reSee.it - Tweets Saved By @Slothenater

Slothenater
Posted - July 28, 2025 at 11:56 AM
Saved - July 29, 2025 at 8:25 PM
reSee.it AI Summary
Palantir is a powerful surveillance company that operates behind the scenes, crucial for the CIA, Pentagon, and Wall Street. Founded after 9/11 with CIA funding, it tracks vast amounts of data to predict behaviors and uncover hidden patterns. Its products, Gotham and Foundry, are used by governments and corporations alike, from mapping terrorist networks to optimizing hospital operations. However, its practices raise concerns, such as tracking employees without consent. Now valued at $300 billion, Palantir is deeply embedded in America's data infrastructure, especially after a 2025 executive order mandating data sharing among federal agencies.

@Slothenater - Michael Anderson

CIA can't operate without it. Pentagon can't function without it. And Wall Street can't trade without it. Yet most people have no idea what Palantir does behind closed doors. Here’s how the U.S. government allowed a $300B surveillance company to track your every move: 🧵 https://t.co/CLHZy8BEkQ

@Slothenater - Michael Anderson

Palantir is the most powerful company you’ve never heard of. It’s used to: Hunt terrorists Predict wars Spy on employees Prevent crashes Win F1 races By the end of this thread, you’ll realize it might be watching you too 👇 https://t.co/Y6Jf3luWuK

@Slothenater - Michael Anderson

It all started after 9/11. Peter Thiel had one mission: Build software that stops terrorists before they strike. VCs thought it was paranoid. Too risky. Too weird. Then the CIA stepped in with $2M in funding. Palantir’s first client was America’s spy agency. https://t.co/jmnG8CBGEB

Video Transcript AI Summary
Palantir was started as a military-related software startup. Initially, venture capitalists were unwilling to invest, considering the idea insane. The lack of interest suggested either a high barrier to entry with no competition upon success, or simply that the idea was flawed. A decade later, Palantir still had no competition. While there is more activity in the defense space now compared to the mid-2000s, having zero competition can be beneficial if successful, but might also indicate the idea's unviability.
AI Similar Videos
Full Transcript
Speaker 0: Started Palantir, the idea of trying to do a military related software startup. There was nobody who even wanted to give you money as a venture capitalist. People thought we were insane. Yeah. There was sort of an element where if you could get through, you would have no competition, and then, you know, a decade later, we still had no competition. There's probably a lot more going on in the in the defense space now than there was in the in the mid two thousands. Having zero competition, it's it's good if it works. Maybe it just tells you you're insane.

@Slothenater - Michael Anderson

So what does Palantir actually do? It tracks everything: Phone logs. Content. License plates. Bank records. Surveillance feeds. Then it finds hidden patterns. And predicts what you’ll do before you do it. https://t.co/hCoDI8rMyR

@Slothenater - Michael Anderson

Palantir sells two products. And both are terrifyingly powerful.

@Slothenater - Michael Anderson

Gotham: for militaries, police, and intelligence agencies. Think of it as Google for spies. It can: Map terrorist networks Track targets in real time Uncover hidden relationships This is the software that helped hunt down Osama bin Laden. https://t.co/4aKblhxn5e

