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Machine Learning Street Talk (MLST) द्वारा प्रदान की गई सामग्री. एपिसोड, ग्राफिक्स और पॉडकास्ट विवरण सहित सभी पॉडकास्ट सामग्री Machine Learning Street Talk (MLST) या उनके पॉडकास्ट प्लेटफ़ॉर्म पार्टनर द्वारा सीधे अपलोड और प्रदान की जाती है। यदि आपको लगता है कि कोई आपकी अनुमति के बिना आपके कॉपीराइट किए गए कार्य का उपयोग कर रहा है, तो आप यहां बताई गई प्रक्रिया का पालन कर सकते हैं https://hi.player.fm/legal
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Pedro Domingos: Tensor Logic Unifies AI Paradigms

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साझा करें
 

Manage episode 523192437 series 2803422
Machine Learning Street Talk (MLST) द्वारा प्रदान की गई सामग्री. एपिसोड, ग्राफिक्स और पॉडकास्ट विवरण सहित सभी पॉडकास्ट सामग्री Machine Learning Street Talk (MLST) या उनके पॉडकास्ट प्लेटफ़ॉर्म पार्टनर द्वारा सीधे अपलोड और प्रदान की जाती है। यदि आपको लगता है कि कोई आपकी अनुमति के बिना आपके कॉपीराइट किए गए कार्य का उपयोग कर रहा है, तो आप यहां बताई गई प्रक्रिया का पालन कर सकते हैं https://hi.player.fm/legal

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.

**SPONSOR MESSAGES START**

Build your ideas with AI Studio from Google - http://ai.studio/build

Prolific - Quality data. From real people. For faster breakthroughs.

https://www.prolific.com/?utm_source=mlst

cyber•Fund https://cyber.fund/?utm_source=mlst is a founder-led investment firm accelerating the cybernetic economy

Hiring a SF VC Principal: https://talent.cyber.fund/companies/cyber-fund-2/jobs/57674170-ai-investment-principal#content?utm_source=mlst

Submit investment deck: https://cyber.fund/contact?utm_source=mlst

**END**

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

  continue reading

239 एपिसोडस

Artwork
iconसाझा करें
 
Manage episode 523192437 series 2803422
Machine Learning Street Talk (MLST) द्वारा प्रदान की गई सामग्री. एपिसोड, ग्राफिक्स और पॉडकास्ट विवरण सहित सभी पॉडकास्ट सामग्री Machine Learning Street Talk (MLST) या उनके पॉडकास्ट प्लेटफ़ॉर्म पार्टनर द्वारा सीधे अपलोड और प्रदान की जाती है। यदि आपको लगता है कि कोई आपकी अनुमति के बिना आपके कॉपीराइट किए गए कार्य का उपयोग कर रहा है, तो आप यहां बताई गई प्रक्रिया का पालन कर सकते हैं https://hi.player.fm/legal

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.

**SPONSOR MESSAGES START**

Build your ideas with AI Studio from Google - http://ai.studio/build

Prolific - Quality data. From real people. For faster breakthroughs.

https://www.prolific.com/?utm_source=mlst

cyber•Fund https://cyber.fund/?utm_source=mlst is a founder-led investment firm accelerating the cybernetic economy

Hiring a SF VC Principal: https://talent.cyber.fund/companies/cyber-fund-2/jobs/57674170-ai-investment-principal#content?utm_source=mlst

Submit investment deck: https://cyber.fund/contact?utm_source=mlst

**END**

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

  continue reading

239 एपिसोडस

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