Shaping AI’s Future | Pedro Domingos
- Pedro Domingos is a Professor Emeritus of computer science and engineering at the University of Washington.
- He is a researcher in machine learning known for the Markov logic Network enabling uncertain inference.
Podcast
Overview
In an exclusive conversation, AI visionary Pedro shares insights into his groundbreaking contributions, including the unification of AI paradigms and the promise of neuro-symbolic AI. He reflects on key moments in his career and discusses the next frontiers in machine learning.
00:27- About Pedro Domingos
- Pedro Domingos is a Professor Emeritus of computer science and engineering at the University of Washington.
- He is a researcher in machine learning known for the Markov logic Network enabling uncertain inference.
05:00- What are your thoughts on new AI models and their potential?
- Transformers are close to the “Master Algorithm” and combine symbolic AI with neural networks.
- Neuro-symbolic AI, the fusion of symbolic AI and neural networks, is gaining more attention.
- Symmetry group theory is essential for AI, serving as the fourth mathematical pillar alongside logic, probability/statistics, and optimization.
35:34- How close are you to AGI and what is your progress in AGI?
- We are likely 100 years away from AGI, with uncertainty about when it will happen.
- Progress in AI is rapid, but periods of stagnation are expected.
- Current AI research is mostly incremental, with some believing AGI will come from breakthroughs in various fields.
RESOURCES:
Learn more about Pedro Domingos: LinkedIn
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Profile
- Pedro Domingos is a Professor Emeritus of computer science and engineering at the University of Washington.
- He is a researcher in machine learning known for the Markov logic Network enabling uncertain inference.
