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Author of Designing Data-Intensive Applications, Martin Kleppmann, on why scaling down is just as challenging as scaling up: “Part of what is interesting about modern cloud services, and backend services in general, is how they've introduced the idea of horizontal scalability and shared nothing systems. We can build systems...

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The Pragmatic Engineer

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21,239 views • 3 months ago •via X (Twitter)

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“What did you think of Lando being booed at race because people and I've seen it online as well say he doesn't deserve the title because McLaren favored him over his teammate. Do you think that's total nonsense?” Jacques Villeneuve: “That's a little bit ridiculous. When there was some booing in some races, that was embarrassing. You should never boo a driver that's clean, doesn't do anything dirty, on track is respectful, and on top of it is super fast. What's wrong with people? That was embarrassing. And, had it been that Piastri was a second a lap faster than him and somehow Lando was winning because a lot of things were happening, his car breaking down every time, then you could start thinking, okay, that's really not cool. That's not fair. But that wasn't the case. And in the second half, Norris has been faster right at the beginning as well, last year as well. So there's this whole middle of the season where Piastri was driving a lot better than Norris and was getting the points. Norris had an engine blowing up, not Piastri. And so those fans, they don't look at that either. You have to look at the whole picture, at the whole season. And suddenly if your favorite is starting to go backwards, you just got to bite the bullet and accept it. Your favorite is just going backwards. That doesn't mean that the other one is treated better or the other one is undeserving just because the one you're a fan of is not winning right now. That’s really wrong. If you're a fan of the sport, then you have to be a fan of the sport and understand when your driver is maybe not cutting it at this point in time, even though he was before and he will in the future again. It's all a question of timing. But that's the price we have to pay now with social media and how big F1 has become. It's very passionate. The people are passionate and once, you know, fans come from fanatism, you stop thinking, when you get in that mindset and it happens to all of us. You want something so much that you get attached and you cannot - it's hard to start seeing reality. So you will try to mold the reality to your thought process and if your champion is not winning then it cannot be his fault. It has to be something from the outside. It has to be the team destroying his chance or not favoring and so on and so on and so on. But there's nothing concrete behind those comments. It's pure fandom and it'll always be like this. And ultimately it's not a bad thing. You know drivers at that - sportsman at that level have to grow a thick skin. If not, you don't deserve to be there. You just have to have a thick skin because they're all very happy to get the compliments. They love it when it's just positive, but it gets balanced out with negatives and you need to be able to take and accept the negatives as well. It goes both ways. You cannot have the good. You just have to be a thick skin and know that it's part and parcels of what's going on. And in one month, it will be forgotten and maybe everything will change and it be the other driver that suddenly will be criticized and so on. So, it's just that's just the way it is.”
3:10

“What did you think of Lando being booed at race because people and I've seen it online as well say he doesn't deserve the title because McLaren favored him over his teammate. Do you think that's total nonsense?” Jacques Villeneuve: “That's a little bit ridiculous. When there was some booing in some races, that was embarrassing. You should never boo a driver that's clean, doesn't do anything dirty, on track is respectful, and on top of it is super fast. What's wrong with people? That was embarrassing. And, had it been that Piastri was a second a lap faster than him and somehow Lando was winning because a lot of things were happening, his car breaking down every time, then you could start thinking, okay, that's really not cool. That's not fair. But that wasn't the case. And in the second half, Norris has been faster right at the beginning as well, last year as well. So there's this whole middle of the season where Piastri was driving a lot better than Norris and was getting the points. Norris had an engine blowing up, not Piastri. And so those fans, they don't look at that either. You have to look at the whole picture, at the whole season. And suddenly if your favorite is starting to go backwards, you just got to bite the bullet and accept it. Your favorite is just going backwards. That doesn't mean that the other one is treated better or the other one is undeserving just because the one you're a fan of is not winning right now. That’s really wrong. If you're a fan of the sport, then you have to be a fan of the sport and understand when your driver is maybe not cutting it at this point in time, even though he was before and he will in the future again. It's all a question of timing. But that's the price we have to pay now with social media and how big F1 has become. It's very passionate. The people are passionate and once, you know, fans come from fanatism, you stop thinking, when you get in that mindset and it happens to all of us. You want something so much that you get attached and you cannot - it's hard to start seeing reality. So you will try to mold the reality to your thought process and if your champion is not winning then it cannot be his fault. It has to be something from the outside. It has to be the team destroying his chance or not favoring and so on and so on and so on. But there's nothing concrete behind those comments. It's pure fandom and it'll always be like this. And ultimately it's not a bad thing. You know drivers at that - sportsman at that level have to grow a thick skin. If not, you don't deserve to be there. You just have to have a thick skin because they're all very happy to get the compliments. They love it when it's just positive, but it gets balanced out with negatives and you need to be able to take and accept the negatives as well. It goes both ways. You cannot have the good. You just have to be a thick skin and know that it's part and parcels of what's going on. And in one month, it will be forgotten and maybe everything will change and it be the other driver that suddenly will be criticized and so on. So, it's just that's just the way it is.”