Video Transcript AI Summary
Palantir's Meredith discusses the shift to great power competition and the need to deter the next great war. She presents a notional scenario: China conducts military exercises in the South China Sea, while ship detection models identify a buildup of fishing vessels surrounding a Taiwanese port, suggesting a potential blockade. Taiwan's semiconductor production is critical, and any disruption would be disastrous. A Chinese destroyer, the Luoyang, goes dark. Gotham projects likely paths, identifying a dangerous route towards the military exercise and Taiwanese port. Satellite coverage is insufficient, so an aircraft from Okinawa is deployed, using AI models to avoid threats and identify military equipment. The aircraft detects the Luoyang heading north. The commander considers options: sending reinforcements, a manned aircraft, or a freedom of navigation operation. They choose the latter, tasking an American ship. As the ship approaches, the blockade disbands, and the Luoyang continues without incident. Palantir Gotham aims to provide decision-making technology to protect values and make the world safer.
AI Similar Videos
Full Transcript
Speaker 0: I'm Meredith, and I'm a deployment strategist at Palantir. During my time as an active duty Air Force officer, I saw firsthand how hard it is to navigate the fog of war. Over the past twenty years, we've been focused on the counterinsurgency fight. And all that time, our near peer rivals have observed our actions, learned our capabilities, and grown bolder. South China Sea is heating. Vladimir Putin tells The US A North Korean nuclear attack could be a huge Tensions between The US and Iran are at all. Near Taiwan as tensions escalate. Now that the focus is shifting to great power competition, the real question is, can we deter the next great war? As a notional example, an escalation could start with something as simple as the Chinese military conducting a routine exercise in the South China Sea. To see the full picture and make tactical, operational, and strategic decisions, The US and allied forces rely on Palantir. Monitoring the exercise, AI models running on satellite data detect an increased level of military activity. To the north, ship detection models identify an alarming buildup of fishing vessels surrounding a major Taiwanese port. An activity model detects that many of those ships are tied together, suggesting an ulterior motive and increasing the risk of a blockade. The US maintains a national interest in free trade throughout the South China Sea. And as an island, only 90 miles off the coast of Mainland China, Taiwan is especially reliant on freedom of navigation through international waters. This free trade is particularly critical given that Taiwan produces 80% of the world's semiconductors. The device you're watching this on today almost certainly relies on these parts. Any disruption could be disastrous. Disastrous. So as the team watches closely with partner nations, a new alert comes in from Japanese intelligence. The Chinese Luoyang destroyer has gone dark and isn't showing up on intelligence feeds. The ship had previously been docked in a southern naval base, but AI models detect that it's now missing. Gotham fuses data from multiple sources to project likely paths for the Luoyang. The most dangerous routes head east towards both the military exercise and the mounting tensions outside the Taiwanese port. The analyst identifies a key fork to monitor between the routes. To collect more imagery, machine learning models built by academic and commercial partners run on data across all domains. The models determine that satellite coverage alone is not enough to find the ship. Based on what is capable and ready, the system recommends a few alternatives. The best option is an aircraft from Okinawa. Before finalizing the selection, analysts deploy the latest micro models trained to avoid incoming threats, identify military equipment, and detect military ships. The unmanned aircraft receives its mission and prepares for takeoff. Time is ticking, and they need to find the ship quickly. As the aircraft departs, video streams back to headquarters in real time. A ship identification model detects the dimensions, speed, and weapon system of the destroyer headed north. An analyst back in the operations center verifies the detection, which confirms the Luoyang is on the most dangerous path and is only a few hours away from the potential blockade. The commander is briefed on the fast developing situation and examines several human and machine generated courses of action that have been jointly tested and developed in past exercises and simulations. The first option involves sending reinforcements to a nearby base, which may take too long. The second option is to send a manned aircraft over the fishing vessels, which could introduce unnecessary risk. The third option is a freedom of navigation operation, which means positioning an American or allied ship closer to the developing situation. This option appears to have the highest probability of success with the lowest risk. Joint forces decide to task an American ship. Once the choice is selected, a task order is submitted and the American ship quickly alters course. The team watches closely as the operation progresses. And as the American ship approaches, the fishing vessel blockade begins to disband and the Luoyang continues north without incident. While this example was notional, events like these happen more often than you realize, and one wrong move could put millions at risk. In these situations, Palantir Gotham provides those who protect our values with the technology to make decisions at speed and in the process makes the world a safer place.

@Slothenater - Michael Anderson

Foundry: It unifies all your messy internal data. Finance, logistics, HR, supply chain into a single interface. Then it lets companies build apps on top of that data. Airbus uses it to predict failures. Ferrari uses it to win races. Hospitals use it to forecast ICU demand. https://t.co/PniOkd7FlR

Video Transcript AI Summary
Foundry offers an open architecture to connect operations and analytics. It integrates existing data and model tooling within an ontology to build workflows, applications, and capture decisions for continuous learning and improved operations. Foundry encourages data teams to connect data lakes and warehouses as the "nouns" of the enterprise, and analytics teams to integrate models as the "verbs." This combination forms a foundation for business processes. This operating layer enables operational workflows where users contribute knowledge, sophisticated analytics like scenario planning, and the capture of decisions that can be piped to various enterprise systems. This closed-loop system differs from a one-way data assembly line. Foundry provides all necessary components for implementing complex workflows, including data and model integration, an ontology layer with objects, relationships, actions, and business processes, and a workflow layer for application building and self-serve analytics.
AI Similar Videos
Full Transcript
Speaker 0: Think about Foundry as providing an open architecture for closing the loop between operations and analytics. It provides the ability to bring your existing data and model tooling together inside of an ontology, which you can then use to build workflows, applications, and actually capture decisions with to inform better operations over time and continuous learning. With Foundry, we kind of say to kind of everybody in the enterprise, to data teams, bring your data lakes, bring your data warehouses, bring kind of all the data that exists across different systems, and connect that into Foundry as sort of what we think of as the nouns of the enterprise, right, the semantics. And to the analytics teams, we say the same thing. Bring the models, bring the linear programming models, the ML models, the stored procedures, and allow those to be connected into the same foundation as sort of the verbs that go along with the nouns that give you kind of all the business processes. And we think if you can then kind of assemble this operating layer iteratively over time through use cases, you then build out a very powerful foundation to do many things. You can drive more and more kind of operational work flows that are read, write, where business users are contributing their knowledge back into the foundation. You can do kind of more sophisticated analytics, like running scenarios and what if analysis. And critically, you can capture decisions and pipe those to all sorts of different enterprise systems, both new and old. So again, we think by closing the loop, it's a very different architecture than kind of the one way assembly line of data. In terms of how it works, Foundry comes with everything you need from top to bottom to implement complex workflows. This includes data integration, model integration, an ontology layer that encompasses objects and relationships and actions and business processes, an entire workflow layer that includes application building, self serve analytics, and more.

