acknowledging the profound philosophical and neurological inquiries raised by the study of AI capabilities, Li advocated for a focus on current challenges and opportunities within the field.
Drawing a relatable analogy, Li emphasized the importance of addressing immediate safety concerns rather than delving into hypothetical scenarios. Likening the approach to supervising a young child on a playground, she highlighted the significance of mitigating immediate risks instead of delving into far-reaching possibilities. Her analogy serves to underscore the importance of addressing current challenges within AI research and development.
With Fei-Fei Li’s passionate advocacy for increased funding and public investment in AI research, the conversation surrounding the future of AI in the United States is poised to gain momentum, emphasizing the critical need for collaborative efforts between the public and private sectors in advancing this transformative field.