naenia ¹ ⁶³

29,833 views • 8 months ago

Ilya Sutskever says the AI scaling era is running out of road because pre-training is about to hit a finite-data wall. "At some point though, pre-training will run out of data. The data is very clearly finite." "Then, okay, what do you do next? Either you do some kind of a souped-up pre-training... or you're doing RL, or maybe something else." "In some sense, we are back to the age of research." His timeline is the part most AI investors and founders should hear: "From 2012 to 2020, it was the age of research. Now from 2020 to 2025, it was the age of scaling... But now the scale is so big." "Is the belief really that... if you had 100x more everything would be so different?" "I don't think that's true. So it's back to the age of research again, just with big computers."
1:10

Ilya Sutskever says the AI scaling era is running out of road because pre-training is about to hit a finite-data wall. "At some point though, pre-training will run out of data. The data is very clearly finite." "Then, okay, what do you do next? Either you do some kind of a souped-up pre-training... or you're doing RL, or maybe something else." "In some sense, we are back to the age of research." His timeline is the part most AI investors and founders should hear: "From 2012 to 2020, it was the age of research. Now from 2020 to 2025, it was the age of scaling... But now the scale is so big." "Is the belief really that... if you had 100x more everything would be so different?" "I don't think that's true. So it's back to the age of research again, just with big computers."

Karl Mehta

200,003 views • 1 month ago

Yann LeCun -- Meta's chief AI scientist and a Turing Award winner -- explains why scaling up LLMs will never reach human-level AI, and names the four things today's systems still can't do: "If you think that we're going to get to human-level AI by just training on more data and scaling up LLMs, you're making a mistake." "If you're an investor and you invest in a company that told you we're going to get to human-level AI and PhD level by just training on more data and with a few tricks... that was probably not a good idea." "There are ideas about how to go forward and have systems that are capable of doing what every intelligent animal and human are capable of doing, and that current AI systems are not capable of doing." "Understanding the physical world, having persistent memory, and being able to reason and plan. Those are the four characteristics that need to be there." "That requires systems that can acquire common sense, that can learn from natural sensors like video, as opposed to just text." The entire market is priced on a straight line from bigger models to AGI. One of the people who invented deep learning is telling you the line doesn't reach -- and that the real bottleneck isn't compute, it's world models. If he's right, the winner isn't whoever stacks the most GPUs. It's whoever teaches a machine to learn from video the way a child does.
0:58

Yann LeCun -- Meta's chief AI scientist and a Turing Award winner -- explains why scaling up LLMs will never reach human-level AI, and names the four things today's systems still can't do: "If you think that we're going to get to human-level AI by just training on more data and scaling up LLMs, you're making a mistake." "If you're an investor and you invest in a company that told you we're going to get to human-level AI and PhD level by just training on more data and with a few tricks... that was probably not a good idea." "There are ideas about how to go forward and have systems that are capable of doing what every intelligent animal and human are capable of doing, and that current AI systems are not capable of doing." "Understanding the physical world, having persistent memory, and being able to reason and plan. Those are the four characteristics that need to be there." "That requires systems that can acquire common sense, that can learn from natural sensors like video, as opposed to just text." The entire market is priced on a straight line from bigger models to AGI. One of the people who invented deep learning is telling you the line doesn't reach -- and that the real bottleneck isn't compute, it's world models. If he's right, the winner isn't whoever stacks the most GPUs. It's whoever teaches a machine to learn from video the way a child does.

Karl Mehta

34,781 views • 1 month ago

Jordan Peterson: "If you can't fix your room, you can't fix your life" "Why should you even bother improving yourself? The answer is something like: so you don't suffer anymore stupidly than you have to. And maybe so others don't have to either. It's not some casual self-help doctrine. If you don't organize yourself properly, you'll pay for it. In a big way. And so will the people around you." Peterson continues: "You can say, 'Well, I don't care about that.' But that's actually not true, you do care about it. Because if you're in pain, you will care about it. It's very rare that you can find someone in excruciating pain who would say, 'Well, it would be no better if I was out of this.' Pain brings the idea that it would be better if it didn't exist along with it. It's incontrovertible." On how to start: "Look around for something that bothers you and see if you can fix it. You can do this in a room. Sit in your bedroom and think: 'If I wanted to spend ten minutes making this room better, what would I have to do?' You have to ask yourself that, it's a genuine question. And things will pop out. There's a stack of papers bugging you. Some rubbish behind your computer monitor you haven't attended to for six months. Cables tangled up." He explains why this matters: "If you were coming to see me for psychotherapy, the easiest thing would be to get you to organize your room. You think, is that psychotherapy? It depends on how you conceive the limits of your being. Start where you can start. If something announces itself as in need of repair that you could repair, fix it. Fix a hundred things like that, your life will be a lot different." On fixing what you repeat every day: "People tend to think of their daily routines as trivial. You get up, brush your teeth, have breakfast. Those probably constitute 50% of your life. People think, they're mundane, I don't need to pay attention to them. No, that's exactly wrong. The things you do every day are the most important things you do. Hands down. Just do the arithmetic." On staying within your competence: "Sometimes you don't know how to fix something. Imagine you're walking down the street and there's a guy who's alcoholic and schizophrenic and has been homeless for ten years. That's a problem. It would be good if you could fix it, but you haven't got a clue. You walk around that and go find something you could fix. Just because something announces itself as in need of repair doesn't mean it's you, right then and there, who should repair it. You have to have some humility. You don't walk up to a helicopter that isn't working and just start tinkering away." Peterson shares the key insight: "As soon as you give your mind a genuine aim, it'll reconfigure the world in keeping with that aim. That's actually how you see to begin with. You've all seen the video where you watch basketballs being tossed back and forth, and while you're doing that, a gorilla walks into the middle of the video and you don't see it. If you thought about that experiment for five years, that would be about the right amount of time to spend thinking about it." He explains what it reveals: "What it shows you is that you see what you aim at. If you can get one thing through your head, that would be a good one. You see what you aim at. One inference you might draw from that is: be careful what you aim at. What you aim at determines the way the world manifests itself to you. So if the world is manifesting itself in a very negative way, one thing to ask is: are you aiming at the right thing?"
6:59

