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हाइपरक्वेस्ट का छद्म-विज्ञान, छद्म-गणित एवं छद्म-इतिहास: भाग १ Pseudo-science, pseudo-math, and pseudo-history of HyperQuest: Part 1 (in Hindi) This video is a response to the original 13-minute 40-second-long video posted by HyperQuest on 6 June 2026. Many thanks to Amit Schandillia for his brilliant research and critique of the...

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Nityānanda Miśra (मिश्रोपाख्यो नित्यानन्दः)

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24,851 Aufrufe • vor 2 Monaten •via X (Twitter)

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First, Happy New Year everyone! It's been a wild ride. I can't wait for 2026, LFG! I love you all! ❤️ Second, here's my conversation with Joel David Hamkins (Joel David Hamkins), mathematician and philosopher specializing in set theory, the foundations of mathematics, and the nature of infinity. We talk about paradoxes that challenged some of the greatest mathematicians of the 20th century, Gödel Incompleteness theorems, the mathematical multiverse, the nature of truth, computation, and much more. By the way, Joel is the #1 highest-rated user on MathOverflow, and writes a great blog called "Infinitely More". It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Introduction 2:17 - Infinity & paradoxes 49:27 - Russell's paradox 1:02:35 - Gödel's incompleteness theorems 1:20:06 - Truth vs proof 1:31:30 - The Halting Problem 1:47:23 - Does infinity exist? 2:04:57 - MathOverflow 2:08:49 - The Continuum Hypothesis 2:18:36 - Hardest problems in mathematics 2:28:03 - Mathematical multiverse 2:46:55 - Surreal numbers 2:57:33 - Conway's Game of Life 2:59:49 - Computability theory 3:09:41 - P vs NP 3:12:58 - Greatest mathematicians in history 3:26:43 - Infinite chess 3:45:01 - Most beautiful idea in mathematics
3:52:17

First, Happy New Year everyone! It's been a wild ride. I can't wait for 2026, LFG! I love you all! ❤️ Second, here's my conversation with Joel David Hamkins (Joel David Hamkins), mathematician and philosopher specializing in set theory, the foundations of mathematics, and the nature of infinity. We talk about paradoxes that challenged some of the greatest mathematicians of the 20th century, Gödel Incompleteness theorems, the mathematical multiverse, the nature of truth, computation, and much more. By the way, Joel is the #1 highest-rated user on MathOverflow, and writes a great blog called "Infinitely More". It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Introduction 2:17 - Infinity & paradoxes 49:27 - Russell's paradox 1:02:35 - Gödel's incompleteness theorems 1:20:06 - Truth vs proof 1:31:30 - The Halting Problem 1:47:23 - Does infinity exist? 2:04:57 - MathOverflow 2:08:49 - The Continuum Hypothesis 2:18:36 - Hardest problems in mathematics 2:28:03 - Mathematical multiverse 2:46:55 - Surreal numbers 2:57:33 - Conway's Game of Life 2:59:49 - Computability theory 3:09:41 - P vs NP 3:12:58 - Greatest mathematicians in history 3:26:43 - Infinite chess 3:45:01 - Most beautiful idea in mathematics

Lex Fridman

516,714 Aufrufe • vor 7 Monaten

Always so much fun to chat with Grant Sanderson AI has been making much faster progress in math than in other fields. As a result, mathematics is showing us, very concretely, what AI progress in other fields will look like. Even within mathematics, there's a jagged landscape. What does it look like? What is the nature of the most important conceptual breakthroughs in the history of mathematics, and how different are they from what AIs are currently able to do? Does AI (on net) increase or decrease human understanding of the field? How big is the overhang from having AIs systematically try to connect ideas already in the literature? And what advice does Grant have for aspiring mathematicians, coders, and other students who are passionate about fields that are being most transformed upon by AI? 0:00:00 – AI is discovering new proofs. Is that AGI? 0:11:32 – The verification loop on conceptual breakthroughs can be a century long 0:26:12 – Will we understand an AI proof of the Riemann hypothesis? 0:38:08 – Can AI find the hidden bridges between fields? 0:53:48 – Why real-world tasks don’t fit into RL environments 1:07:07 – Good writing requires theory of mind that AI still lacks 1:16:02 – Why learning will still depend on human curation Look up Dwarkesh Podcast on Spotify, Apple Podcasts, YouTube, etc.
1:33:39

Always so much fun to chat with Grant Sanderson AI has been making much faster progress in math than in other fields. As a result, mathematics is showing us, very concretely, what AI progress in other fields will look like. Even within mathematics, there's a jagged landscape. What does it look like? What is the nature of the most important conceptual breakthroughs in the history of mathematics, and how different are they from what AIs are currently able to do? Does AI (on net) increase or decrease human understanding of the field? How big is the overhang from having AIs systematically try to connect ideas already in the literature? And what advice does Grant have for aspiring mathematicians, coders, and other students who are passionate about fields that are being most transformed upon by AI? 0:00:00 – AI is discovering new proofs. Is that AGI? 0:11:32 – The verification loop on conceptual breakthroughs can be a century long 0:26:12 – Will we understand an AI proof of the Riemann hypothesis? 0:38:08 – Can AI find the hidden bridges between fields? 0:53:48 – Why real-world tasks don’t fit into RL environments 1:07:07 – Good writing requires theory of mind that AI still lacks 1:16:02 – Why learning will still depend on human curation Look up Dwarkesh Podcast on Spotify, Apple Podcasts, YouTube, etc.

Dwarkesh Patel

289,936 Aufrufe • vor 1 Monat

Here's my conversation with Narendra Modi, Prime Minister of India. It was one of the most moving & powerful conversations and experiences of my life. This episode is fully dubbed into multiple languages including English and Hindi. It's also available in the original (mix of Hindi & English). On X, I post the full English-dub version. See comment for more. So the options are: - Audio: English, Hindi, Original (Mixed), and more - Subtitles: English, Hindi, and more Timestamps: 0:00 - In this episode... 3:07 - Introduction 9:19 - Fasting 21:38 - Early life 33:33 - Advice to Young People 39:16 - Journey in the Himalayas 50:45 - Becoming a monk 52:33 - RSS and Hindu nationalism 1:00:17 - Explaining India 1:04:27 - Mahatma Gandhi 1:16:23 - Path to peace in Ukraine 1:19:37 - India and Pakistan 1:25:16 - Cricket and Football 1:29:41 - Donald Trump 1:40:51 - China and Xi Jinping 1:47:56 - Gujarat riots in 2002 2:03:33 - Biggest democracy in the world 2:13:48 - Power 2:18:34 - Hard work 2:21:42 - Srinivasa Ramanujan 2:23:48 - Decision-making process 2:31:35 - AI 2:41:50 - Education 2:52:06 - Learning and focus 2:57:56 - Mantra 2:59:41 - Meditation 3:05:38 - Lex visiting India 3:10:04 - Siddhartha
3:17:33