@Slothenater - Michael Anderson

But not all use cases are heroic. In 2012, Palantir partnered with New Orleans police. They crunched arrest records and gang affiliations. Then quietly flagged “high risk” individuals for future crimes. No oversight. No consent. https://t.co/hMHTZR1hOu

@Slothenater - Michael Anderson

JPMorgan used Palantir to spy on employees. Emails, web browsing, badge swipes, phone calls Even executives were tracked without authorization. Nothing inside the building was private. Palantir isn’t just surveillance for governments. It’s surveillance for everyone. https://t.co/vvgrg9emRw

@Slothenater - Michael Anderson

Here’s the wild part: Palantir wasn’t profitable for 17 years. But now? It’s worth $300 billion. As much as Bank of America. And it’s deeply embedded across hospitals, militaries, and federal agencies. https://t.co/B1KsgwSOZM

@Slothenater - Michael Anderson

And 2025 changed everything. In March 2025, Trump signed an executive order. Every federal agency must now share their data. Tax records, health data, immigration files, surveillance logs Palantir’s Foundry is integrating it all. America is becoming one massive database. https://t.co/ZDI8ra0Rwj

@Slothenater - Michael Anderson

And Wall Street loves it. Palantir stock is outpacing the S&P 500. Investors don’t just see a tech company, they see a new kind of infrastructure. It’s no longer a controversial startup… It’s the backbone of America’s surveillance machine. https://t.co/O3y4ROxhKw

@Slothenater - Michael Anderson

But what do you think: Too much power? Or exactly what the world needs? Thanks for reading. If you enjoyed: Follow @Slothenater for more insights like this.

Slothenater
Posted - July 28, 2025 at 11:56 AM
Saved - July 28, 2025 at 5:35 PM
reSee.it AI Summary
Palantir, a $300 billion surveillance company, plays a crucial role for the CIA, Pentagon, and Wall Street, yet remains largely unknown to the public. Founded post-9/11 with CIA funding, it tracks extensive data to predict actions and identify patterns. Its products, Gotham and Foundry, serve military and corporate clients, mapping networks and unifying data. Controversially, it has been used for employee surveillance and profiling individuals without consent. Recent executive orders have further integrated federal data, solidifying Palantir's role in national surveillance.

@Slothenater - Michael Anderson

CIA can't operate without it. Pentagon can't function without it. And Wall Street can't trade without it. Yet most people have no idea what Palantir does behind closed doors. Here’s how the U.S. government allowed a $300B surveillance company to track your every move: 🧵 https://t.co/CLHZy8BEkQ

@Slothenater - Michael Anderson

Palantir is the most powerful company you’ve never heard of. It’s used to: Hunt terrorists Predict wars Spy on employees Prevent crashes Win F1 races By the end of this thread, you’ll realize it might be watching you too 👇 https://t.co/Y6Jf3luWuK

@Slothenater - Michael Anderson

It all started after 9/11. Peter Thiel had one mission: Build software that stops terrorists before they strike. VCs thought it was paranoid. Too risky. Too weird. Then the CIA stepped in with $2M in funding. Palantir’s first client was America’s spy agency. https://t.co/jmnG8CBGEB

Video Transcript AI Summary
Palantir was started as a military-related software startup, but initially, no venture capitalists wanted to invest, thinking the idea was insane. The lack of interest suggested that success would mean little to no competition, which proved true for a decade. While there's more activity in the defense space now compared to the mid-2000s, having zero competition can be beneficial if it works, but it might also indicate the idea is flawed.
AI Similar Videos
Full Transcript
Speaker 0: Started Palantir, the idea of trying to do a military related software startup. There was nobody who even wanted to give you money as a venture capitalist. People thought we were insane. Yeah. There was sort of an element where if you could get through, you would have no competition, and then, you know, a decade later, we still had no competition. There's probably a lot more going on in the in the defense space now than there was in the in the mid two thousands. Having zero competition, it's it's good if it works. Maybe it just tells you you're insane.

