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"The enterprise's ability to leverage this depends on its ability to create training data as fast as it can. Not enough people are focused on training data. I need to get into the brains of the people who solve these problems, extract that knowledge, and codify it so I... show more

Harry Stebbings

599,817 subscribers

26,924 次观看 • 1 天前 •via X (Twitter)

科学技术教育新闻政治

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Why data is a trillion-dollar market "The bigger models scale, the more data you need. Data is a very durable need. If you believe in the scaling of models, then absolutely you should believe in the data market. I believe it's going to be at least a $100BN by 2030, if not $1TRN." Anastasios Nikolas Angelopoulos Do you have to scale into enterprise and mid-market to get this revenue scale or could you do it on frontier lab spend alone? Brendan (can/do) Garrett Lord Jonathan Siddharth Ali Ansari

Why data is a trillion-dollar market "The bigger models scale, the more data you need. Data is a very durable need. If you believe in the scaling of models, then absolutely you should believe in the data market. I believe it's going to be at least a $100BN by 2030, if not $1TRN." Anastasios Nikolas Angelopoulos Do you have to scale into enterprise and mid-market to get this revenue scale or could you do it on frontier lab spend alone? Brendan (can/do) Garrett Lord Jonathan Siddharth Ali Ansari

Harry Stebbings

20,227 次观看 • 4 天前

"What is P vs NP and how does it relate to human knowledge?" Avi Wigderson (Turing Award & Abel Prize winner): "In a very basic way, all the problems we want to solve are really NP problems. A subset of it is the problems we can solve. So the question of P versus NP is whether we can solve all the problems we want to solve, whether we can know everything we want to know. This is basically about the limits of our knowledge. You can think there is no limit to what we may want to know but I claim that essentially in any human endeavor, what people are searching for have the property that when a solution is found, it is easily recognized. NP are all problems that we can honestly say we really want to solve and P are those that we can solve. Whether they are equal is just the very fact that a solution can be easily recognized would imply that it can be efficiently found. That means that we can know everything we ever want to know, it's a fundamental question about human knowledge."

"What is P vs NP and how does it relate to human knowledge?" Avi Wigderson (Turing Award & Abel Prize winner): "In a very basic way, all the problems we want to solve are really NP problems. A subset of it is the problems we can solve. So the question of P versus NP is whether we can solve all the problems we want to solve, whether we can know everything we want to know. This is basically about the limits of our knowledge. You can think there is no limit to what we may want to know but I claim that essentially in any human endeavor, what people are searching for have the property that when a solution is found, it is easily recognized. NP are all problems that we can honestly say we really want to solve and P are those that we can solve. Whether they are equal is just the very fact that a solution can be easily recognized would imply that it can be efficiently found. That means that we can know everything we ever want to know, it's a fundamental question about human knowledge."

Ryan Peterman

20,069 次观看 • 2 个月前

One day, we need to talk about this idea that “someone must already have a skill before they can join certain units to serve God.” What do you mean I have to know a lot about music before I can join the choir? I’m not even asking for a microphone. I just want the opportunity to learn, grow, and faithfully attend rehearsals. And before anyone says, “Go to music school,” it doesn’t work that way. Should I leave medical school just to study music? I think the most important thing is having the passion and willingness to learn that craft so you can serve the Lord well. I’ve seen people join the media unit with little or no prior knowledge, receive consistent training, and today they’re doing amazingly well and serving effectively. Not every willing servant starts as an expert. Sometimes the ministry should be where the training begins.

One day, we need to talk about this idea that “someone must already have a skill before they can join certain units to serve God.” What do you mean I have to know a lot about music before I can join the choir? I’m not even asking for a microphone. I just want the opportunity to learn, grow, and faithfully attend rehearsals. And before anyone says, “Go to music school,” it doesn’t work that way. Should I leave medical school just to study music? I think the most important thing is having the passion and willingness to learn that craft so you can serve the Lord well. I’ve seen people join the media unit with little or no prior knowledge, receive consistent training, and today they’re doing amazingly well and serving effectively. Not every willing servant starts as an expert. Sometimes the ministry should be where the training begins.