Here's my conversation with Narendra Modi, Prime Minister of India. It was one of the most moving & powerful conversations and experiences of my life. This episode is fully dubbed into multiple languages including English and Hindi. It's also available in the original (mix of Hindi & English). On X, I post the full English-dub version. See comment for more. So the options are: - Audio: English, Hindi, Original (Mixed), and more - Subtitles: English, Hindi, and more Timestamps: 0:00 - In this episode... 3:07 - Introduction 9:19 - Fasting 21:38 - Early life 33:33 - Advice to Young People 39:16 - Journey in the Himalayas 50:45 - Becoming a monk 52:33 - RSS and Hindu nationalism 1:00:17 - Explaining India 1:04:27 - Mahatma Gandhi 1:16:23 - Path to peace in Ukraine 1:19:37 - India and Pakistan 1:25:16 - Cricket and Football 1:29:41 - Donald Trump 1:40:51 - China and Xi Jinping 1:47:56 - Gujarat riots in 2002 2:03:33 - Biggest democracy in the world 2:13:48 - Power 2:18:34 - Hard work 2:21:42 - Srinivasa Ramanujan 2:23:48 - Decision-making process 2:31:35 - AI 2:41:50 - Education 2:52:06 - Learning and focus 2:57:56 - Mantra 2:59:41 - Meditation 3:05:38 - Lex visiting India 3:10:04 - Siddhartha

Lex Fridman

3,786,899 Aufrufe • vor 1 Jahr

DIVINE MATHEMATICS Number One (1) is the Number of God. Everything is from Number. Number One (1) is the Number of Hydrogen. Your DNA is written in the Divine Mathematics of the Fibonacci Geometric Patterns/Sequences. Your DNA is written in Mathematical Number Patterns. That is why Science is filled with Calculations. Nature is written in the Fibonacci Geometric Patterns/Sequences. You do not need religion to know God. You need to understand the nature of existence from the angle of Science and Mathematics. Galileo Galilei, who deserves to be called the Father of Physics said thus how God created the Universe: "God created the Universe in the language of Mathematics" Everything in the Universe is Governed by Numbers. For this Purpose, Zero or Nothing or the Void is counted, not just as a Number, but as the Source of All Numbers. Zero or Nothing or the Void is mentioned in the Bible as early as Genesis because the Zero or the Void or Nothing is the Basis of All Numbers. In Genesis 1: 1-3 it is written thus: 1. In the Heaven and Earth. 2. And the Earth was without Form and Void; and Darkness was upon the Face of the Deep.... 3. And God said Let there be Light and there was Light. What follows are the 7 Days of Creation. Religion deceives and brainwashed the Masses that these are 7 literal Days. They're really about the Fibonacci Geometric Patterns/Sequences. Numbers govern the Chemical Elements that constitute the Universe, with Hydrogen being Number One to emerge from Zero and is the Same as the Zero with the Zero being the Darkness that was upon the Face of the Great Deep mentioned in Genesis 1:2. Number One became the Light which emerged from the Darkness. Without Darkness, there can be no Light. Everything is essentially a Mirror of the Same Thing. This is what is called Polarity. In other Words, Opposite Things depend on the each other in order to exist. Without Darkness, you cannot know what Light is. This is also represented by Gender, with the Female and the Male being diverse Forms of the Same Thing. The Hermetic Principles explain the relationship between everything in some details. In that regards, I suggest that you should look up the Hermetic Principles in the Kyballion. It is because the Numbers begins from Zero or Nothing or the Void that it is said that God made the Universe from Nothing. As already mentioned Number One is the Number of Hydrogen. The Hydrogen Atom permeates Everything in the Universe. It is because there is Hydrogen that there is a Material Universe. Hydrogen is Number One (1) on the Chemical Periodic Table. There is Nothing in the Material Universe that is not from Hydrogen. Hydrogen is the Basis of all Physical Existence. That is why Number One (1) is also the Number of God. The Sun and the Stars and Planets are All comprised of Hydrogen. Oxygen is constituted by the Thermonuclear Synthesis Hydrogen in the Nuclei of Stars. Hydrogen then COMBUSTS with Hydrogen to produce Dihydrogen Monoxide aka WATER. Your very being is literally powered by Hydrogen. As already indicated, Oxygen first came into Existence through Thermonuclear Fusion of Hydrogen Atoms in Stars. Stars are composed of the Hydrogen. Hydrogen is the Medium of Consciousness and Medium of the Material Universe of which we are an Intrinsic part. All of Nature is powered by Number One (1) aka Hydrogen. You're literally made of Hydrogen that has been transformed in Stars. The Sun, as a Star is composed of Hydrogen Atoms. The Circle which represents Zeros Nothing or the Void or the Darkness and also the Light represents the Hydrogen Atom. That is why the Sun and Moon are Circles. The Circle is the Basic Geometric Pattern. The multiplication of identical Circles create the Patterns and Sequences of the Flower of Life which is in All Indigenous Cultures. ✨🙌🏾💫
3:25

DIVINE MATHEMATICS Number One (1) is the Number of God. Everything is from Number. Number One (1) is the Number of Hydrogen. Your DNA is written in the Divine Mathematics of the Fibonacci Geometric Patterns/Sequences. Your DNA is written in Mathematical Number Patterns. That is why Science is filled with Calculations. Nature is written in the Fibonacci Geometric Patterns/Sequences. You do not need religion to know God. You need to understand the nature of existence from the angle of Science and Mathematics. Galileo Galilei, who deserves to be called the Father of Physics said thus how God created the Universe: "God created the Universe in the language of Mathematics" Everything in the Universe is Governed by Numbers. For this Purpose, Zero or Nothing or the Void is counted, not just as a Number, but as the Source of All Numbers. Zero or Nothing or the Void is mentioned in the Bible as early as Genesis because the Zero or the Void or Nothing is the Basis of All Numbers. In Genesis 1: 1-3 it is written thus: 1. In the Heaven and Earth. 2. And the Earth was without Form and Void; and Darkness was upon the Face of the Deep.... 3. And God said Let there be Light and there was Light. What follows are the 7 Days of Creation. Religion deceives and brainwashed the Masses that these are 7 literal Days. They're really about the Fibonacci Geometric Patterns/Sequences. Numbers govern the Chemical Elements that constitute the Universe, with Hydrogen being Number One to emerge from Zero and is the Same as the Zero with the Zero being the Darkness that was upon the Face of the Great Deep mentioned in Genesis 1:2. Number One became the Light which emerged from the Darkness. Without Darkness, there can be no Light. Everything is essentially a Mirror of the Same Thing. This is what is called Polarity. In other Words, Opposite Things depend on the each other in order to exist. Without Darkness, you cannot know what Light is. This is also represented by Gender, with the Female and the Male being diverse Forms of the Same Thing. The Hermetic Principles explain the relationship between everything in some details. In that regards, I suggest that you should look up the Hermetic Principles in the Kyballion. It is because the Numbers begins from Zero or Nothing or the Void that it is said that God made the Universe from Nothing. As already mentioned Number One is the Number of Hydrogen. The Hydrogen Atom permeates Everything in the Universe. It is because there is Hydrogen that there is a Material Universe. Hydrogen is Number One (1) on the Chemical Periodic Table. There is Nothing in the Material Universe that is not from Hydrogen. Hydrogen is the Basis of all Physical Existence. That is why Number One (1) is also the Number of God. The Sun and the Stars and Planets are All comprised of Hydrogen. Oxygen is constituted by the Thermonuclear Synthesis Hydrogen in the Nuclei of Stars. Hydrogen then COMBUSTS with Hydrogen to produce Dihydrogen Monoxide aka WATER. Your very being is literally powered by Hydrogen. As already indicated, Oxygen first came into Existence through Thermonuclear Fusion of Hydrogen Atoms in Stars. Stars are composed of the Hydrogen. Hydrogen is the Medium of Consciousness and Medium of the Material Universe of which we are an Intrinsic part. All of Nature is powered by Number One (1) aka Hydrogen. You're literally made of Hydrogen that has been transformed in Stars. The Sun, as a Star is composed of Hydrogen Atoms. The Circle which represents Zeros Nothing or the Void or the Darkness and also the Light represents the Hydrogen Atom. That is why the Sun and Moon are Circles. The Circle is the Basic Geometric Pattern. The multiplication of identical Circles create the Patterns and Sequences of the Flower of Life which is in All Indigenous Cultures. ✨🙌🏾💫