Jordan Peterson: "If you can't fix your room, you can't fix your life" "Why should you even bother improving yourself? The answer is something like: so you don't suffer anymore stupidly than you have to. And maybe so others don't have to either. It's not some casual self-help doctrine. If you don't organize yourself properly, you'll pay for it. In a big way. And so will the people around you." Peterson continues: "You can say, 'Well, I don't care about that.' But that's actually not true, you do care about it. Because if you're in pain, you will care about it. It's very rare that you can find someone in excruciating pain who would say, 'Well, it would be no better if I was out of this.' Pain brings the idea that it would be better if it didn't exist along with it. It's incontrovertible." On how to start: "Look around for something that bothers you and see if you can fix it. You can do this in a room. Sit in your bedroom and think: 'If I wanted to spend ten minutes making this room better, what would I have to do?' You have to ask yourself that, it's a genuine question. And things will pop out. There's a stack of papers bugging you. Some rubbish behind your computer monitor you haven't attended to for six months. Cables tangled up." He explains why this matters: "If you were coming to see me for psychotherapy, the easiest thing would be to get you to organize your room. You think, is that psychotherapy? It depends on how you conceive the limits of your being. Start where you can start. If something announces itself as in need of repair that you could repair, fix it. Fix a hundred things like that, your life will be a lot different." On fixing what you repeat every day: "People tend to think of their daily routines as trivial. You get up, brush your teeth, have breakfast. Those probably constitute 50% of your life. People think, they're mundane, I don't need to pay attention to them. No, that's exactly wrong. The things you do every day are the most important things you do. Hands down. Just do the arithmetic." On staying within your competence: "Sometimes you don't know how to fix something. Imagine you're walking down the street and there's a guy who's alcoholic and schizophrenic and has been homeless for ten years. That's a problem. It would be good if you could fix it, but you haven't got a clue. You walk around that and go find something you could fix. Just because something announces itself as in need of repair doesn't mean it's you, right then and there, who should repair it. You have to have some humility. You don't walk up to a helicopter that isn't working and just start tinkering away." Peterson shares the key insight: "As soon as you give your mind a genuine aim, it'll reconfigure the world in keeping with that aim. That's actually how you see to begin with. You've all seen the video where you watch basketballs being tossed back and forth, and while you're doing that, a gorilla walks into the middle of the video and you don't see it. If you thought about that experiment for five years, that would be about the right amount of time to spend thinking about it." He explains what it reveals: "What it shows you is that you see what you aim at. If you can get one thing through your head, that would be a good one. You see what you aim at. One inference you might draw from that is: be careful what you aim at. What you aim at determines the way the world manifests itself to you. So if the world is manifesting itself in a very negative way, one thing to ask is: are you aiming at the right thing?"

Jaynit

68,799 views • 4 months ago

Author of Designing Data-Intensive Applications, Martin Kleppmann, gives us a peek into "The Troubles with Distributed Systems" and why you can't assume things behave well in distributed systems: "The whole idea is that in distributed system theory, there are certain things that we tend to assume. For example, we just assume that there's no upper bound on how long it might take for a message to go over the network. So when you send a message, it might arrive within a hundred microseconds, or it might take 10 years, and distributed system theory just doesn't make any assumptions about that sort of timing if we can avoid it. Or rather, some theory does make those assumptions, but it's a dangerous assumption to make because occasionally the network delay does become much higher than what is typical. Another thing is about crashes. Distributed system theory just says nodes can crash, but what does that actually mean? What in practice does it mean for a node to become unavailable? Because it might be a software crash, but it might be a hardware failure. It might be somebody unplugging the power cable. It might be that the node is actually still running, but it's just become disconnected from the network. And so, the point of this book chapter really is to defend and justify the theoretical models that we use for analysing distributed systems and to give a lot of stories and case studies to show that, actually, tonnes of stuff does go wrong. Don't believe anyone who says, 'Oh, failures are rare. Don't worry about it. It's fine’. Actually, no. If you want to make things reliable, you really do have to worry about a whole bunch of weird, unusual, but certainly possible edge cases. Timing is another one of those things. It's very easy to assume that your clocks are correct, and most of the time the clocks are pretty correct, but we just can't rely on it because actually they're just not precise enough on the whole. It's very tempting to make certain assumptions that things are well behaved and in distributed systems, we just have to try to get away from those assumptions if we want the systems to work reliably, even in the face of things going wrong."
2:37