Tife of CCI🥰❤️

54,731 次观看 • 14 天前

"If you're an analytical SaaS company, it's over. It's over." - Palo Alto Networks CEO Nikesh Arora "What is an analytical SaaS company? It is a company that says, “I'm going to collect a lot of data for you and analyze it for you.” I don't need you to analyze it for me. I can run models against the data and analyze it myself. Think about it: almost every SaaS company has a marketplace. You can buy applications from the Salesforce Marketplace. What do those applications say? “You have Salesforce data. I'm a marketplace app. Use me, and I'll help you analyze that data.” But I don't need to do that. You don't need those applications anymore. I can simply run an LLM against the data. Therefore, all the additional functionality that has traditionally been sold to us as incremental software modules may no longer need to be sold separately. I would much rather have an LLM run against the data." ---- From "All-In Podcast" YouTube channel, (full video link in comment)

"If you're an analytical SaaS company, it's over. It's over." - Palo Alto Networks CEO Nikesh Arora "What is an analytical SaaS company? It is a company that says, “I'm going to collect a lot of data for you and analyze it for you.” I don't need you to analyze it for me. I can run models against the data and analyze it myself. Think about it: almost every SaaS company has a marketplace. You can buy applications from the Salesforce Marketplace. What do those applications say? “You have Salesforce data. I'm a marketplace app. Use me, and I'll help you analyze that data.” But I don't need to do that. You don't need those applications anymore. I can simply run an LLM against the data. Therefore, all the additional functionality that has traditionally been sold to us as incremental software modules may no longer need to be sold separately. I would much rather have an LLM run against the data." ---- From "All-In Podcast" YouTube channel, (full video link in comment)

Rohan Paul

40,959 次观看 • 5 天前

Me: I discuss in the book—it refers to the state where I know something, you know something, I know that you know it, you know that I know it, I know that you know that I know it, and so on ad infinitum. So it differs a bit from the conventional usage, which just refers to something that everyone knows. Here, everyone has to know that everyone knows. Times Radio Interviewer (Daniel Finkelstein Daniel Finkelstein): Can I use this with reference to the interview that I did yesterday with my brother? My brother’s a professor at City University; he’s president of the university, and there’s a campaign at the moment going on against one of their professors who was in the Israeli Defense Forces in the 1980s. We were having a discussion about how the university was standing up for the free speech of its staff, and I’d begun to wonder, as I went home reading your book on the tube, whether I’d made a big mistake—because the protest against this professor is really just a coordination exercise, isn’t it? And maybe I’d aided it by talking about it. Me: Oh yes—protests are coordination exercises. They’re designed to make private knowledge common knowledge. So, in a repressive regime, everyone may know that they despise the government, but because criticism of the government is punished, people might keep their opinions to themselves, with a result that they really don’t know what their fellow citizens think. Each one might think that they’re the only ones that are disgruntled, and so they can’t fear standing up to—they fear standing up to oppose the regime, because they can be picked off one at a time. If everyone were to protest at once, no government has the firepower to intimidate all its citizens at once. In a public protest, people can see other people there, and they know that the people there see other people there, and that can give them the strength and numbers to oppose the regime—sometimes by literally storming the palace, or sometimes just bringing the machinery of the state to a halt through work stoppages. But the crucial thing is that they are coordinated. They can only be coordinated if everyone knows that everyone knows that they hate the regime. Daniel Finkelstein: I suppose that social media is making people—is increasing the stock of common knowledge. We’re all much more aware of what other people like us, in particular like us, know, and we also know that other people know it, and so on, as you put it, and that makes people have more common knowledge. It’s not making us happier though; maybe we’d be better with less common knowledge? Me: Social media are making us more connected within certain circles—that is, those who are receiving the same texts and feeds that we are. It reduces the pool of, or shrinks the largest pool of common knowledge, namely the whole country, which may have been accessible in a day in which, say, in the United States there were three networks, or in Britain everyone was listening to the BBC. And yes, it probably doesn’t make us as happy, because when everything is public, it means that your reputation is on the line for anything you say or do. It means that since social media allow us to generate common knowledge, not just receive it like in the old days, it means that attacks on people’s reputation can be common knowledge, which means that it’s all the more painful for people on the receiving end of the attack. It may have something to do with the fact that in certain demographics—especially young people whose lives increasingly are online—that there’s that much more social competition, opportunities for gossip and ostracism and demeaning comments, and so on. When Everyone Knows That Everyone Knows . . .: Common Knowledge and the Mysteries of Money, Power, and Everyday Life:

Me: I discuss in the book—it refers to the state where I know something, you know something, I know that you know it, you know that I know it, I know that you know that I know it, and so on ad infinitum. So it differs a bit from the conventional usage, which just refers to something that everyone knows. Here, everyone has to know that everyone knows. Times Radio Interviewer (Daniel Finkelstein Daniel Finkelstein): Can I use this with reference to the interview that I did yesterday with my brother? My brother’s a professor at City University; he’s president of the university, and there’s a campaign at the moment going on against one of their professors who was in the Israeli Defense Forces in the 1980s. We were having a discussion about how the university was standing up for the free speech of its staff, and I’d begun to wonder, as I went home reading your book on the tube, whether I’d made a big mistake—because the protest against this professor is really just a coordination exercise, isn’t it? And maybe I’d aided it by talking about it. Me: Oh yes—protests are coordination exercises. They’re designed to make private knowledge common knowledge. So, in a repressive regime, everyone may know that they despise the government, but because criticism of the government is punished, people might keep their opinions to themselves, with a result that they really don’t know what their fellow citizens think. Each one might think that they’re the only ones that are disgruntled, and so they can’t fear standing up to—they fear standing up to oppose the regime, because they can be picked off one at a time. If everyone were to protest at once, no government has the firepower to intimidate all its citizens at once. In a public protest, people can see other people there, and they know that the people there see other people there, and that can give them the strength and numbers to oppose the regime—sometimes by literally storming the palace, or sometimes just bringing the machinery of the state to a halt through work stoppages. But the crucial thing is that they are coordinated. They can only be coordinated if everyone knows that everyone knows that they hate the regime. Daniel Finkelstein: I suppose that social media is making people—is increasing the stock of common knowledge. We’re all much more aware of what other people like us, in particular like us, know, and we also know that other people know it, and so on, as you put it, and that makes people have more common knowledge. It’s not making us happier though; maybe we’d be better with less common knowledge? Me: Social media are making us more connected within certain circles—that is, those who are receiving the same texts and feeds that we are. It reduces the pool of, or shrinks the largest pool of common knowledge, namely the whole country, which may have been accessible in a day in which, say, in the United States there were three networks, or in Britain everyone was listening to the BBC. And yes, it probably doesn’t make us as happy, because when everything is public, it means that your reputation is on the line for anything you say or do. It means that since social media allow us to generate common knowledge, not just receive it like in the old days, it means that attacks on people’s reputation can be common knowledge, which means that it’s all the more painful for people on the receiving end of the attack. It may have something to do with the fact that in certain demographics—especially young people whose lives increasingly are online—that there’s that much more social competition, opportunities for gossip and ostracism and demeaning comments, and so on. When Everyone Knows That Everyone Knows . . .: Common Knowledge and the Mysteries of Money, Power, and Everyday Life:

Steven Pinker

21,547 次观看 • 7 个月前

Coinbase CEO, Brian Armstrong: Some great insights on how they are using internally hosted AI Agents. "It’s connected to every Slack message, every Google Doc, and every Salesforce data confluence. Now, this is all linked up and the data is all aggregated, so you can ask these agents questions. Every team is using it—legal, finance, everything. It’s like the "Oracle of Coinbase." I’ve started to ask it things that go beyond just simple prompting, like "Hey, can you write this kind of memo for me?" I’m asking these AI agents now, as CEO, "What should I be aware of in the company that I might not be aware of?" It will tell me, "Did you know that there’s actually disagreement on this team about the strategy?" I realized I didn't know that, but the AI does because it can read every Slack message and every Google Doc. Tobi, who is on my board, calls this "reverse prompting." Instead of telling the AI agent what you want to do, you ask it what you should be thinking more about." --- From The All-In Podcast YT channel (link in comment)

Coinbase CEO, Brian Armstrong: Some great insights on how they are using internally hosted AI Agents. "It’s connected to every Slack message, every Google Doc, and every Salesforce data confluence. Now, this is all linked up and the data is all aggregated, so you can ask these agents questions. Every team is using it—legal, finance, everything. It’s like the "Oracle of Coinbase." I’ve started to ask it things that go beyond just simple prompting, like "Hey, can you write this kind of memo for me?" I’m asking these AI agents now, as CEO, "What should I be aware of in the company that I might not be aware of?" It will tell me, "Did you know that there’s actually disagreement on this team about the strategy?" I realized I didn't know that, but the AI does because it can read every Slack message and every Google Doc. Tobi, who is on my board, calls this "reverse prompting." Instead of telling the AI agent what you want to do, you ask it what you should be thinking more about." --- From The All-In Podcast YT channel (link in comment)