🧬Maxpein🧬

25,608 Aufrufe • vor 1 Jahr

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science
49:06

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science

Matt Turck

66,936 Aufrufe • vor 2 Monaten

Here's my conversation with Terence Tao, one of the greatest mathematicians in history. We talk about the hardest problems in mathematics & physics, and how AI might help us humans to solve them. This conversation was a huge honor for me. I can't quite put it into words, but once again I'm grateful for whatever simulation code resulted in me having the life I do 🙏 To further confirm simulation, podcast length accidentally turned out to be 3:14 (pi=3.141592). But it's not 3:14:15, because the simulation code has some bugs 🤣 Podcast is here on X in full, and is up everywhere else (see comment). Timestamps: 0:00 - Introduction 0:49 - First hard problem 6:16 - Navier–Stokes singularity 26:26 - Game of life 33:01 - Infinity 38:07 - Math vs Physics 44:26 - Nature of reality 1:07:09 - Theory of everything 1:13:10 - General relativity 1:16:37 - Solving difficult problems 1:20:01 - AI-assisted theorem proving 1:32:51 - Lean programming language 1:42:51 - DeepMind's AlphaProof 1:47:45 - Human mathematicians vs AI 1:57:37 - AI winning the Fields Medal 2:04:47 - Grigori Perelman 2:17:30 - Twin Prime Conjecture 2:34:04 - Collatz conjecture 2:40:50 - P = NP 2:43:43 - Fields Medal 2:51:18 - Andrew Wiles and Fermat's Last Theorem 2:55:16 - Productivity 2:57:55 - Advice for young people 3:06:17 - The greatest mathematician of all time
3:14:33

Here's my conversation with Terence Tao, one of the greatest mathematicians in history. We talk about the hardest problems in mathematics & physics, and how AI might help us humans to solve them. This conversation was a huge honor for me. I can't quite put it into words, but once again I'm grateful for whatever simulation code resulted in me having the life I do 🙏 To further confirm simulation, podcast length accidentally turned out to be 3:14 (pi=3.141592). But it's not 3:14:15, because the simulation code has some bugs 🤣 Podcast is here on X in full, and is up everywhere else (see comment). Timestamps: 0:00 - Introduction 0:49 - First hard problem 6:16 - Navier–Stokes singularity 26:26 - Game of life 33:01 - Infinity 38:07 - Math vs Physics 44:26 - Nature of reality 1:07:09 - Theory of everything 1:13:10 - General relativity 1:16:37 - Solving difficult problems 1:20:01 - AI-assisted theorem proving 1:32:51 - Lean programming language 1:42:51 - DeepMind's AlphaProof 1:47:45 - Human mathematicians vs AI 1:57:37 - AI winning the Fields Medal 2:04:47 - Grigori Perelman 2:17:30 - Twin Prime Conjecture 2:34:04 - Collatz conjecture 2:40:50 - P = NP 2:43:43 - Fields Medal 2:51:18 - Andrew Wiles and Fermat's Last Theorem 2:55:16 - Productivity 2:57:55 - Advice for young people 3:06:17 - The greatest mathematician of all time

Lex Fridman

1,230,941 Aufrufe • vor 1 Jahr

.Jacob Trefethen runs the science program at Open Philanthropy, directing about $100m/year in philanthropic funding. For New Science, we ended up talking about academia, peer review, grant-making; and also about love, the meaning of life, and our personal histories. Enjoy! Timestamps 0:00:00 - Introduction 0:01:11 - On Open Philanthropy's decision process 0:06:48 - Is it possible to make expected value calculations for basic scientific research? 0:16:27 - Non-profit funding vs for-profit funding 0:17:19 - Why the NIH rejects grants 0:19:39 - Jacob's "PhD" working side-by-side with biochemists for 5 years 0:25:22 - Today's system of federal funding are not supporting generalists 0:28:34 - How will AI affect the pace of scientific progress? 0:41:53 - AI Baumol Disease 0:54:41 - Can AI speed up aging research? 0:58:20 - The wisest people Jacob & Alexey know 1:13:31 - The future of science in academia 1:19:26 - How Open Philanthropy uses neglectedness to make funding trade-offs 1:35:16 - Jacob's advice for a talented 20 year old watching this 1:45:24 - Jacob's favorite joke
1:47:57

.Jacob Trefethen runs the science program at Open Philanthropy, directing about $100m/year in philanthropic funding. For New Science, we ended up talking about academia, peer review, grant-making; and also about love, the meaning of life, and our personal histories. Enjoy! Timestamps 0:00:00 - Introduction 0:01:11 - On Open Philanthropy's decision process 0:06:48 - Is it possible to make expected value calculations for basic scientific research? 0:16:27 - Non-profit funding vs for-profit funding 0:17:19 - Why the NIH rejects grants 0:19:39 - Jacob's "PhD" working side-by-side with biochemists for 5 years 0:25:22 - Today's system of federal funding are not supporting generalists 0:28:34 - How will AI affect the pace of scientific progress? 0:41:53 - AI Baumol Disease 0:54:41 - Can AI speed up aging research? 0:58:20 - The wisest people Jacob & Alexey know 1:13:31 - The future of science in academia 1:19:26 - How Open Philanthropy uses neglectedness to make funding trade-offs 1:35:16 - Jacob's advice for a talented 20 year old watching this 1:45:24 - Jacob's favorite joke

Alexey Guzey

23,458 Aufrufe • vor 1 Jahr

E174: Tarek Mansour - Launching the First Regulated Perps In The U.S and building the next generation of financial markets Tarek Mansour is the co-founder and CEO of Kalshi, the first regulated prediction market exchange in the US, valued at $22 Billion. He grew up in Lebanon with a single mom, studied at MIT, worked at Citadel, and spent 6 years years building a company most people ignored before it finally took off. We talk about what it actually takes to not give up, why markets are better at finding truth than experts, why Kalshi is launching the first regulated Perps in the US, and how his team is building what he calls the next generation of financial markets. Timestamps: 0:00 Intro 1:54 Urgency 3:11 Anime 4:53 Who is Tarek? 7:02 Mathematics & Certainty 9:10 Tarek's chip on the shoulder 13:33 Partnerships: Trezor Bitwise 15:19 Resilience 16:31 Entrepreneurship is Therapy 18:23 The startup emotional rollercoaster 22:16 Showing up for 2000 days with no results 24:45 First time Founder advantage 26:40 When Kalshi almost made it, but did not 29:54 Partnerships: KAST 31:19 Focus Inputs, Not Results 33:16 The Kalshi beginnings story 36:00 The True Innovation Of Prediction Markets 38:28 How Prediction Markets Revolutionize The Media 41:37 Prediction Markets and Hedging explained simply 44:55 Leverage In Prediction Markets 47:16 Partnerships: Jupiter Ethena 48:00 Insider Trading 51:19 Insider Trading Rules enforcement: who is responsible? 55:26 How Kalshi spots Suspicious Behavior 56:59 Tarek's Honest View On Crypto 59:41 Launching the first Regulated Perps In The U.S 1:00:30 What Does Regulated Perps Mean? 1:02:22 Was Kalshi perps launch inspired by Hyperliquid? 1:03:41 Competition 1:05:58 Kalshi Endgame 1:07:06 What is Kalshi doing with the billions of $ they raised 1:08:31 Happiness and engagement 1:13:08 One Thing Tarek Should Let Go Of 1:14:18 Closing Thoughts
1:15:03