Author of Designing Data-Intensive Applications, Martin Kleppmann, gives us a peek into "The Troubles with Distributed Systems" and why you can't assume things behave well in distributed systems: "The whole idea is that in distributed system theory, there are certain things that we tend to assume. For example, we just assume that there's no upper bound on how long it might take for a message to go over the network. So when you send a message, it might arrive within a hundred microseconds, or it might take 10 years, and distributed system theory just doesn't make any assumptions about that sort of timing if we can avoid it. Or rather, some theory does make those assumptions, but it's a dangerous assumption to make because occasionally the network delay does become much higher than what is typical. Another thing is about crashes. Distributed system theory just says nodes can crash, but what does that actually mean? What in practice does it mean for a node to become unavailable? Because it might be a software crash, but it might be a hardware failure. It might be somebody unplugging the power cable. It might be that the node is actually still running, but it's just become disconnected from the network. And so, the point of this book chapter really is to defend and justify the theoretical models that we use for analysing distributed systems and to give a lot of stories and case studies to show that, actually, tonnes of stuff does go wrong. Don't believe anyone who says, 'Oh, failures are rare. Don't worry about it. It's fine’. Actually, no. If you want to make things reliable, you really do have to worry about a whole bunch of weird, unusual, but certainly possible edge cases. Timing is another one of those things. It's very easy to assume that your clocks are correct, and most of the time the clocks are pretty correct, but we just can't rely on it because actually they're just not precise enough on the whole. It's very tempting to make certain assumptions that things are well behaved and in distributed systems, we just have to try to get away from those assumptions if we want the systems to work reliably, even in the face of things going wrong."

The Pragmatic Engineer

50,567 views • 3 months ago

Scott on why conviction in an idea is dangerous as an investor but required as a founder: "From the investor seat, I don't think you want to be in love with an idea. That's a risky thing because you'll find a way to express that by investing and make some compromises on the team because you know this idea is just so good, its time has come. But if the team isn't there, 90% of the time it doesn't work. Then there's a whole thing can you swap out the team? But the whole Founders Fund thesis was always no, you need the founder to run the company. But on the company side, you have to be in love with the idea. It's not that rational to start a company. There's a lot easier, more comfortable ways to make money if that's the goal. So it's got to be about what the company is doing specifically. If you want to actually start a company, it better be something that you're really passionate about, or you think that the problem is really important."
1:15

Scott on why conviction in an idea is dangerous as an investor but required as a founder: "From the investor seat, I don't think you want to be in love with an idea. That's a risky thing because you'll find a way to express that by investing and make some compromises on the team because you know this idea is just so good, its time has come. But if the team isn't there, 90% of the time it doesn't work. Then there's a whole thing can you swap out the team? But the whole Founders Fund thesis was always no, you need the founder to run the company. But on the company side, you have to be in love with the idea. It's not that rational to start a company. There's a lot easier, more comfortable ways to make money if that's the goal. So it's got to be about what the company is doing specifically. If you want to actually start a company, it better be something that you're really passionate about, or you think that the problem is really important."

Patrick OShaughnessy

33,016 views • 4 months ago

It's not important that your partner is an identical copy of you. It's important that they're not, that they bring something else to the table that you don't have. Now, in the context of entrepreneurship, because that's what I'm associated with, you need to find somebody that's willing to put up with the fact that you're just never there. I mean, that's very difficult because if you're running a business and you can't have a balanced life when you're an entrepreneur. It's really about finding that person that understands what you're about, that you're going down that journey and that you're not gonna stop doing it.
2:20

It's not important that your partner is an identical copy of you. It's important that they're not, that they bring something else to the table that you don't have. Now, in the context of entrepreneurship, because that's what I'm associated with, you need to find somebody that's willing to put up with the fact that you're just never there. I mean, that's very difficult because if you're running a business and you can't have a balanced life when you're an entrepreneur. It's really about finding that person that understands what you're about, that you're going down that journey and that you're not gonna stop doing it.