Rohan Paul

174,884 次观看 • 4 个月前

"One of the very confusing things about the models right now: how to reconcile the fact that they are doing so well on evals. And you look at the evals and you go, 'Those are pretty hard evals.' But the economic impact seems to be dramatically behind. There is [a possible] explanation. Back when people were doing pre-training, the question of what data to train on was answered, because that answer was everything. So you don't have to think if it's going to be this data or that data. When people do RL training, they say, 'Okay, we want to have this kind of RL training for this thing and that kind of RL training for that thing.' You say, 'Hey, I would love our model to do really well when we release it. I want the evals to look great. What would be RL training that could help on this task?' If you combine this with generalization of the models actually being inadequate, that has the potential to explain a lot of what we are seeing, this disconnect between eval performance and actual real-world performance"

"One of the very confusing things about the models right now: how to reconcile the fact that they are doing so well on evals. And you look at the evals and you go, 'Those are pretty hard evals.' But the economic impact seems to be dramatically behind. There is [a possible] explanation. Back when people were doing pre-training, the question of what data to train on was answered, because that answer was everything. So you don't have to think if it's going to be this data or that data. When people do RL training, they say, 'Okay, we want to have this kind of RL training for this thing and that kind of RL training for that thing.' You say, 'Hey, I would love our model to do really well when we release it. I want the evals to look great. What would be RL training that could help on this task?' If you combine this with generalization of the models actually being inadequate, that has the potential to explain a lot of what we are seeing, this disconnect between eval performance and actual real-world performance"

Dwarkesh Patel

502,249 次观看 • 8 个月前

Sen. Josh Hawley at NatCon 5 on AI and copyright theft: Americans should have the ability to defend their human data and their rights to that data against what is amounting to the largest copyright threat in the world. Many of you have online profiles and writings and creative productions that you care deeply about. It's your work, belongs to you. But get this: LLMs have already trained on enough copyrighted works to fill the Library of Congress 22 times over. As I look out across the room and see many authors, all of your works have already been taken. Did they consult you? I doubt it. Did they compensate you? Of course not. This is wrong. This is dangerous. We should empower human beings to protect the very human data that they create. -Assign property rights to specific forms of data. -Create legal liability for the companies who use that data. -Fully repeal Second 230. Open the courtroom doors. Allow people who have their rights taken away to sue, including suing companies and actors and individuals who use AI.

Sen. Josh Hawley at NatCon 5 on AI and copyright theft: Americans should have the ability to defend their human data and their rights to that data against what is amounting to the largest copyright threat in the world. Many of you have online profiles and writings and creative productions that you care deeply about. It's your work, belongs to you. But get this: LLMs have already trained on enough copyrighted works to fill the Library of Congress 22 times over. As I look out across the room and see many authors, all of your works have already been taken. Did they consult you? I doubt it. Did they compensate you? Of course not. This is wrong. This is dangerous. We should empower human beings to protect the very human data that they create. -Assign property rights to specific forms of data. -Create legal liability for the companies who use that data. -Fully repeal Second 230. Open the courtroom doors. Allow people who have their rights taken away to sue, including suing companies and actors and individuals who use AI.

National Conservatism

26,004 次观看 • 11 个月前

Fetterman: What I am saying is like as a Democrat you know I will absolutely call this out who they are you know like I would never pretend to say anything good about any of this new crop of people that are coming into congress so I refuse to do that. Why can’t you just say that? You know every time you tell voters to say oh it’s ok, no problem here, no problem here, people—people though they have eyes, they have ears, they’re appalled by it to across you know people then you lose your credibility. So, so, that’s, that’s the way every Democrat should. We should poli—we should poli—we should police our own ranks right now and say look, you know this is a not a big tent kind of situation. These are people that have intensely extreme Anti-American kinds of of of views. And now, you seen the new polls. You know, 45% of Democrats are only proud to be American. You know.

Fetterman: What I am saying is like as a Democrat you know I will absolutely call this out who they are you know like I would never pretend to say anything good about any of this new crop of people that are coming into congress so I refuse to do that. Why can’t you just say that? You know every time you tell voters to say oh it’s ok, no problem here, no problem here, people—people though they have eyes, they have ears, they’re appalled by it to across you know people then you lose your credibility. So, so, that’s, that’s the way every Democrat should. We should poli—we should poli—we should police our own ranks right now and say look, you know this is a not a big tent kind of situation. These are people that have intensely extreme Anti-American kinds of of of views. And now, you seen the new polls. You know, 45% of Democrats are only proud to be American. You know.

