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AGI by 2028 - Shane Legg (DeepMind Founder)
3 segments available
Full Episode: https://youtu.be/Kc1atfJkiJU Apple Podcasts: https://podcasts.apple.com/us/podcast/shane-legg-deepmind-founder-2028-agi-new-architectures/id1516093381?i=1000632720307 Spotify: https://open.spotify.com/episode/0Ru2CtaJqsQ5mpA5dqHWAK?si=4AsglwIZQpqht7p9Wpc_CA Transcript: https://www.dwarkeshpatel.com/p/shane-legg Follow me on Twitter: https://twitter.com/dwarkesh_sp
Segments Timeline
Predicting AGI: The Early Insights
Shane Legg reflects on his 2009 blog post predicting human-level AI by 2025, with an expected value of 2028. He discusses the foundational beliefs he formed in 2001 after reading Ray Kurzweil's 'The Age of Spiritual Machines,' emphasizing the exponential growth of computational power and data. Legg explains how these trends create a strong incentive for developing scalable algorithms, which are crucial for advancing AI technology.
"speaking of the early years it's really interesting that in um 2009 you had a blog post where you say my modal expectation of when we get human level AI is 2025 expected value is 2028 and this is befo..."
The Feedback Loop of AI Development
In this segment, Shane Legg elaborates on the positive feedback loops between computational power, data growth, and algorithm scalability. He argues that as algorithms improve in harnessing data, the value of that data increases, leading to more investment in AI research. Legg predicts that by the 2020s, models will be trained on data far exceeding human experience, paving the way for significant advancements towards AGI.
"and that the quantity of data in the world would grow exponentially for a few decades and when you have exponentially increasing quantities of computation and data then the value of Highly scalable al..."
The 50% Chance of AGI by 2028
Shane Legg discusses his current assessment of the timeline for achieving AGI, stating there is a 50% chance it could happen by 2028. He acknowledges the unpredictability of research and the potential for unforeseen challenges that could delay progress. Legg's candid outlook reflects the complexities of AI development and the inherent uncertainties in predicting technological breakthroughs.
"AGI so that was that was my reasoning process and I think we're now at that first part I think we can start training models now with the scale of the data is beyond what a human can experience in life..."