Kevin O'Leary aka Mr. Wonderful

17,254 views • 8 months ago

Axiom Math's Carina Hong on why verification isn't about catching mistakes, it's how you drive the cost of a proof to zero: "Formal verification is going to make your life slightly better if you're facing a proof with one million lines. Remember the Erdős unit distance problem, the chain of thought being generated? There are actual mathematicians trying to follow it step by step and scrutinize it. That seems very difficult if you're not in that very niche domain of discrete geometry intersecting with algebraic number theory." "But if you have a Lean proof accompanying it, you can just run it. And running the Lean proof gives you that provable guarantee that this proof is sound." "I have a hot take. People think Lean is this library built on the existing Mathlib. I think it's going to grow significantly. A lot of the hurdles where Lean is difficult is that the basic definitions of some mathematical fields are just not in the library." "My hot take is the scaling law, if you go down the formal mathematics path, is going to be a lot steeper than informal mathematics. So it's not just for verification, for trust, it's also for performance, it's also for optimal generation." "Verification is not like insurance. It's not something where, oh, we want to make sure there's no flaw. That's great, but it also helps you generate mathematics, both proofs and conjectures and theories, a lot better." "So imagine the cost of proof goes to zero. Then you can massage the problem statements, and even if it's an open problem, a lot more easily, flexibly, and adaptively." Carina Hong Axiom
3:17

Axiom Math's Carina Hong on why verification isn't about catching mistakes, it's how you drive the cost of a proof to zero: "Formal verification is going to make your life slightly better if you're facing a proof with one million lines. Remember the Erdős unit distance problem, the chain of thought being generated? There are actual mathematicians trying to follow it step by step and scrutinize it. That seems very difficult if you're not in that very niche domain of discrete geometry intersecting with algebraic number theory." "But if you have a Lean proof accompanying it, you can just run it. And running the Lean proof gives you that provable guarantee that this proof is sound." "I have a hot take. People think Lean is this library built on the existing Mathlib. I think it's going to grow significantly. A lot of the hurdles where Lean is difficult is that the basic definitions of some mathematical fields are just not in the library." "My hot take is the scaling law, if you go down the formal mathematics path, is going to be a lot steeper than informal mathematics. So it's not just for verification, for trust, it's also for performance, it's also for optimal generation." "Verification is not like insurance. It's not something where, oh, we want to make sure there's no flaw. That's great, but it also helps you generate mathematics, both proofs and conjectures and theories, a lot better." "So imagine the cost of proof goes to zero. Then you can massage the problem statements, and even if it's an open problem, a lot more easily, flexibly, and adaptively." Carina Hong Axiom

MTS

13,175 views • 18 days ago

Steve Jobs on how he learned to run a company: Question: "You're 21. You're a big success. You know, you've just sort of done it by the seat of your pants. You don't have any particular training in this. How do you learn to run a company?" Steve Jobs: "You know, throughout the years in business, I found something, which was that I always ask why you do things. And the answers you invariably get are, oh, that's just the way it's done. Nobody knows why they do what they do. Nobody thinks about things very deeply in business. That's what I found. I'll give you an example. When we were building our Apple I's in the garage, we knew exactly what they cost. When we got into a factory in the Apple II days, the accounting had this notion of a standard cost, where you'd kind of set a standard cost and at the end of a quarter you'd adjust it with a variance. And I kept asking, well, why do we do this? And the answer was, well, that's just the way it's done. And after about six months of digging into this, what I realized was the reason you do it is because you don't really have good enough controls to know how much it costs. So you guess, and then you fix your guess at the end of the quarter. And the reason you don't know how much it costs is because your information systems aren't good enough. But nobody said it that way. And so later on, when we designed this automated factory for Macintosh, we were able to get rid of a lot of these antiquated concepts and know exactly what something cost to the second. So in business, a lot of things are, I call it folklore. They're done because they were done yesterday and the day before. And so what that means is if you're willing to sort of ask a lot of questions and think about things and work really hard, you can learn business pretty fast. It's not the hardest thing in the world. It's not rocket science. It's not rocket science."
2:06

Steve Jobs on how he learned to run a company: Question: "You're 21. You're a big success. You know, you've just sort of done it by the seat of your pants. You don't have any particular training in this. How do you learn to run a company?" Steve Jobs: "You know, throughout the years in business, I found something, which was that I always ask why you do things. And the answers you invariably get are, oh, that's just the way it's done. Nobody knows why they do what they do. Nobody thinks about things very deeply in business. That's what I found. I'll give you an example. When we were building our Apple I's in the garage, we knew exactly what they cost. When we got into a factory in the Apple II days, the accounting had this notion of a standard cost, where you'd kind of set a standard cost and at the end of a quarter you'd adjust it with a variance. And I kept asking, well, why do we do this? And the answer was, well, that's just the way it's done. And after about six months of digging into this, what I realized was the reason you do it is because you don't really have good enough controls to know how much it costs. So you guess, and then you fix your guess at the end of the quarter. And the reason you don't know how much it costs is because your information systems aren't good enough. But nobody said it that way. And so later on, when we designed this automated factory for Macintosh, we were able to get rid of a lot of these antiquated concepts and know exactly what something cost to the second. So in business, a lot of things are, I call it folklore. They're done because they were done yesterday and the day before. And so what that means is if you're willing to sort of ask a lot of questions and think about things and work really hard, you can learn business pretty fast. It's not the hardest thing in the world. It's not rocket science. It's not rocket science."