E174: Tarek Mansour - Launching the First Regulated Perps In The U.S and building the next generation of financial markets Tarek Mansour is the co-founder and CEO of Kalshi, the first regulated prediction market exchange in the US, valued at $22 Billion. He grew up in Lebanon with a single mom, studied at MIT, worked at Citadel, and spent 6 years years building a company most people ignored before it finally took off. We talk about what it actually takes to not give up, why markets are better at finding truth than experts, why Kalshi is launching the first regulated Perps in the US, and how his team is building what he calls the next generation of financial markets. Timestamps: 0:00 Intro 1:54 Urgency 3:11 Anime 4:53 Who is Tarek? 7:02 Mathematics & Certainty 9:10 Tarek's chip on the shoulder 13:33 Partnerships: Trezor Bitwise 15:19 Resilience 16:31 Entrepreneurship is Therapy 18:23 The startup emotional rollercoaster 22:16 Showing up for 2000 days with no results 24:45 First time Founder advantage 26:40 When Kalshi almost made it, but did not 29:54 Partnerships: KAST 31:19 Focus Inputs, Not Results 33:16 The Kalshi beginnings story 36:00 The True Innovation Of Prediction Markets 38:28 How Prediction Markets Revolutionize The Media 41:37 Prediction Markets and Hedging explained simply 44:55 Leverage In Prediction Markets 47:16 Partnerships: Jupiter Ethena 48:00 Insider Trading 51:19 Insider Trading Rules enforcement: who is responsible? 55:26 How Kalshi spots Suspicious Behavior 56:59 Tarek's Honest View On Crypto 59:41 Launching the first Regulated Perps In The U.S 1:00:30 What Does Regulated Perps Mean? 1:02:22 Was Kalshi perps launch inspired by Hyperliquid? 1:03:41 Competition 1:05:58 Kalshi Endgame 1:07:06 What is Kalshi doing with the billions of $ they raised 1:08:31 Happiness and engagement 1:13:08 One Thing Tarek Should Let Go Of 1:14:18 Closing Thoughts

MR SHIFT 🦁

596,102 Aufrufe • vor 2 Monaten

The history of Fibonacci's clock is quite intriguing, as it combines the fascinating world of mathematics with the practical application of timekeeping. The clock is named after Leonardo Fibonacci, also known as Leonardo of Pisa, an Italian mathematician from the Middle Ages. Fibonacci is most famous for introducing the Hindu-Arabic numeral system to the Western world and for his work in the Fibonacci sequence. However, the Fibonacci clock we know today is not a direct creation of Leonardo Fibonacci. The modern Fibonacci clock is a tribute to his mathematical genius and the beauty of the Fibonacci sequence. The clock's design is based on the sequence, with each number represented by a specific color or pattern. The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding ones, starting with 0 and 1. The sequence goes as follows: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, and so on. The sequence appears in many natural phenomena, such as the arrangement of leaves on a stem, the spiral patterns of a pinecone, and the growth of a nautilus shell. The Fibonacci clock is a unique timepiece that displays the time using the Fibonacci sequence. The clock face is divided into sections that correspond to the numbers in the sequence. The time is shown by illuminating specific sections of the clock face, with each section representing a different unit of time. For example, one section might represent hours, another minutes, and another seconds.
0:25

The history of Fibonacci's clock is quite intriguing, as it combines the fascinating world of mathematics with the practical application of timekeeping. The clock is named after Leonardo Fibonacci, also known as Leonardo of Pisa, an Italian mathematician from the Middle Ages. Fibonacci is most famous for introducing the Hindu-Arabic numeral system to the Western world and for his work in the Fibonacci sequence. However, the Fibonacci clock we know today is not a direct creation of Leonardo Fibonacci. The modern Fibonacci clock is a tribute to his mathematical genius and the beauty of the Fibonacci sequence. The clock's design is based on the sequence, with each number represented by a specific color or pattern. The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding ones, starting with 0 and 1. The sequence goes as follows: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, and so on. The sequence appears in many natural phenomena, such as the arrangement of leaves on a stem, the spiral patterns of a pinecone, and the growth of a nautilus shell. The Fibonacci clock is a unique timepiece that displays the time using the Fibonacci sequence. The clock face is divided into sections that correspond to the numbers in the sequence. The time is shown by illuminating specific sections of the clock face, with each section representing a different unit of time. For example, one section might represent hours, another minutes, and another seconds.

Historic Vids

1,397,624 Aufrufe • vor 2 Jahren

The Science of Chanting: Why 32 Lakh Times for the Gayatri Mantra? Have you ever wondered why there is a specific count for mantra chanting in our traditions? It is not just a random number; it is a deep spiritual science based on the structure of the mantra itself. In this video, the significance of the Gayatri Mantra and its "Purushcharana" (the process of mastering a mantra) is explained through simple spiritual mathematics. The Math Behind the Mantra: - The 24 Varnas: The basic Gayatri Mantra consists of 24 syllables or letters, known as varnas. - The 24 Lakh Goal: According to Mantra Shastra, to initiate or "awaken" a mantra, one must chant it as many lakh times as there are syllables. Therefore, the basic practice requires 24 lakh chants, which a dedicated seeker can usually complete in about 2 years. The Vishvamitra Tradition: The count changes when we follow the method used by Brahmarishi Vishvamitra, which includes the Vyahritis. - Adding the Vyahritis: By adding Om and the three Vyahritis (Bhur, Bhuvah, Svah), the total count of syllables increases. - The 32 Lakh Sankalp: These additions bring the total to 32 syllables (24 + 8 = 32). To complete the full Purushcharana of this version, one must perform 32 lakh chants. This tradition shows us that every sound has weight and every chant brings us closer to spiritual awakening. It is a journey of discipline, patience, and pure devotion. Jai Maa Gayatri! If you found this insight helpful, save this post for your spiritual journey and share it with others!
1:09

The Science of Chanting: Why 32 Lakh Times for the Gayatri Mantra? Have you ever wondered why there is a specific count for mantra chanting in our traditions? It is not just a random number; it is a deep spiritual science based on the structure of the mantra itself. In this video, the significance of the Gayatri Mantra and its "Purushcharana" (the process of mastering a mantra) is explained through simple spiritual mathematics. The Math Behind the Mantra: - The 24 Varnas: The basic Gayatri Mantra consists of 24 syllables or letters, known as varnas. - The 24 Lakh Goal: According to Mantra Shastra, to initiate or "awaken" a mantra, one must chant it as many lakh times as there are syllables. Therefore, the basic practice requires 24 lakh chants, which a dedicated seeker can usually complete in about 2 years. The Vishvamitra Tradition: The count changes when we follow the method used by Brahmarishi Vishvamitra, which includes the Vyahritis. - Adding the Vyahritis: By adding Om and the three Vyahritis (Bhur, Bhuvah, Svah), the total count of syllables increases. - The 32 Lakh Sankalp: These additions bring the total to 32 syllables (24 + 8 = 32). To complete the full Purushcharana of this version, one must perform 32 lakh chants. This tradition shows us that every sound has weight and every chant brings us closer to spiritual awakening. It is a journey of discipline, patience, and pure devotion. Jai Maa Gayatri! If you found this insight helpful, save this post for your spiritual journey and share it with others!