Acyn

175,560 次观看 • 1 个月前

Mark Cuban says anyone can become a millionaire by following these 4 rules #1: “Find something you can be good at and then be great at it” #2: “You have to know how to sell. Whatever it is you’re good at, somebody’s gonna need that service, someone’s gonna need that product” “Whatever it is that you’re creating but you have to be able to sell because you don’t wanna be in a position where you’re dependent on other people” #3: “Be curious and always be learning because one thing that’s certain about business is that it changes every single day” #4: “When you have that knowledge and you have that ability to sell, when you know that when you walk into a room, you know your stuff better than anybody else in the room, that’s when it’s time to start a company” “Then you can start to control your own destiny”

Mark Cuban says anyone can become a millionaire by following these 4 rules #1: “Find something you can be good at and then be great at it” #2: “You have to know how to sell. Whatever it is you’re good at, somebody’s gonna need that service, someone’s gonna need that product” “Whatever it is that you’re creating but you have to be able to sell because you don’t wanna be in a position where you’re dependent on other people” #3: “Be curious and always be learning because one thing that’s certain about business is that it changes every single day” #4: “When you have that knowledge and you have that ability to sell, when you know that when you walk into a room, you know your stuff better than anybody else in the room, that’s when it’s time to start a company” “Then you can start to control your own destiny”

Jack

82,641 次观看 • 2 个月前

MAJOR Developments In The Idaho Farmland Water Shutoff Story 🚨 Not only are they putting millions into cobalt mining in the area but Mark Zuckerberg META is opening huge data centers, some a million square feet, that need the Idaho groundwater for the facilities “That is where we can get cobalt out of the ground in the United States. So they put $15, 000, 000 out of the this cobalt mine in in Idaho hasn't been profitable. I mean, it was purchased from a Canadian company in 2019. They reopened it in 2022, then they shut it down because it just wasn't profitable. Um, but now that they've got the DOD coming in and funding them through the Ukraine bill, you know, they're they're back on track. They're they're exploring, they're finding new cobalt, they're finding ways to extract that cobalt, and the the entire mine is moving forward. So that is a major water user. The other major user in this area, I don't know if you guys have been paying attention to this, but META is opening these massive data centers, close to a million square feet in some locations. And they're opening 1 right there in Idaho. And they're going to be another competitor for groundwater because they use a ton of groundwater to cool their system. Some people said as much as an Olympic swimming Olympic swimming pools are 660,000 gallons. They're using as much as 2,500,000 gallons of water a day to cool their systems. And these databases are also important to our government because our government is able to access information on its constituents, citizens without their knowledge. I mean, think about it. Every time you post something on Facebook or you're you're searching on Facebook, do you, you don't think about the fact that everything you do, every move you make, that that system is tracking you, learning you, learning what your face looks like, learning what your kids look like. Facebook data centers are one of the most important things to our government, and they're putting these data centers in everywhere, and they're constantly taking water rights away from US citizens, US farms, just to put in a data center so they could have more information on you. So that's 2 big things that I think the farmers in Idaho are facing right now. 2 major water users are coming in.”

MAJOR Developments In The Idaho Farmland Water Shutoff Story 🚨 Not only are they putting millions into cobalt mining in the area but Mark Zuckerberg META is opening huge data centers, some a million square feet, that need the Idaho groundwater for the facilities “That is where we can get cobalt out of the ground in the United States. So they put $15, 000, 000 out of the this cobalt mine in in Idaho hasn't been profitable. I mean, it was purchased from a Canadian company in 2019. They reopened it in 2022, then they shut it down because it just wasn't profitable. Um, but now that they've got the DOD coming in and funding them through the Ukraine bill, you know, they're they're back on track. They're they're exploring, they're finding new cobalt, they're finding ways to extract that cobalt, and the the entire mine is moving forward. So that is a major water user. The other major user in this area, I don't know if you guys have been paying attention to this, but META is opening these massive data centers, close to a million square feet in some locations. And they're opening 1 right there in Idaho. And they're going to be another competitor for groundwater because they use a ton of groundwater to cool their system. Some people said as much as an Olympic swimming Olympic swimming pools are 660,000 gallons. They're using as much as 2,500,000 gallons of water a day to cool their systems. And these databases are also important to our government because our government is able to access information on its constituents, citizens without their knowledge. I mean, think about it. Every time you post something on Facebook or you're you're searching on Facebook, do you, you don't think about the fact that everything you do, every move you make, that that system is tracking you, learning you, learning what your face looks like, learning what your kids look like. Facebook data centers are one of the most important things to our government, and they're putting these data centers in everywhere, and they're constantly taking water rights away from US citizens, US farms, just to put in a data center so they could have more information on you. So that's 2 big things that I think the farmers in Idaho are facing right now. 2 major water users are coming in.”