Founder Mode

32,290 views • 6 months ago

Justin Thomas was asked about his group getting put on the clock: "We just didn't really agree with it. ... The hard part to me with the whole pace of play thing is that you, there's so much that goes into golf and there's so much that goes into hole to hole in terms of, are you hitting it close, are you able to tap it in, or you have to mark it, stuff like that, to where, are you holding the group up or are you not, to where it's very hard to make that call. And we just didn't agree with it, to be honest. "But we got taken off, and a hole later we were caught up. So it kind of goes to our point of why we didn't think we should of, but it is what it is. It's a part of it."
1:15

Justin Thomas was asked about his group getting put on the clock: "We just didn't really agree with it. ... The hard part to me with the whole pace of play thing is that you, there's so much that goes into golf and there's so much that goes into hole to hole in terms of, are you hitting it close, are you able to tap it in, or you have to mark it, stuff like that, to where, are you holding the group up or are you not, to where it's very hard to make that call. And we just didn't agree with it, to be honest. "But we got taken off, and a hole later we were caught up. So it kind of goes to our point of why we didn't think we should of, but it is what it is. It's a part of it."

Cameron Jourdan

619,266 views • 3 months ago

Something Stinks About Dominion Voting Machines and Elon Musk Can Smell It He finds it to be a “heck of a coincidence” that Philadelphia and Maricopa County use them, but “not in a lot of other places.” “I know a lot about computers, and I'm like, the last thing I would do is trust a computer program because it's just too easy to hack. It's too easy to add just one line, and it's really difficult to hack paper ballots. “So in-person voting with proof of ID, which, by the way, every country has. Almost every country that has democratic elections requires in-person voting with voter ID. “This is weird. It's super weird to not have that. I think that's the only way to effectively address fraud, given that we are where we are today. “I think we just need a very big margin of victory. If the margin of victory is big enough, then as I say, it's got to beat the cheat.”
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Something Stinks About Dominion Voting Machines and Elon Musk Can Smell It He finds it to be a “heck of a coincidence” that Philadelphia and Maricopa County use them, but “not in a lot of other places.” “I know a lot about computers, and I'm like, the last thing I would do is trust a computer program because it's just too easy to hack. It's too easy to add just one line, and it's really difficult to hack paper ballots. “So in-person voting with proof of ID, which, by the way, every country has. Almost every country that has democratic elections requires in-person voting with voter ID. “This is weird. It's super weird to not have that. I think that's the only way to effectively address fraud, given that we are where we are today. “I think we just need a very big margin of victory. If the margin of victory is big enough, then as I say, it's got to beat the cheat.”

The Vigilant Fox 🦊

141,016 views • 1 year ago

Black American says “Black fatigue is rampant” in America She talks about specific crimes and acts of violence “I can't believe that me saying that there's a violence problem in the Black community is seen as something that's like self-hating or racist — when you think of a culture that holds guns up to cameras and talks about it and romanticizes it, what culture do you think that is? Do you think that's white Americans that do that? No, it is Black Americans. That's not racist to say that. That's pointing out a problem. When you care about a group of people, when you have a child that's acting wrong and they're acting out, do you allow them to continue that behavior without pointing it out” “We're seeing it with our own eyes every day. We're seeing it. So, you know, say Black fatigue isn't a thing, say it's just racist. At the end of the day, if you don't want to point out something that is rampant and it's only going to increase and it's affecting younger and younger children and generations, then you don't care about the community. You're just worried about defending something that needs saving” Here are some harsh realities Black Americans make up only 12.6% of America but - Commit 55% of homicides - 29% of violent acts - Have a 6x homicide rate compared to whites - 30% of all EBT recipients are Black (remember they are only 13% of the whole population)
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Black American says “Black fatigue is rampant” in America She talks about specific crimes and acts of violence “I can't believe that me saying that there's a violence problem in the Black community is seen as something that's like self-hating or racist — when you think of a culture that holds guns up to cameras and talks about it and romanticizes it, what culture do you think that is? Do you think that's white Americans that do that? No, it is Black Americans. That's not racist to say that. That's pointing out a problem. When you care about a group of people, when you have a child that's acting wrong and they're acting out, do you allow them to continue that behavior without pointing it out” “We're seeing it with our own eyes every day. We're seeing it. So, you know, say Black fatigue isn't a thing, say it's just racist. At the end of the day, if you don't want to point out something that is rampant and it's only going to increase and it's affecting younger and younger children and generations, then you don't care about the community. You're just worried about defending something that needs saving” Here are some harsh realities Black Americans make up only 12.6% of America but - Commit 55% of homicides - 29% of violent acts - Have a 6x homicide rate compared to whites - 30% of all EBT recipients are Black (remember they are only 13% of the whole population)