@Slothenater - Michael Anderson

So what does Palantir actually do? It tracks everything: Phone logs. Content. License plates. Bank records. Surveillance feeds. Then it finds hidden patterns. And predicts what you’ll do before you do it. https://t.co/hCoDI8rMyR

@Slothenater - Michael Anderson

Palantir sells two products. And both are terrifyingly powerful.

@Slothenater - Michael Anderson

Gotham: for militaries, police, and intelligence agencies. Think of it as Google for spies. It can: Map terrorist networks Track targets in real time Uncover hidden relationships This is the software that helped hunt down Osama bin Laden. https://t.co/4aKblhxn5e

Video Transcript AI Summary
Palantir's Meredith, a former Air Force officer, highlights the shift to great power competition and the need to deter major conflicts. She uses a notional example of escalating tensions in the South China Sea, beginning with a Chinese military exercise. AI models detect increased military activity and a potential blockade of a Taiwanese port by fishing vessels. A Chinese destroyer, the Luoyang, goes missing, and Gotham projects its likely paths. An aircraft is deployed to locate the ship, confirming it's heading towards the potential blockade. The commander considers options, including reinforcements, a manned aircraft, and a freedom of navigation operation. They choose to task an American ship, which causes the blockade to disband and the Luoyang to continue without incident. Palantir Gotham aims to provide decision-makers with the technology to act quickly and promote global safety.
AI Similar Videos
Full Transcript
Speaker 0: I'm Meredith, and I'm a deployment strategist at Palantir. During my time as an active duty Air Force officer, I saw firsthand how hard it is to navigate the fog of war. Over the past twenty years, we've been focused on the counterinsurgency fight. And all that time, our near peer rivals have observed our actions, learned our capabilities, and grown bolder. South China Sea is heating. Vladimir Putin tells The US A North Korean nuclear attack could be a huge Tensions between The US and Iran are at all. Near Taiwan as tensions escalate. Now that the focus is shifting to great power competition, the real question is, can we deter the next great war? As a notional example, an escalation could start with something as simple as the Chinese military conducting a routine exercise in the South China Sea. To see the full picture and make tactical, operational, and strategic decisions, The US and allied forces rely on Palantir. Monitoring the exercise, AI models running on satellite data detect an increased level of military activity. To the north, ship detection models identify an alarming buildup of fishing vessels surrounding a major Taiwanese port. An activity model detects that many of those ships are tied together, suggesting an ulterior motive and increasing the risk of a blockade. The US maintains a national interest in free trade throughout the South China Sea. And as an island, only 90 miles off the coast of Mainland China, Taiwan is especially reliant on freedom of navigation through international waters. This free trade is particularly critical given that Taiwan produces 80% of the world's semiconductors. The device you're watching this on today almost certainly relies on these parts. Any disruption could be disastrous. Disastrous. So as the team watches closely with partner nations, a new alert comes in from Japanese intelligence. The Chinese Luoyang destroyer has gone dark and isn't showing up on intelligence feeds. The ship had previously been docked in a southern naval base, but AI models detect that it's now missing. Gotham fuses data from multiple sources to project likely paths for the Luoyang. The most dangerous routes head east towards both the military exercise and the mounting tensions outside the Taiwanese port. The analyst identifies a key fork to monitor between the routes. To collect more imagery, machine learning models built by academic and commercial partners run on data across all domains. The models determine that satellite coverage alone is not enough to find the ship. Based on what is capable and ready, the system recommends a few alternatives. The best option is an aircraft from Okinawa. Before finalizing the selection, analysts deploy the latest micro models trained to avoid incoming threats, identify military equipment, and detect military ships. The unmanned aircraft receives its mission and prepares for takeoff. Time is ticking, and they need to find the ship quickly. As the aircraft departs, video streams back to headquarters in real time. A ship identification model detects the dimensions, speed, and weapon system of the destroyer headed north. An analyst back in the operations center verifies the detection, which confirms the Luoyang is on the most dangerous path and is only a few hours away from the potential blockade. The commander is briefed on the fast developing situation and examines several human and machine generated courses of action that have been jointly tested and developed in past exercises and simulations. The first option involves sending reinforcements to a nearby base, which may take too long. The second option is to send a manned aircraft over the fishing vessels, which could introduce unnecessary risk. The third option is a freedom of navigation operation, which means positioning an American or allied ship closer to the developing situation. This option appears to have the highest probability of success with the lowest risk. Joint forces decide to task an American ship. Once the choice is selected, a task order is submitted and the American ship quickly alters course. The team watches closely as the operation progresses. And as the American ship approaches, the fishing vessel blockade begins to disband and the Luoyang continues north without incident. While this example was notional, events like these happen more often than you realize, and one wrong move could put millions at risk. In these situations, Palantir Gotham provides those who protect our values with the technology to make decisions at speed and in the process makes the world a safer place.

