
Pedro Domingos: Tensor Logic Unifies AI Paradigms
Machine Learning Street Talk (MLST)
Reasoning in Embedding Space: Sound Deduction and Analogy
Pedro shows how embeddings, high-dimensional similarity, and temperature control enable both analogical and sound deductive reasoning.
Pedro Domingos, author of the bestselling book "The Master Algorithm," introduces his latest work: Tensor Logic - a new programming language he believes could become the fundamental language for artificial intelligence.
Think of it like this: Physics found its language in calculus. Circuit design found its language in Boolean logic. Pedro argues that AI has been missing its language - until now.
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Current AI is split between two worlds that don't play well together:
Deep Learning (neural networks, transformers, ChatGPT) - great at learning from data, terrible at logical reasoning
Symbolic AI (logic programming, expert systems) - great at logical reasoning, terrible at learning from messy real-world data
Tensor Logic unifies both. It's a single language where you can:
Write logical rules that the system can actually learn and modify
Do transparent, verifiable reasoning (no hallucinations)
Mix "fuzzy" analogical thinking with rock-solid deduction
INTERACTIVE TRANSCRIPT:
https://app.rescript.info/public/share/NP4vZQ-GTETeN_roB2vg64vbEcN7isjJtz4C86WSOhw
TOC:
00:00:00 - Introduction
00:04:41 - What is Tensor Logic?
00:09:59 - Tensor Logic vs PyTorch & Einsum
00:17:50 - The Master Algorithm Connection
00:20:41 - Predicate Invention & Learning New Concepts
00:31:22 - Symmetries in AI & Physics
00:35:30 - Computational Reducibility & The Universe
00:43:34 - Technical Details: RNN Implementation
00:45:35 - Turing Completeness Debate
00:56:45 - Transformers vs Turing Machines
01:02:32 - Reasoning in Embedding Space
01:11:46 - Solving Hallucination with Deductive Modes
01:16:17 - Adoption Strategy & Migration Path
01:21:50 - AI Education & Abstraction
01:24:50 - The Trillion-Dollar Waste
REFS
Tensor Logic: The Language of AI [Pedro Domingos]
https://arxiv.org/abs/2510.12269
The Master Algorithm [Pedro Domingos]
https://www.amazon.co.uk/Master-Algorithm-Ultimate-Learning-Machine/dp/0241004543
Einsum is All you Need (TIM ROCKTÄSCHEL)
https://rockt.ai/2018/04/30/einsum
https://www.youtube.com/watch?v=6DrCq8Ry2cw
Autoregressive Large Language Models are Computationally Universal (Dale Schuurmans et al - GDM)
https://arxiv.org/abs/2410.03170
Memory Augmented Large Language Models are Computationally Universal [Dale Schuurmans]
https://arxiv.org/pdf/2301.04589
On the computational power of NNs [95/Siegelmann]
https://binds.cs.umass.edu/papers/1995_Siegelmann_JComSysSci.pdf
Sebastian Bubeck
https://www.reddit.com/r/OpenAI/comments/1oacp38/openai_researcher_sebastian_bubeck_falsely_claims/
I am a strange loop - Hofstadter
https://www.amazon.co.uk/Am-Strange-Loop-Douglas-Hofstadter/dp/0465030793
Stephen Wolfram
https://www.youtube.com/watch?v=dkpDjd2nHgo
The Complex World: An Introduction to the Foundations of Complexity Science [David C. Krakauer]
https://www.amazon.co.uk/Complex-World-Introduction-Foundations-Complexity/dp/1947864629
Geometric Deep Learning
https://www.youtube.com/watch?v=bIZB1hIJ4u8
Andrew Wilson (NYU)
https://www.youtube.com/watch?v=M-jTeBCEGHc
Yi Ma
https://www.patreon.com/posts/yi-ma-scientific-141953348
Roger Penrose - road to reality
https://www.amazon.co.uk/Road-Reality-Complete-Guide-Universe/dp/0099440687
Artificial Intelligence: A Modern Approach [Russel and Norvig]
https://www.amazon.co.uk/Artificial-Intelligence-Modern-Approach-Global/dp/1292153962