Wall Street Apes

471,888 次观看 • 2 年前

Jaylen Brown on teaming up with LeBron: "I love learning, so to have the opportunity to learn from one if, if not the greatest player of all time ... On the court, off the court, learn and gather experiences that can accumulate to my own knowledge base."

Jaylen Brown on teaming up with LeBron: "I love learning, so to have the opportunity to learn from one if, if not the greatest player of all time ... On the court, off the court, learn and gather experiences that can accumulate to my own knowledge base."

Underdog NBA

335,292 次观看 • 5 天前

Mark Cuban says there are four rules anyone must follow if they want to become a millionaire "If you want to be a millionaire, you can do it. But there's a couple of things you have to be able to accomplish. Rule number one, find something you can be good at and then be great at it." "Second, you have to know how to sell. Whatever it is you're good at, somebody's going to need that service. Someone's going to need that, whatever it is that you're creating. But you have to be able to sell because you don't want to be in a position where you're dependent on other people." "Number three, be curious and always be learning. Because the one thing that's certain about business is that it changes every single day." "And then the fourth thing, when you have that knowledge, when you have that ability to sell,"

Mark Cuban says there are four rules anyone must follow if they want to become a millionaire "If you want to be a millionaire, you can do it. But there's a couple of things you have to be able to accomplish. Rule number one, find something you can be good at and then be great at it." "Second, you have to know how to sell. Whatever it is you're good at, somebody's going to need that service. Someone's going to need that, whatever it is that you're creating. But you have to be able to sell because you don't want to be in a position where you're dependent on other people." "Number three, be curious and always be learning. Because the one thing that's certain about business is that it changes every single day." "And then the fourth thing, when you have that knowledge, when you have that ability to sell,"

Lunix Twin

176,381 次观看 • 1 个月前

So here’s the deal, THE TREASURY DEPARTMENT DATA IS COMPROMISED. Actors without security clearance have been given access to scrape your data. Elon Musk now controls your data and it represents the same level of control exerted by the Chinese government’s social credit system. Musk is now able to profile every name on the treasury data systems. There is no way to sugar coat the fact that your data is no longer secure. It can now be used to target you and not for your benefit, be sure of that. Democrats and advocacy groups can take all the legal action they like, THE DATA IS COMPROMISED and you can’t put the genie back in the bottle. This data can now be used to literally social engineer services to target any perceived enemy of ‘the state’. Call me a conspiracy theorist if you like, but then sit back have a think if any of what I am suggesting is not possible. I analyse big data for a living and I have no solution to this problem and neither does any Democrat telling you it can be fixed.

𝔗𝔯𝔲𝔱𝔥 𝔐𝔞𝔱𝔱𝔢𝔯𝔰

16,366 次观看 • 1 年前

🚨NEW: Joe Rogan: "How crazy is it that Biden deported 1.49 million while letting in 20?" "Like, what do you think they were doing!?" "I know there was also efforts to move people to specific states so that you can get a larger number for the census so you get more congressional seats." "This is a dark thing that people don't want to admit because they're a dyed-in-the-wool Democrat." "I had a conversation with my parents about it and they're like, 'No!' I'm like, 'Yes! It's about congressional seats. It's like, the census counts illegals!'" "And not only that, they're trying to make it so that those people can vote!" "And if you can make it so that those people can vote, then all of the sudden you ship these people to a place, you give them EBT cards, you get them on food stamps, you give them Medicaid money — they have money." "And now, who are you going to vote for? You're going to vote for the people who got you money!" Daily Caller