@Slothenater - Michael Anderson

Foundry: It unifies all your messy internal data. Finance, logistics, HR, supply chain into a single interface. Then it lets companies build apps on top of that data. Airbus uses it to predict failures. Ferrari uses it to win races. Hospitals use it to forecast ICU demand. https://t.co/PniOkd7FlR

Video Transcript AI Summary
Foundry provides an open architecture for closing the loop between operations and analytics. It allows users to bring existing data and model tooling together inside of an ontology to build workflows, applications, and capture decisions to inform better operations and continuous learning. Data teams can bring data lakes and warehouses into Foundry as the nouns of the enterprise. Analytics teams can bring models, linear programming models, ML models, and stored procedures as the verbs. Assembling this operating layer iteratively builds a foundation to drive operational workflows, conduct sophisticated analytics, and capture decisions to pipe to enterprise systems. Foundry includes data integration, model integration, an ontology layer encompassing objects, relationships, actions, and business processes, and a workflow layer with application building and self-serve analytics.
AI Similar Videos
Full Transcript
Speaker 0: Think about Foundry as providing an open architecture for closing the loop between operations and analytics. It provides the ability to bring your existing data and model tooling together inside of an ontology, which you can then use to build workflows, applications, and actually capture decisions with to inform better operations over time and continuous learning. With Foundry, we kind of say to kind of everybody in the enterprise, to data teams, bring your data lakes, bring your data warehouses, bring kind of all the data that exists across different systems, and connect that into Foundry as sort of what we think of as the nouns of the enterprise, right, the semantics. And to the analytics teams, we say the same thing. Bring the models, bring the linear programming models, the ML models, the stored procedures, and allow those to be connected into the same foundation as sort of the verbs that go along with the nouns that give you kind of all the business processes. And we think if you can then kind of assemble this operating layer iteratively over time through use cases, you then build out a very powerful foundation to do many things. You can drive more and more kind of operational work flows that are read, write, where business users are contributing their knowledge back into the foundation. You can do kind of more sophisticated analytics, like running scenarios and what if analysis. And critically, you can capture decisions and pipe those to all sorts of different enterprise systems, both new and old. So again, we think by closing the loop, it's a very different architecture than kind of the one way assembly line of data. In terms of how it works, Foundry comes with everything you need from top to bottom to implement complex workflows. This includes data integration, model integration, an ontology layer that encompasses objects and relationships and actions and business processes, an entire workflow layer that includes application building, self serve analytics, and more.

@Slothenater - Michael Anderson

But not all use cases are heroic. In 2012, Palantir partnered with New Orleans police. They crunched arrest records and gang affiliations. Then quietly flagged “high risk” individuals for future crimes. No oversight. No consent. https://t.co/hMHTZR1hOu

@Slothenater - Michael Anderson

JPMorgan used Palantir to spy on employees. Emails, web browsing, badge swipes, phone calls Even executives were tracked without authorization. Nothing inside the building was private. Palantir isn’t just surveillance for governments. It’s surveillance for everyone. https://t.co/vvgrg9emRw

@Slothenater - Michael Anderson

Here’s the wild part: Palantir wasn’t profitable for 17 years. But now? It’s worth $300 billion. As much as Bank of America. And it’s deeply embedded across hospitals, militaries, and federal agencies. https://t.co/B1KsgwSOZM

@Slothenater - Michael Anderson

And 2025 changed everything. In March 2025, Trump signed an executive order. Every federal agency must now share their data. Tax records, health data, immigration files, surveillance logs Palantir’s Foundry is integrating it all. America is becoming one massive database. https://t.co/ZDI8ra0Rwj

@Slothenater - Michael Anderson

And Wall Street loves it. Palantir stock is outpacing the S&P 500. Investors don’t just see a tech company, they see a new kind of infrastructure. It’s no longer a controversial startup… It’s the backbone of America’s surveillance machine. https://t.co/O3y4ROxhKw

@Slothenater - Michael Anderson

But what do you think: Too much power? Or exactly what the world needs? Thanks for reading. If you enjoyed: Follow @Slothenater for more insights like this.