Arpit

23,314 Aufrufe • vor 7 Monaten

E97: Gavin Wood : Why Ethereum is Going Nowhere since 8 years (and my solution to it) Dr. Gavin Wood is the CoFounder of Ethereum, the Creator of the EVM and of the solidity language, and the Inventor and Founder of Polkadot & Parity Technologies Timestamps 0:00 Introduction 2:44 Culture in Japan VS UK 6:00 Humour 7:40 Who is Gavin? 9:17 Mission 10:28 Characteristics of Successful Founders 13:53 Developing Big Ideas 16:08 Creative Success Mechanism 20:03 Suffering 24:56 From Theory to Transactions 32:28 Building a Support Network 34:36 Legacy Banking Systems 36:01 Music Engineering 45:08 Childhood Dreams 46:27 Camino de Santiago 49:19 Crypto Fascination 54:44 Web3: The Post Snowden Web 1:00:39 Co-Founding Ethereum 1:03:12 Biggest Ethereum Achievement 1:04:04 Is Ethereum a Success? 1:07:38 Why Gavin Left Ethereum 1:09:48 Polkadot 1:14:53 Polkadots Achievements and Problems 1:24:05 Solution to Polkadot Main Problem 1:28:12 Polkadots Adoption & Communication Strategy 1:38:26 Polkadot Vision of Success 1:42:30 Memecoins 1:45:19 Crypto Integrity 1:49:45 Crypto's Limited Adoption 1:58:35 Identity vs. Individuality 2:07:15 Is AI a Bad Thing? 2:09:27 AI's Communication Revolution 2:25:06 Decentralization Role in AI 2:29:08 Eternal Happiness 2:32:17 Are You Happy? 2:33:52 Meaning of Life 2:38:58 What is Money? 2:45:55 Experience as a Father 2:48:54 Non-Consensus Beliefs
2:52:39

E97: Gavin Wood : Why Ethereum is Going Nowhere since 8 years (and my solution to it) Dr. Gavin Wood is the CoFounder of Ethereum, the Creator of the EVM and of the solidity language, and the Inventor and Founder of Polkadot & Parity Technologies Timestamps 0:00 Introduction 2:44 Culture in Japan VS UK 6:00 Humour 7:40 Who is Gavin? 9:17 Mission 10:28 Characteristics of Successful Founders 13:53 Developing Big Ideas 16:08 Creative Success Mechanism 20:03 Suffering 24:56 From Theory to Transactions 32:28 Building a Support Network 34:36 Legacy Banking Systems 36:01 Music Engineering 45:08 Childhood Dreams 46:27 Camino de Santiago 49:19 Crypto Fascination 54:44 Web3: The Post Snowden Web 1:00:39 Co-Founding Ethereum 1:03:12 Biggest Ethereum Achievement 1:04:04 Is Ethereum a Success? 1:07:38 Why Gavin Left Ethereum 1:09:48 Polkadot 1:14:53 Polkadots Achievements and Problems 1:24:05 Solution to Polkadot Main Problem 1:28:12 Polkadots Adoption & Communication Strategy 1:38:26 Polkadot Vision of Success 1:42:30 Memecoins 1:45:19 Crypto Integrity 1:49:45 Crypto's Limited Adoption 1:58:35 Identity vs. Individuality 2:07:15 Is AI a Bad Thing? 2:09:27 AI's Communication Revolution 2:25:06 Decentralization Role in AI 2:29:08 Eternal Happiness 2:32:17 Are You Happy? 2:33:52 Meaning of Life 2:38:58 What is Money? 2:45:55 Experience as a Father 2:48:54 Non-Consensus Beliefs

MR SHIFT 🦁

265,222 Aufrufe • vor 1 Jahr

NEW POD | EP 71 Where Does Crypto Go From Here? ft. qw & Imran Timestamps: 0:46 $LIBRA 6:23 4 Use Cases of Crypto 8:17 The End Goal for Payments 9:54 DePIN and Energy 12:12 Simplicity of Crypto 13:18 Crypto is Finance 14:43 “Web 3.0” is a Lie? 15:43 The Biggest Risk for Ethereum 16:16 Qiao on DeFi 18:19 Crypto AI Builders Pivoting Straight to AI 19:47 AI in Education 27:25 AI for Ad Creation 29:32 AI for Building dApps 31:51 Personalized Apps 32:49 "The Future is Personalization" 34:07 "Lazy People Will Get F**ked by AI" 35:08 AI in Gaming and Video Generation 36:54 NFTs Comeback with AI? 42:21 Verticalized Science AI 48:52 Startups Solving Capital Markets Problem 54:59 Criticizing Trump's Token Launch 59:19 "Crypto Twitter is imploding" 1:00:51 Reminiscing Good Times in Crypto 1:02:27 Promising Crypto Startups 1:04:15 AI Arms Race 1:06:26 Impact of AI on Startups 1:12:11 AI in B2B 1:15:52 Are Memecoins Dead? 1:16:11 Market Analysis 1:18:48 End of the Cycle or 1 More Pump? 1:20:13 Reflection on Early Crypto Ideals 1:21:05 Cypherpunk Ideologies Link ↓
1:22:45

NEW POD | EP 71 Where Does Crypto Go From Here? ft. qw & Imran Timestamps: 0:46 $LIBRA 6:23 4 Use Cases of Crypto 8:17 The End Goal for Payments 9:54 DePIN and Energy 12:12 Simplicity of Crypto 13:18 Crypto is Finance 14:43 “Web 3.0” is a Lie? 15:43 The Biggest Risk for Ethereum 16:16 Qiao on DeFi 18:19 Crypto AI Builders Pivoting Straight to AI 19:47 AI in Education 27:25 AI for Ad Creation 29:32 AI for Building dApps 31:51 Personalized Apps 32:49 "The Future is Personalization" 34:07 "Lazy People Will Get F**ked by AI" 35:08 AI in Gaming and Video Generation 36:54 NFTs Comeback with AI? 42:21 Verticalized Science AI 48:52 Startups Solving Capital Markets Problem 54:59 Criticizing Trump's Token Launch 59:19 "Crypto Twitter is imploding" 1:00:51 Reminiscing Good Times in Crypto 1:02:27 Promising Crypto Startups 1:04:15 AI Arms Race 1:06:26 Impact of AI on Startups 1:12:11 AI in B2B 1:15:52 Are Memecoins Dead? 1:16:11 Market Analysis 1:18:48 End of the Cycle or 1 More Pump? 1:20:13 Reflection on Early Crypto Ideals 1:21:05 Cypherpunk Ideologies Link ↓