🚨NEW: Joe Rogan: "How crazy is it that Biden deported 1.49 million while letting in 20?" "Like, what do you think they were doing!?" "I know there was also efforts to move people to specific states so that you can get a larger number for the census so you get more congressional seats." "This is a dark thing that people don't want to admit because they're a dyed-in-the-wool Democrat." "I had a conversation with my parents about it and they're like, 'No!' I'm like, 'Yes! It's about congressional seats. It's like, the census counts illegals!'" "And not only that, they're trying to make it so that those people can vote!" "And if you can make it so that those people can vote, then all of the sudden you ship these people to a place, you give them EBT cards, you get them on food stamps, you give them Medicaid money — they have money." "And now, who are you going to vote for? You're going to vote for the people who got you money!" Daily Caller

Jason Cohen 🇺🇸

259,092 次观看 • 11 个月前

Why aren't more people talking about how difficult it is to turn documents into structured data? This is literally a problem that every single company I talk to is trying to solve. They have a buttload of documents with forms and tables, and they want to turn them into usable data. Let me show you how you can do this using Tensorlake. Probably the best parser I've found:

Why aren't more people talking about how difficult it is to turn documents into structured data? This is literally a problem that every single company I talk to is trying to solve. They have a buttload of documents with forms and tables, and they want to turn them into usable data. Let me show you how you can do this using Tensorlake. Probably the best parser I've found:

Santiago

46,413 次观看 • 1 年前

.gabriel on learning without a map: When you’re not surrounded by startup culture, everything feels impossible. If everyone around you talks about startups, it feels obvious. What can change everything is getting into the market as fast as possible. Solving real problems. Having accountability. And now, with ChatGPT, you don’t even need to know everything upfront. You just need to prove you’re high-agency, that you can ask the right questions, learn fast, and build. Show creativity. Show initiative. Show you can extract information. The rest? figure it out while building.

.gabriel on learning without a map: When you’re not surrounded by startup culture, everything feels impossible. If everyone around you talks about startups, it feels obvious. What can change everything is getting into the market as fast as possible. Solving real problems. Having accountability. And now, with ChatGPT, you don’t even need to know everything upfront. You just need to prove you’re high-agency, that you can ask the right questions, learn fast, and build. Show creativity. Show initiative. Show you can extract information. The rest? figure it out while building.

Extraordinary

13,693 次观看 • 7 个月前

Minnesotans deserve a government that can carry its weight and match their drive and ambition. If you give me the opportunity to serve as your governor, I will work every day to build a government that solves problems and delivers results for the people it serves.

Minnesotans deserve a government that can carry its weight and match their drive and ambition. If you give me the opportunity to serve as your governor, I will work every day to build a government that solves problems and delivers results for the people it serves.

Amy Klobuchar

18,037 次观看 • 2 个月前

NAVAL: ELON BUILDS THINGS THAT ARE TECHNICALLY HARD BUT OBVIOUSLY USEFUL “Like a lot of us, I'm inspired by Elon, and all the incredible work he's done. So, I don't want to build things that are easy. I want to build things that are hard and interesting. I want to take on more technical risk and less market risk. This is the classic VC learning: You want to build something that, if people get it, if you can deliver it, you know people will want it. It's just hard to build. As opposed to things that you want to build, and you don't know if people will want it.” Source: All-In Podcast, February 14, 2025

NAVAL: ELON BUILDS THINGS THAT ARE TECHNICALLY HARD BUT OBVIOUSLY USEFUL “Like a lot of us, I'm inspired by Elon, and all the incredible work he's done. So, I don't want to build things that are easy. I want to build things that are hard and interesting. I want to take on more technical risk and less market risk. This is the classic VC learning: You want to build something that, if people get it, if you can deliver it, you know people will want it. It's just hard to build. As opposed to things that you want to build, and you don't know if people will want it.” Source: All-In Podcast, February 14, 2025