Slothenater
Posted - April 14, 2025 at 12:16 PM
Saved - April 15, 2025 at 1:31 PM
reSee.it AI Summary
Intelligent people often make poor decisions, as highlighted by Richard Feynman, a Nobel Prize-winning physicist. He emphasized that our minds can deceive us, leading to distorted perceptions of reality. Feynman's Rule teaches us that we must not fool ourselves, as intelligence can provide justifications for our mistakes. He valued questioning over certainty and was unafraid to admit when he was wrong. Feynman believed in the importance of unlearning and pursuing truth through better questions rather than chasing answers.

@Slothenater - Michael Anderson

Intelligent people make terrible decisions. This Nobel Prize-winning physicist spent 35+ years proving it. He exposed the most dangerous illusion in human thinking. Once you see it, you can’t unsee it. And you’ll question every decision you’ve ever made: 🧵 https://t.co/b2nzd7NMAm

@Slothenater - Michael Anderson

1/ This is Richard Feynman: - Nobel Prize in Physics - Helped build the atomic bomb - Solved the Challenger disaster - Rewrote how we think about science But his greatest insight wasn’t about atoms or rockets. It was about human ignorance. https://t.co/z8YNBMrZur

@Slothenater - Michael Anderson

2/ You might think you know yourself. But your mind has been deceiving you your entire life. Just look at this:👇 https://t.co/jNxXrv8Gi6

@Slothenater - Michael Anderson

3/ At first glance, this might look like two squares are different colors. But in reality, they’re the same color. Your brain is tricking you. This is how our mind works—constantly distorting reality. Stay with me, I'll show you how this plays out in real life...

@Slothenater - Michael Anderson

4/ Ever heard of Feynman’s Rule? He said: “The first principle is that you must not fool yourself—and you are the easiest person to fool.” It’s not about what you know. It’s about what you think you know. You’ll see what I mean next… https://t.co/bMUbLJvmia

Video Transcript AI Summary
Richard Feynman, who worked on the Manhattan Project, uncovered the cause of the Challenger disaster, and won a Nobel Prize in Physics, had an IQ of 125. While above average, this IQ is not high enough to qualify for MENSA. Feynman considered himself an ordinary person who studied hard, not a "miracle person." He believed his defining characteristic was his curiosity.
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Full Transcript
Speaker 0: Richard Feynman worked on the Manhattan Project that built the atomic bomb. He uncovered what caused the space shuttle Challenger disaster when no one else could. He won a Nobel Prize in Physics. He accomplished all this with an IQ of one twenty five. You might think that's a pretty high IQ considering the standard is a hundred. However, one in 20 people has that IQ and it isn't high enough to make it into MENSA which accepts only the top 2%, usually a score of one thirty two or higher. I was an ordinary person who studied hard. There's no miracle people. He didn't see himself as anything special, as he said in this BBC interview. But what set him apart was his curiosity.

@Slothenater - Michael Anderson

5/ The smarter you get, the easier it is to fool yourself. Intelligence gives you better reasons to justify your mistakes. But Feynman saw through this. He believed: “I would rather have questions that can't be answered than answers that can't be questioned.” https://t.co/525km1yE4V

Video Transcript AI Summary
The speaker is looking for how everything works and what makes everything work, aiming to view the world from another point of view. They state that just as a runner enjoys sweating, they enjoy "thin feet." The speaker concludes by saying they can't stop and that "it's true nothing."
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Speaker 0: What we're looking for is how everything works. What makes everything work. Take the world from another point of view. Just like a runner gets a kick out of sweating. I get a kick out of thin feet. I can't stop. It's true nothing.

@Slothenater - Michael Anderson

6/ This is the problem: You think you know. But real thinkers don’t chase certainty. They chase not knowing. That’s where Feynman’s genius lies. He didn’t want answers. He wanted better questions. And here’s how that mindset worked for him: https://t.co/STzH2vGYRE