Good Game

29,494 Aufrufe • vor 1 Jahr

Here's my conversation with Kevin Spacey (Kevin Spacey), a two-time Oscar winning actor, who has created powerful haunting performances of characters who often embody the dark side of human nature. As I've said before, I will talk to everyone, with empathy and with backbone. I won't whitewash their sins, but I won't reduce them to a worst-possible-caricature of their sins either. This is what outrage mobs and click-bait journalists too often do, rushing to judgment before the facts are in. I will try to do better than that: to respect due process in service of the truth. And I hope to have the courage to always think independently, and to speak honestly and with compassion, even when the eyes of the outrage mob are on me. We discuss the allegations in this conversation and reference further details. Briefly: 7 years ago, Kevin Spacey was canceled, when Anthony Rapp made a sexual allegation against him, and then filed a civil lawsuit seeking $40 million dollars. In this trial and all civil and criminal trials that followed, Kevin was acquitted. He has never been found guilty nor liable in the court of law. Again, my goal is to understand human beings, at their best and at their worst. And the hope is such understanding leads to more compassion and wisdom in the world. I will make mistakes, and when I do, I will work hard to improve. I love you all ❤ PS: The conversation is here on X in full, and is up on YouTube, Spotify, and everywhere else. Links in comment. Timestamps: 0:00 - Introduction 2:44 - Seven 6:24 - David Fincher 14:16 - Brad Pitt and Morgan Freeman 19:46 - Acting 28:10 - Improve 36:54 - Al Pacino 40:38 - Jack Lemmon 49:55 - American Beauty 1:10:04 - Mortality 1:12:52 - Allegations 1:30:50 - House of Cards 1:49:25 - Jack Nicholson 1:52:27 - Mike Nichols 1:58:01 - Christopher Walken 2:05:08 - Father 2:14:00 - Future
2:19:07

Here's my conversation with Kevin Spacey (Kevin Spacey), a two-time Oscar winning actor, who has created powerful haunting performances of characters who often embody the dark side of human nature. As I've said before, I will talk to everyone, with empathy and with backbone. I won't whitewash their sins, but I won't reduce them to a worst-possible-caricature of their sins either. This is what outrage mobs and click-bait journalists too often do, rushing to judgment before the facts are in. I will try to do better than that: to respect due process in service of the truth. And I hope to have the courage to always think independently, and to speak honestly and with compassion, even when the eyes of the outrage mob are on me. We discuss the allegations in this conversation and reference further details. Briefly: 7 years ago, Kevin Spacey was canceled, when Anthony Rapp made a sexual allegation against him, and then filed a civil lawsuit seeking $40 million dollars. In this trial and all civil and criminal trials that followed, Kevin was acquitted. He has never been found guilty nor liable in the court of law. Again, my goal is to understand human beings, at their best and at their worst. And the hope is such understanding leads to more compassion and wisdom in the world. I will make mistakes, and when I do, I will work hard to improve. I love you all ❤ PS: The conversation is here on X in full, and is up on YouTube, Spotify, and everywhere else. Links in comment. Timestamps: 0:00 - Introduction 2:44 - Seven 6:24 - David Fincher 14:16 - Brad Pitt and Morgan Freeman 19:46 - Acting 28:10 - Improve 36:54 - Al Pacino 40:38 - Jack Lemmon 49:55 - American Beauty 1:10:04 - Mortality 1:12:52 - Allegations 1:30:50 - House of Cards 1:49:25 - Jack Nicholson 1:52:27 - Mike Nichols 1:58:01 - Christopher Walken 2:05:08 - Father 2:14:00 - Future

Lex Fridman

1,395,674 Aufrufe • vor 2 Jahren

Here's my conversation with Gregory Aldrete, a historian specializing in ancient Rome and military history. We talk all about the Roman Empire: its rise and fall, major battles & leaders, military technology & tactics, gladiators, politics, laws, economy, religion. I will do many more episodes on history (interviews & solo). If we don't understand our past, we are doomed to repeat the same mistakes that many before us have paid a heavy price for. Timestamps: 0:00 - Introduction 2:23 - Ancient world 16:18 - Three phases of Roman history 19:08 - Rome's expansion 30:48 - Punic wars 39:20 - Conquering Greece 40:59 - Scipio vs Hannibal 44:05 - Heavy infantry vs Cavalry 47:42 - Armor 1:00:32 - Alexander the Great 1:06:33 - Roman law 1:16:13 - Slavery 1:23:53 - Fall of the Roman Republic 1:27:38 - Julius Caesar 1:32:17 - Octavian's rise 1:42:09 - Cleopatra 1:50:32 - Augustus 2:18:42 - Religion in Rome 2:42:47 - Emperors 2:49:54 - Marcus Aurelius 2:56:05 - Taxes 2:59:13 - Fall of the Roman Empire 3:16:25 - Decisive battles 3:40:35 - Hope
3:42:11

Here's my conversation with Gregory Aldrete, a historian specializing in ancient Rome and military history. We talk all about the Roman Empire: its rise and fall, major battles & leaders, military technology & tactics, gladiators, politics, laws, economy, religion. I will do many more episodes on history (interviews & solo). If we don't understand our past, we are doomed to repeat the same mistakes that many before us have paid a heavy price for. Timestamps: 0:00 - Introduction 2:23 - Ancient world 16:18 - Three phases of Roman history 19:08 - Rome's expansion 30:48 - Punic wars 39:20 - Conquering Greece 40:59 - Scipio vs Hannibal 44:05 - Heavy infantry vs Cavalry 47:42 - Armor 1:00:32 - Alexander the Great 1:06:33 - Roman law 1:16:13 - Slavery 1:23:53 - Fall of the Roman Republic 1:27:38 - Julius Caesar 1:32:17 - Octavian's rise 1:42:09 - Cleopatra 1:50:32 - Augustus 2:18:42 - Religion in Rome 2:42:47 - Emperors 2:49:54 - Marcus Aurelius 2:56:05 - Taxes 2:59:13 - Fall of the Roman Empire 3:16:25 - Decisive battles 3:40:35 - Hope

Lex Fridman

8,260,648 Aufrufe • vor 1 Jahr

My conversation with Dylan Patel on everything you ever wanted to know about the incredible buildout happening in AI infrastructure This is a whirlwind tour through the companies, deals, models, chips, power sources, partnerships, and people powering AI Dylan is some sort of genius. I wish a version of him existed for every subject. I hope you enjoy this as much as I did. Timestamps: 0:00 Introduction 0:39 The Infinite Money Glitch 4:42 Oracle's Bet on OpenAI 6:06 Nvidia's Strategic Investment and Deal Mechanics 9:17 Why Bigger Models Aren't Always Better 15:07 The Adoption Curve Problem 19:01 The Tokenomics of AI 23:59 Over-Parameterization and Model Learning 28:10 Building Environments for AI Training 32:16 AI in Everyday Life 34:46 The Future of Reasoning and Compute Scaling 44:34 The Spectrum of AI Optimism 46:29 Timeline to AGI 49:25 Talent Wars 58:37 Power Dynamics in the AI Ecosystem 1:18:42 AI for Material Science and Hard Tech 1:22:21 Building Infrastructure 1:29:55 US vs China: Who Really Needs AI to Win? 1:37:42 Favorite AI Bears 1:48:08 Speed Round: Company Impressions 1:55:11 The Death of Traditional SaaS Business Models 2:00:24 The Kindest Thing
2:02:21