Mario Nawfal

135,417 次观看 • 1 年前

.Naval: You define wealth in a beautiful way. You talk about wealth as a set of physical transformations that we can affect. So as a society it becomes very clear that knowledge leads directly to wealth creation for everybody. A given individual can obviously affect physical transformations proportional to the resources available to them—but much more proportional to the knowledge available to them. Knowledge is a huge force multiplier. You then define resources as the thing that you combine with knowledge to create wealth. New knowledge allows you to use new things as resources and discard old things that maybe we’re running out of. There are lots of examples of how we’ve done that in the past. For example, in energy we’ve gone from wood to coal to oil to nuclear. But then people say, “Now we’re out of ideas. Now we’re caught up. Now we’re done. There aren’t going to be new ideas, and now we have to freeze the frame and conserve what we have.” The counter to that is, “No, we’ll create new knowledge and have new resources. Don’t worry about the old ones.” Well they say, “If you’re going to have new resources, if you can’t think of them now, it’s not real.” This now gets into the realm of people demanding that if you’re going to claim that new knowledge will be created, you have to name that knowledge now. Otherwise it’s not real. But that seems like a Catch-22. David Deutsch: It does, and it’s a bad argument. I don’t want to claim that the knowledge will be created. We’re fallible; we may not create it. We may destroy ourselves. We may miss the solution that’s right under our nose, so that when the snailiens come from another galaxy and look at us, they’ll say, “How can it possibly be that they failed to do so-and-so when it was right in front of them?” That could happen. I can’t prove or argue that it won’t happen. What I always argue, though, is that we have what it takes. We have everything that it takes to achieve that. If we don’t, it’ll be because of bad choices we have made, not because of constraints imposed on us by the planet or the solar system. Naval: It will be by anti-rational memes that restrict the creation of knowledge and the growth of knowledge. David Deutsch: Maybe. Or maybe it’ll be by well-intentioned errors, which nobody could see why they were errors. Again, it doesn’t take malevolence to make mistakes. Mistakes are the normal condition of humans. All we can do is try to find them. Maybe not destroying the means of correcting errors is the heart of morality; because if there is no way of correcting errors, then sooner or later one of those will get us. Naval: Don’t destroy the means of error correction is the base of morality. I love that. I think about places like North Korea where you can’t have elections and a revolution is very difficult because the gang in charge is armed to the teeth and they’ve destroyed the means of political error correction for a long time. That is a case where humanity is trapped in a local minimum, and it’s very hard to climb out of that hole. If too much of the world falls into that mindset, then we as a species may just stagnate because we’ve lost our biggest advantage. We’ve lost our biggest discovery, which was the ability to make new discoveries.

.Naval: You define wealth in a beautiful way. You talk about wealth as a set of physical transformations that we can affect. So as a society it becomes very clear that knowledge leads directly to wealth creation for everybody. A given individual can obviously affect physical transformations proportional to the resources available to them—but much more proportional to the knowledge available to them. Knowledge is a huge force multiplier. You then define resources as the thing that you combine with knowledge to create wealth. New knowledge allows you to use new things as resources and discard old things that maybe we’re running out of. There are lots of examples of how we’ve done that in the past. For example, in energy we’ve gone from wood to coal to oil to nuclear. But then people say, “Now we’re out of ideas. Now we’re caught up. Now we’re done. There aren’t going to be new ideas, and now we have to freeze the frame and conserve what we have.” The counter to that is, “No, we’ll create new knowledge and have new resources. Don’t worry about the old ones.” Well they say, “If you’re going to have new resources, if you can’t think of them now, it’s not real.” This now gets into the realm of people demanding that if you’re going to claim that new knowledge will be created, you have to name that knowledge now. Otherwise it’s not real. But that seems like a Catch-22. David Deutsch: It does, and it’s a bad argument. I don’t want to claim that the knowledge will be created. We’re fallible; we may not create it. We may destroy ourselves. We may miss the solution that’s right under our nose, so that when the snailiens come from another galaxy and look at us, they’ll say, “How can it possibly be that they failed to do so-and-so when it was right in front of them?” That could happen. I can’t prove or argue that it won’t happen. What I always argue, though, is that we have what it takes. We have everything that it takes to achieve that. If we don’t, it’ll be because of bad choices we have made, not because of constraints imposed on us by the planet or the solar system. Naval: It will be by anti-rational memes that restrict the creation of knowledge and the growth of knowledge. David Deutsch: Maybe. Or maybe it’ll be by well-intentioned errors, which nobody could see why they were errors. Again, it doesn’t take malevolence to make mistakes. Mistakes are the normal condition of humans. All we can do is try to find them. Maybe not destroying the means of correcting errors is the heart of morality; because if there is no way of correcting errors, then sooner or later one of those will get us. Naval: Don’t destroy the means of error correction is the base of morality. I love that. I think about places like North Korea where you can’t have elections and a revolution is very difficult because the gang in charge is armed to the teeth and they’ve destroyed the means of political error correction for a long time. That is a case where humanity is trapped in a local minimum, and it’s very hard to climb out of that hole. If too much of the world falls into that mindset, then we as a species may just stagnate because we’ve lost our biggest advantage. We’ve lost our biggest discovery, which was the ability to make new discoveries.

Deutsch Explains

143,913 次观看 • 2 年前