Wall Street Apes

61,949 views • 2 months ago

Elon Musk: “Optimus Will Be The Biggest Product Ever Created” Let's see Optimus. You know, as you've heard me say before, I think Optimus will be the biggest product ever. But it is a very complex problem to solve. It's one of the hardest things to solve. To make a humanoid robot that can do tasks that you simply ask it to do, or show it a video, and it can do the task without any programming — like, no one's ever achieved this. And there are many challenges in the electromechanical design of the robot, to achieve sufficient dexterity and reliable hands, to be very reliable and have long, long wear and tear. But, I mean, it's good to be out in the field and not break down. Otherwise, you get this 70-kilogram robot that just flopped over, and you could carry it around like a baby, you know. And we don't want Optimus to go haywire. So, it's a lot of work to scale, to get the design right, and to scale production. And I really want to emphasize here that the production scaling challenge is very, very substantial. So this is going to be the hardest product to scale manufacturing that we've ever made at Tesla, because everything on the robot is new. And the difficulty of scaling the production up is proportionate to the newness of the parts in the robot.
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Elon Musk: “Optimus Will Be The Biggest Product Ever Created” Let's see Optimus. You know, as you've heard me say before, I think Optimus will be the biggest product ever. But it is a very complex problem to solve. It's one of the hardest things to solve. To make a humanoid robot that can do tasks that you simply ask it to do, or show it a video, and it can do the task without any programming — like, no one's ever achieved this. And there are many challenges in the electromechanical design of the robot, to achieve sufficient dexterity and reliable hands, to be very reliable and have long, long wear and tear. But, I mean, it's good to be out in the field and not break down. Otherwise, you get this 70-kilogram robot that just flopped over, and you could carry it around like a baby, you know. And we don't want Optimus to go haywire. So, it's a lot of work to scale, to get the design right, and to scale production. And I really want to emphasize here that the production scaling challenge is very, very substantial. So this is going to be the hardest product to scale manufacturing that we've ever made at Tesla, because everything on the robot is new. And the difficulty of scaling the production up is proportionate to the newness of the parts in the robot.

Tesla Owners Silicon Valley

42,131 views • 23 days ago

"Courage is far shorter in supply than genius." - Peter Thiel "One of the challenges in writing a book about entrepreneurship or teaching a class on this is that there is sort of no formula. And I think science always starts with a number two. It starts with experiments you can repeat, things you can do over and over again. But there's sort of a sense in which every moment in the history of business, every moment in the history of technology happens only once. The next Mark Zuckerberg will not be starting a social networking company. The next Larry Page will not start a search engine. The next Bill Gates will not be starting an operating system. And so if you are trying to copy these people, you're in some sense not learning from them. And so I think one of the really big challenges in teaching or writing about entrepreneurship is what can you say about being an entrepreneur at all when the key thing is always to do something new, different, that's not precisely been done before. And so the point of departure I start with in Zero to One is a somewhat indirect approach by asking a series of contrarian questions. The business question is, what great company is nobody starting? The more intellectual version of this question is, tell me something true that very few people agree with you on. And this is a fantastic interview question. It turns out to be quite a hard question, even when people can read on the internet that you ask of everybody who comes in the door, it still is a hard question. It's one of those unusual questions where if you know it's on the test, it's still hard. And it's hard not just because we sort of think that new things require brilliance or something like that, but because it's socially difficult. If I ask you that question, if you tell me something like the education system is screwed up or our political system doesn't work very well, those are true answers, but they're not actually good answers because all of us already know them to be true. The good answers are ones that are somehow uncomfortable that the person interviewing you does not actually want to hear. And I think we live in this world where courage is in far shorter supply than genius. And so it is sort of this, it is in a sense this problem of political correctness properly understood, is this very deep, very, very broad sort of a problem."
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"Courage is far shorter in supply than genius." - Peter Thiel "One of the challenges in writing a book about entrepreneurship or teaching a class on this is that there is sort of no formula. And I think science always starts with a number two. It starts with experiments you can repeat, things you can do over and over again. But there's sort of a sense in which every moment in the history of business, every moment in the history of technology happens only once. The next Mark Zuckerberg will not be starting a social networking company. The next Larry Page will not start a search engine. The next Bill Gates will not be starting an operating system. And so if you are trying to copy these people, you're in some sense not learning from them. And so I think one of the really big challenges in teaching or writing about entrepreneurship is what can you say about being an entrepreneur at all when the key thing is always to do something new, different, that's not precisely been done before. And so the point of departure I start with in Zero to One is a somewhat indirect approach by asking a series of contrarian questions. The business question is, what great company is nobody starting? The more intellectual version of this question is, tell me something true that very few people agree with you on. And this is a fantastic interview question. It turns out to be quite a hard question, even when people can read on the internet that you ask of everybody who comes in the door, it still is a hard question. It's one of those unusual questions where if you know it's on the test, it's still hard. And it's hard not just because we sort of think that new things require brilliance or something like that, but because it's socially difficult. If I ask you that question, if you tell me something like the education system is screwed up or our political system doesn't work very well, those are true answers, but they're not actually good answers because all of us already know them to be true. The good answers are ones that are somehow uncomfortable that the person interviewing you does not actually want to hear. And I think we live in this world where courage is in far shorter supply than genius. And so it is sort of this, it is in a sense this problem of political correctness properly understood, is this very deep, very, very broad sort of a problem."