Video Transcript AI Summary
Science may not answer questions about our purpose or the universe's meaning, but that shouldn't lead to mysticism. The goal is to explore and discover more about the world without predetermined expectations, whether a simple ultimate law exists or endless layers. Beliefs about our relationship with the universe seem too localized and disproportionate considering the vastness of space. Doubt and questioning are fundamental. It's acceptable to live with uncertainty rather than rely on potentially wrong answers. Having approximate answers, possible beliefs, and varying degrees of certainty is sufficient. Not knowing doesn't cause fear, even when faced with the possibility of being lost in a mysterious, purposeless universe.
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Full Transcript
Speaker 0: If you expected science to give all the answers to the wonderful questions about what we are, where we're going, what the meaning of the universe is, and so on, then I think you could easily become disillusioned and then look for some mystic answer to these problems. We're exploring. We're trying to find out as much as we can about the world. People say to me, are you looking for the ultimate laws of physics? No. I'm not. I'm just looking to find out more about the world. And if it turns out there is a simple ultimate law that explains everything, so be it. That would be very nice to discover. If it turns out it's like an onion with millions of layers and we're just sick and tired of looking at the layers, then that's the way it is. But whatever way it comes out, its nature is there and she's gonna come out the way she is. And therefore, when we go to investigate it, we shouldn't predecide what it is we're trying to do except to find out more about it. And so altogether, I can't believe the special stories that have been made up about our relationship to the universe at large because they seem to be too local, too provincial. The earth, he came to the earth. One of the aspects of God came to the earth, mind you. And look at what's out there. How can he it isn't in proportion. And also another thing, has to do with the question of how do you find out if something's true. And if you have all these theories of of the different religions, have all different theories about the thing, Then you begin to wonder. Once you start doubting, which I think is to me is a very fundamental part of my soul is to doubt and to ask. And when you doubt and ask, it gets a little harder to believe. I can live without and uncertainty and not knowing. I think it's much more interesting to live not knowing than to have answers which might be wrong. I have approximate answers and possible beliefs and different degrees of certainty about different things, but I'm not absolutely sure of anything and the many things I don't know anything about. But I don't have to know an answer. I don't have I don't feel frightened by not knowing things, by being lost in the mysterious universe without having any purpose, which is the way it really is as far as I can tell possibly. It doesn't frighten me.

@Slothenater - Michael Anderson

7/ Feynman doubted everything, even the things that seemed obvious. He never took things for granted. Every answer led to a new question. So when was the last time you doubted what seemed obvious to you? Stay with me, this is key to unlocking true intelligence… https://t.co/LdH5BiJuFG

Video Transcript AI Summary
Many intelligent people incorrectly answer that Moses took animals on the ark, when it was Noah. This is because they are cognitive misers, capable of reasoning but relying on gut feelings. Cognitive miserliness can cause people to be swayed by irrelevant information and feelings, leading to poor decisions, and making them susceptible to fake news. Arthur Conan Doyle was an intelligent man who understood logical deduction, but in his private life, he was not rational due to his belief in spiritualism. Despite evidence from friends like Harry Houdini that he was being scammed by fraudulent mediums, Doyle used arguments, such as electromagnetic fields, to rationalize the existence of fairies.
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Speaker 0: Consider this question. How many animals of each species did Moses take on the ark? The answer, of course, is zero. It was Noah, not Moses, who was supposed to have built the ark. But many intelligent people get this wrong. They are cognitive misers. They are capable of intelligent reasoning, but they don't apply that brainpower effectively, instead relying too much on their gut feelings. Speaker 1: Cognitive miserliness can cause us to be swayed by irrelevant information and our own feelings. For example, leading us to poor financial decisions when buying a house. It can also explain why apparently intelligent people can fall for fake news if they rely too much on the gist rather than details of a statement. Speaker 0: Sometimes, thanks to the emotional pull of an argument, we think, in a very one-sided manner. So Arthur Conan Doyle is the perfect example of motivated reasoning. Now he was obviously an incredibly intelligent man. He was a doctor and also wrote all of the Sherlock Holmes books, where he really shows a very clear understanding of what logical deduction should be. But in his own private life, Arthur Conan Doyle was not nearly so rational. He had a very strong emotional belief in spiritualism and often visited fraudulent mediums. Now, Arthur Conan Doyle's friends, which included Harry Houdini, the illusionist, often tried to persuade him that he was wrong and to show him the evidence that he was being scammed by these people. But Arthur Conan Doyle just didn't believe their arguments. So for instance, he would try to bring in the latest physics on the, electromagnetic field to explain how fairies might exist but just appeared in another wavelength.