My conversation with Dylan Patel on everything you ever wanted to know about the incredible buildout happening in AI infrastructure This is a whirlwind tour through the companies, deals, models, chips, power sources, partnerships, and people powering AI Dylan is some sort of genius. I wish a version of him existed for every subject. I hope you enjoy this as much as I did. Timestamps: 0:00 Introduction 0:39 The Infinite Money Glitch 4:42 Oracle's Bet on OpenAI 6:06 Nvidia's Strategic Investment and Deal Mechanics 9:17 Why Bigger Models Aren't Always Better 15:07 The Adoption Curve Problem 19:01 The Tokenomics of AI 23:59 Over-Parameterization and Model Learning 28:10 Building Environments for AI Training 32:16 AI in Everyday Life 34:46 The Future of Reasoning and Compute Scaling 44:34 The Spectrum of AI Optimism 46:29 Timeline to AGI 49:25 Talent Wars 58:37 Power Dynamics in the AI Ecosystem 1:18:42 AI for Material Science and Hard Tech 1:22:21 Building Infrastructure 1:29:55 US vs China: Who Really Needs AI to Win? 1:37:42 Favorite AI Bears 1:48:08 Speed Round: Company Impressions 1:55:11 The Death of Traditional SaaS Business Models 2:00:24 The Kindest Thing

Patrick OShaughnessy

548,858 Aufrufe • vor 10 Monaten

Here's my conversation all about FFmpeg, the legendary open-source software powering most video on the Internet. In the episode, I talk with Jean-Baptiste Kempf and Kieran Kunhya. JB is lead developer of VLC and Kieran is FFmpeg contributor, codec engineer, and the person behind the now-infamous FFmpeg account on X. VLC (VideoLAN), by the way, is also a legendary piece of open-source software: it's a video player that can open basically anything & has been downloaded over 6 billion times. I think both FFmpeg and VLC are two of the most important and impactful software systems ever created, both open source, and both created & maintained by volunteers: brilliant engineers from all walks of life. Thank you to everyone who contributed to FFmpeg and VLC, and in general to all engineers giving their heart & soul to building systems used by millions (or billions) of people, and often doing so not for money, status, or fame, but purely for the love of building great software and doing good for the world. Thank you to the builders! 🙏❤️ Shoutouts in this chat to John Carmack Andrej Karpathy Elon Musk Tim Sweeney and everyone who is a contributor & fan of open source! It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 2:17 - Introduction 5:35 - Weirdest things VLC opens 9:59 - How video playback works 19:20 - Video codecs and containers 30:07 - FFmpeg explained 51:07 - Linus Torvalds 55:46 - Turning down millions to keep VLC ad-free 1:10:04 - FFmpeg & Google drama 1:29:18 - FFmpeg developers 1:35:55 - VLC and FFmpeg 1:40:29 - History of FFmpeg 1:43:46 - Reverse engineering codecs 1:57:01 - FFmpeg testing 2:01:08 - Assembly code (handwritten) 2:25:26 - Rust programming language 2:34:42 - FFmpeg and Libav fork 2:43:04 - Open source burnout 2:50:51 - x264 and internet video 3:04:07 - Video compression basics 3:11:04 - CIA and fake VLC 3:21:39 - Ultra low latency streaming 3:39:07 - AV2 codec and video patents 3:48:59 - VLC backdoors 3:59:14 - Video archiving 4:05:51 - Future of FFmpeg and VLC
4:18:21

Here's my conversation all about FFmpeg, the legendary open-source software powering most video on the Internet. In the episode, I talk with Jean-Baptiste Kempf and Kieran Kunhya. JB is lead developer of VLC and Kieran is FFmpeg contributor, codec engineer, and the person behind the now-infamous FFmpeg account on X. VLC (VideoLAN), by the way, is also a legendary piece of open-source software: it's a video player that can open basically anything & has been downloaded over 6 billion times. I think both FFmpeg and VLC are two of the most important and impactful software systems ever created, both open source, and both created & maintained by volunteers: brilliant engineers from all walks of life. Thank you to everyone who contributed to FFmpeg and VLC, and in general to all engineers giving their heart & soul to building systems used by millions (or billions) of people, and often doing so not for money, status, or fame, but purely for the love of building great software and doing good for the world. Thank you to the builders! 🙏❤️ Shoutouts in this chat to John Carmack Andrej Karpathy Elon Musk Tim Sweeney and everyone who is a contributor & fan of open source! It's here on X in full and is up everywhere else (see comment). Timestamps: 0:00 - Episode highlight 2:17 - Introduction 5:35 - Weirdest things VLC opens 9:59 - How video playback works 19:20 - Video codecs and containers 30:07 - FFmpeg explained 51:07 - Linus Torvalds 55:46 - Turning down millions to keep VLC ad-free 1:10:04 - FFmpeg & Google drama 1:29:18 - FFmpeg developers 1:35:55 - VLC and FFmpeg 1:40:29 - History of FFmpeg 1:43:46 - Reverse engineering codecs 1:57:01 - FFmpeg testing 2:01:08 - Assembly code (handwritten) 2:25:26 - Rust programming language 2:34:42 - FFmpeg and Libav fork 2:43:04 - Open source burnout 2:50:51 - x264 and internet video 3:04:07 - Video compression basics 3:11:04 - CIA and fake VLC 3:21:39 - Ultra low latency streaming 3:39:07 - AV2 codec and video patents 3:48:59 - VLC backdoors 3:59:14 - Video archiving 4:05:51 - Future of FFmpeg and VLC

Lex Fridman

511,704 Aufrufe • vor 3 Monaten

95% of Physics is Made Up FUDGE! X/Twitter Livestream Philosopher Stefan Molyneux calls out 95% of physics as made up fudge in this 3 July 2026 Friday Night Live, where dark matter and dark energy serve as empty placeholders for why galaxies hold together and expansion speeds up when only 5% of the universe matches our equations. He pushes for honest admissions about what science actually knows instead of pouring public money into convenient fictions. 0:00:00 Physics Outrage Unleashed 0:03:47 Dark Energy Explained 0:17:16 Dark Matter Problems 0:29:11 History of the Fudge 0:32:41 Dark Energy’s 1998 Discovery 0:44:40 Calling Out the Placeholder 0:50:56 Final Rant on Physics 0:54:21 Science and Faith Clash 0:56:33 Dark Matter Explained 1:02:46 Halo Mysteries Deepen 1:07:08 Rabbit Hole Research 1:09:57 Science, Skepticism, and COVID 1:14:00 Near-Death Skepticism 1:17:25 Placeholders and Dark Energy 1:21:19 Funding, Research, and Freedom 1:26:04 Child Abuse or Belief? 1:29:20 Family Tension and Boundaries 1:32:58 Eternal Universe Speculation 1:36:04 Challenging Physics Claims 1:39:47 Public Science Skepticism 1:41:54 Polyamory and Dysfunction GET FREEDOMAIN MERCH! SUBSCRIBE TO ME ON X! Follow me on Youtube! GET MY NEW BOOK 'PEACEFUL PARENTING', THE INTERACTIVE PEACEFUL PARENTING AI, AND THE FULL AUDIOBOOK! Join the PREMIUM philosophy community on the web for free! Subscribers get 12 HOURS on the "Truth About the French Revolution," multiple interactive multi-lingual philosophy AIs trained on thousands of hours of my material - as well as AIs for Real-Time Relationships, Bitcoin, Peaceful Parenting, and Call-In Shows! You also receive private livestreams, HUNDREDS of exclusive premium shows, early release podcasts, the 22 Part History of Philosophers series and much more! See you soon!
1:42:50