Founder Mode

12,339 views • 6 months ago

Matthew Walker says the problem with waking at 4 a.m. is knowing it's 4 a.m. "How do you know it's four o'clock in the morning?" "That's your problem. You're looking at the clock." "And knowing that it's 3:15 or 4 a.m. in the morning does you no favors at all. It's not going to change the outcome." "So the first recommendation is remove all clock faces from the bedroom." "It's okay to, if you really must do, keep your phone next to your bed, but keep it out of sight, even though I would strongly recommend that you keep your phone in the kitchen." "Or even better still, a friend of mine recommended recently, just put it in the garage, put it in your car, in the garage." "And that way, the amount of motivation effort to go and get your phone within the first 10 minutes of the morning is very, very high, meaning you're probably not going to do it." "So let's baby steps. Let's just say crawl, walk, run. First thing to do, just make sure you can't see any clock faces." "And if you wake up, resist the urge, because as soon as you start doing that night after night, you're actually training your brain, reinforcing it to wake up at 3:15 in the morning." I used to treat checking the time as neutral information. Walker's point is that it is the trigger: you wake up fine, one glance, and now you are doing math about the alarm and how tired tomorrow will be. If he is also right about the training, the reliability of your 3:15 is the evidence, and a rehearsed loop is one you can interrupt. - Matthew Walker (Dr. Matthew Walker) on On Purpose with Jay Shetty (Jay Shetty)
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Matthew Walker says the problem with waking at 4 a.m. is knowing it's 4 a.m. "How do you know it's four o'clock in the morning?" "That's your problem. You're looking at the clock." "And knowing that it's 3:15 or 4 a.m. in the morning does you no favors at all. It's not going to change the outcome." "So the first recommendation is remove all clock faces from the bedroom." "It's okay to, if you really must do, keep your phone next to your bed, but keep it out of sight, even though I would strongly recommend that you keep your phone in the kitchen." "Or even better still, a friend of mine recommended recently, just put it in the garage, put it in your car, in the garage." "And that way, the amount of motivation effort to go and get your phone within the first 10 minutes of the morning is very, very high, meaning you're probably not going to do it." "So let's baby steps. Let's just say crawl, walk, run. First thing to do, just make sure you can't see any clock faces." "And if you wake up, resist the urge, because as soon as you start doing that night after night, you're actually training your brain, reinforcing it to wake up at 3:15 in the morning." I used to treat checking the time as neutral information. Walker's point is that it is the trigger: you wake up fine, one glance, and now you are doing math about the alarm and how tired tomorrow will be. If he is also right about the training, the reliability of your 3:15 is the evidence, and a rehearsed loop is one you can interrupt. - Matthew Walker (Dr. Matthew Walker) on On Purpose with Jay Shetty (Jay Shetty)

Jay McHale

17,231 views • 22 days ago

Dan has a distinctive lens for understanding companies and his view on LLMs as a blend of Netflix and Spotify is particularly interesting: "You are spending a ton of money upfront to train these models. You go sell them at extremely high incremental margins. You don't know what the revenues are going to be, but you want to sell as much as possible so that you can get the cash flow to build the next model. That's very similar to Netflix. When you're an early mover in this fixed asset business, you invest heavily, you get the revenues, and you spread it out over an increasing number of people. The difference is Netflix's content was differentiated. The models are more similar than they are different at any given time. That's where the Spotify analogy comes in. The differentiating factor will not necessarily be that Google gives you a better answer. However, the personalization matters. The first mover advantage is the more that these models know about you, you build up this data history and it becomes very sticky. What makes Spotify have pricing power? It's because they've tailored the service to take a product which is a commodity, and personalize it to the point where you're willing to pay a premium for that commodity."
2:19

Dan has a distinctive lens for understanding companies and his view on LLMs as a blend of Netflix and Spotify is particularly interesting: "You are spending a ton of money upfront to train these models. You go sell them at extremely high incremental margins. You don't know what the revenues are going to be, but you want to sell as much as possible so that you can get the cash flow to build the next model. That's very similar to Netflix. When you're an early mover in this fixed asset business, you invest heavily, you get the revenues, and you spread it out over an increasing number of people. The difference is Netflix's content was differentiated. The models are more similar than they are different at any given time. That's where the Spotify analogy comes in. The differentiating factor will not necessarily be that Google gives you a better answer. However, the personalization matters. The first mover advantage is the more that these models know about you, you build up this data history and it becomes very sticky. What makes Spotify have pricing power? It's because they've tailored the service to take a product which is a commodity, and personalize it to the point where you're willing to pay a premium for that commodity."

Patrick OShaughnessy

58,906 views • 5 months ago