@Slothenater - Michael Anderson

8/ Feynman wasn’t afraid to admit when he was wrong. He was constantly learning—and part of that was unlearning. What about you? When was the last time you admitted you didn’t know? Read on, this is the real secret to Feynman’s success… https://t.co/s7ROhhoxEu

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More harm is caused by stupid, incompetent people than by evil people. Phronesis, a Greek concept, is a practical wisdom needed to navigate life. Stupidity stems from the certainty that one has all the answers, often absorbing ideas without critical thought. Leaders who are certain can lead nations into poorly planned wars, referencing the Peloponnesian War where Athenian leaders, certain of victory, failed to consider the consequences. Certainty without thorough consideration makes people stupid, and dangerous when in positions of power. Stupid people are likely more numerous than evil people. Cynicism and the belief of always having the right answer often overlap.
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Speaker 0: That the stupidest people are always the ones who think they have the right answers. Speaker 1: Yeah. Yeah. So getting back to my studies of of the ancient world, which is main main part of of me. One thing that always excited me was this concept of the ancient Greeks that more harm is caused in this world by stupid, incompetent people than by evil people. Right? And what they there's a word in Greek called phronesis, which is a form of wisdom, to use your title here, but it's a form of practical wisdom to be able to get things done, to navigate through life, navigate through people, to be balanced and get things done. Okay? So what makes people stupid and right now, we have a lot of stupid people in this world. There always have been stupid people, but because there are more people on the planet exponentially, there are more stupid people on the planet. What makes people stupid, and I'm sorry, I'm just gonna tell it like it is, is their certainty that they have all the answers. This is what's going on with our government. This is what's wrong, you know, with this or that. This is what people should be like, Blah blah blah blah blah. So you're narrowing your focus to this little tiny little rail, something that you heard from somebody else. It's not even your own stupid idea. So you absorbed it on the Internet, whatever, and you're going down on this this kind of monorail path. Meanwhile, the world is all around you, and you're just going like zoom like that because you're so certain you have the answer. And when you have leaders this is to get back to the Greek thing. When you have leaders who are so certain, they enter they enter a country into a war that have they haven't been thought out of because and and so the paradigm in in ancient culture was the Peloponnesian War of between Athens and Sparta, the war that ended up kind of being the end of Athenian democracy and of their golden era. Right? And it was the idea and Thucydides, one of the greatest writers who ever lived, wrote the history of the Peloponnesian war living at that time. He was saying that people the leaders thought, oh, this will be so easy. And think of all the great things when we go and we take Sicily and we conquer that, the whole world will end the Sparta will be destroyed. Right? It wasn't thought through. They were so certain of the answer that they didn't think of the parameters. Right? They didn't think really on a grand strategic level. So people who are certain of things are very stupid, and when they have power, they're very, very dangerous. I'm not saying evil people aren't dangerous, but incompetent stupid people who are so certain, who haven't thought things through, are just as dangerous as evil people. Speaker 0: I think there's far more stupid people than there are evil people as well. Probably. Probably. Yeah. Yeah. It's very interesting to think about the where the Venn diagram intersects for people who are always cynical and people who always have the right answer or who always know. They go hand in hand. Correct. Speaker 1: Totally overlap. Yeah. Great.

@Slothenater - Michael Anderson

9/ You don’t need all the answers. You need better questions. “The imagination of nature is far greater than the imagination of man.” Feynman understood that reality is much stranger and more complex than we could ever grasp. https://t.co/0bZpK1MGGz

@Slothenater - Michael Anderson

10/ His genius wasn’t in what he knew. It was in how much he was willing to unlearn. Feynman didn’t chase being right. He chased truth. https://t.co/4uNoJaGHZi

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The speaker is writing a book called "Why Smart People Do Dumb Things," and illustrates the concept with an example of decent people who risked what they had and needed to make money they didn't have and didn't need. The speaker believes that risking something important for something unimportant is foolish, regardless of IQ. They give an analogy of being offered money to pull the trigger of a gun with a million chambers and one bullet. The speaker states they would not pull the trigger, as the downside is clear and the upside does nothing for them.
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Speaker 0: A book. It's gonna be called why smart people do dumb things. My partner says that it should be autobiographical, but I but but this might be an interesting illustration. And these are perfectly decent guys. I, you know, I I I I respect them, and they helped me out when I was had problems with Solomon. So they they they are they are not bad people at all. But to make money they didn't have and didn't need, they risked what they did have and did need. And that's foolish. That is just plain foolish. I don't make any difference what your IQ is. If you if you risk something that is important to you for something that is unimportant to you, it just does not make any sense. I don't care whether the odds are a hundred to one that you succeed or a thousand to one that you succeed. If you hand me a gun with a thousand chambers or a million chambers in it, and there's a bullet in one chamber and you said put it up your temple, how much do you want to be paid to pull it once? I'm not gonna pull it. You know, you can name any some you want, but it doesn't do anything for me on the upside. And I think the downside is fairly clear.

@Slothenater - Michael Anderson

I’m Michael. I’ve built 4+ ecom brands to 7-8 figs. And helped 100+ people do the same. Now, I’m helping 3 brand owners scale their brand. If you need my help, comment “Scale.” https://t.co/nu8sr2D8t5

@Slothenater - Michael Anderson

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