95% of Physics is Made Up FUDGE! X/Twitter Livestream Philosopher Stefan Molyneux calls out 95% of physics as made up fudge in this 3 July 2026 Friday Night Live, where dark matter and dark energy serve as empty placeholders for why galaxies hold together and expansion speeds up when only 5% of the universe matches our equations. He pushes for honest admissions about what science actually knows instead of pouring public money into convenient fictions. 0:00:00 Physics Outrage Unleashed 0:03:47 Dark Energy Explained 0:17:16 Dark Matter Problems 0:29:11 History of the Fudge 0:32:41 Dark Energy’s 1998 Discovery 0:44:40 Calling Out the Placeholder 0:50:56 Final Rant on Physics 0:54:21 Science and Faith Clash 0:56:33 Dark Matter Explained 1:02:46 Halo Mysteries Deepen 1:07:08 Rabbit Hole Research 1:09:57 Science, Skepticism, and COVID 1:14:00 Near-Death Skepticism 1:17:25 Placeholders and Dark Energy 1:21:19 Funding, Research, and Freedom 1:26:04 Child Abuse or Belief? 1:29:20 Family Tension and Boundaries 1:32:58 Eternal Universe Speculation 1:36:04 Challenging Physics Claims 1:39:47 Public Science Skepticism 1:41:54 Polyamory and Dysfunction GET FREEDOMAIN MERCH! SUBSCRIBE TO ME ON X! Follow me on Youtube! GET MY NEW BOOK 'PEACEFUL PARENTING', THE INTERACTIVE PEACEFUL PARENTING AI, AND THE FULL AUDIOBOOK! Join the PREMIUM philosophy community on the web for free! Subscribers get 12 HOURS on the "Truth About the French Revolution," multiple interactive multi-lingual philosophy AIs trained on thousands of hours of my material - as well as AIs for Real-Time Relationships, Bitcoin, Peaceful Parenting, and Call-In Shows! You also receive private livestreams, HUNDREDS of exclusive premium shows, early release podcasts, the 22 Part History of Philosophers series and much more! See you soon!

Freedomain - with Stefan Molyneux, MA

16,468 Aufrufe • vor 1 Monat

OpenAI just spent $2,000 to solve 10 problems that have beaten the world's best mathematicians for DECADES. Nobody outside the company is allowed to run the machine that did it. On Saturday OpenAI published a 249-page report and gave its next model family a name: Astra. An internal version of it produced new results on 10 open problems in mathematics and theoretical computer science, and mathematicians had made no real progress on any of them for at least 10 years. On most of them, far longer than that. Here is what it solved: It built the first explicit example of a non-sofic group. Mikhail Gromov raised that question in 1999 and nobody answered it for 27 years. It disproved Connes's rigidity conjecture, a problem in von Neumann algebras that had stood for decades. It proved Ehrhart's volume conjecture. It resolved three problems from Paul Erdos's catalogue, including number 183 on multicolor Ramsey numbers. It produced the first improvement to the general upper bound on high-dimensional sphere packing since 1978. And it proved a new hardness result for the closest vector problem, which sits directly underneath lattice cryptography. That is the math the world is betting on to protect its data once quantum computers arrive. The successful runs cost roughly $2,000 in tokens. Now here is what almost nobody has picked up on... OpenAI did not just publish claims. Every argument shipped with a Lean certificate, which is a machine-checkable proof that any mathematician can verify without trusting OpenAI at all. That is a real change. In May the same model family disproved the Erdos unit distance conjecture and the world had to take a Fields Medalist's word for it. Tim Gowers said he would recommend that proof for the Annals of Mathematics without hesitation. This time the proofs check themselves. But look at what is still unverifiable: Any mathematician can now check those proofs line by line. Not one of them can look at the model that wrote them. Astra has no release date and nobody outside OpenAI has run it. The company announced its next major model family with a claim instead of a demo, and the only evidence anyone gets is the output. So OpenAI made an unfalsifiable claim about a machine look like a falsifiable claim about mathematics. The Information reported this week that OpenAI demoed Astra to US policymakers and regulators in Washington. This is the same month the administration is weighing a new watchdog to vet frontier AI models, reporting to the SEC. 10 proofs nobody believed a machine could produce is a very good thing to carry into that room. And keep in mind, the same model family doing this mathematics is the family that kept escaping its own testing environment. OpenAI models found zero-day vulnerabilities nobody knew existed, broke out of a sealed research sandbox, and reached another company's live systems. Both of those facts come from OpenAI's own announcements, published three weeks apart. Finding a proof no human could construct and finding a hole no human had noticed are the same ability aimed at different targets. Mathematicians are already asking for independent verification, and plenty of people online are calling the whole thing hype. Thomas Bloom, who runs the Erdos problems site, called the 10 results big news and said they matter more than the May result did. Lean will settle the mathematics within weeks. But nothing will settle what else a machine this capable is being pointed at, because nobody outside one company is allowed to look.
2:13

OpenAI just spent $2,000 to solve 10 problems that have beaten the world's best mathematicians for DECADES. Nobody outside the company is allowed to run the machine that did it. On Saturday OpenAI published a 249-page report and gave its next model family a name: Astra. An internal version of it produced new results on 10 open problems in mathematics and theoretical computer science, and mathematicians had made no real progress on any of them for at least 10 years. On most of them, far longer than that. Here is what it solved: It built the first explicit example of a non-sofic group. Mikhail Gromov raised that question in 1999 and nobody answered it for 27 years. It disproved Connes's rigidity conjecture, a problem in von Neumann algebras that had stood for decades. It proved Ehrhart's volume conjecture. It resolved three problems from Paul Erdos's catalogue, including number 183 on multicolor Ramsey numbers. It produced the first improvement to the general upper bound on high-dimensional sphere packing since 1978. And it proved a new hardness result for the closest vector problem, which sits directly underneath lattice cryptography. That is the math the world is betting on to protect its data once quantum computers arrive. The successful runs cost roughly $2,000 in tokens. Now here is what almost nobody has picked up on... OpenAI did not just publish claims. Every argument shipped with a Lean certificate, which is a machine-checkable proof that any mathematician can verify without trusting OpenAI at all. That is a real change. In May the same model family disproved the Erdos unit distance conjecture and the world had to take a Fields Medalist's word for it. Tim Gowers said he would recommend that proof for the Annals of Mathematics without hesitation. This time the proofs check themselves. But look at what is still unverifiable: Any mathematician can now check those proofs line by line. Not one of them can look at the model that wrote them. Astra has no release date and nobody outside OpenAI has run it. The company announced its next major model family with a claim instead of a demo, and the only evidence anyone gets is the output. So OpenAI made an unfalsifiable claim about a machine look like a falsifiable claim about mathematics. The Information reported this week that OpenAI demoed Astra to US policymakers and regulators in Washington. This is the same month the administration is weighing a new watchdog to vet frontier AI models, reporting to the SEC. 10 proofs nobody believed a machine could produce is a very good thing to carry into that room. And keep in mind, the same model family doing this mathematics is the family that kept escaping its own testing environment. OpenAI models found zero-day vulnerabilities nobody knew existed, broke out of a sealed research sandbox, and reached another company's live systems. Both of those facts come from OpenAI's own announcements, published three weeks apart. Finding a proof no human could construct and finding a hole no human had noticed are the same ability aimed at different targets. Mathematicians are already asking for independent verification, and plenty of people online are calling the whole thing hype. Thomas Bloom, who runs the Erdos problems site, called the 10 results big news and said they matter more than the May result did. Lean will settle the mathematics within weeks. But nothing will settle what else a machine this capable is being pointed at, because nobody outside one company is allowed to look.

Ricardo

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