正在加载视频...

视频加载失败

返回首页

How Google’s CEO predicted ChatGPT in 2016 “It’ll use Android/iOS, fast networks, and powerful machine learning… The model where you crowdsource information in, learn it, and then sell it is a highly likely candidate for the next $100 billion company.” As Eric Schmidt explains, it’s much easier to predict...

StartupArchive_'s profile picture

Startup Archive

94,826 subscribers

11,254 次观看 • 1 年前 •via X (Twitter)

科学技术新闻政治教育
LIVE

Anya Rossi• Live Now

Private livecam show

6 条评论

Startup Archive 的头像
Startup Archive1 年前

Watch the full @StartupGrind interview with Eric Schmidt here:

Startup Archive 的头像
Startup Archive1 年前

Want even more startup insights from the world's best founders? Join the 10,000+ founders who read our free newsletter here:

SecBriefs | Making Cybersecurity Simple 的头像
SecBriefs | Making Cybersecurity Simple1 年前

😔600+ healthcare data breaches exposed over 40 MILLION patient records last year. 💸The average cost of a healthcare data breach is $10.1 MILLION! 💔Protect your patients! Knowledge is power.💪 The "CYBERSECURITY DICTIONARY For Everyone" is on Amazon 🛒

growthesque 的头像
growthesque1 年前

He successfully predicted reCAPTCHA just 2 years after it was created.

SaaS Growth Strategies 的头像
SaaS Growth Strategies1 年前

You can't build a big company if you can't predict the future or where the world is heading. Especially if you are in tech, it is the most rapidly changing area. Unable to foresee the future can soon make you unrelatable to the market and eventually lead to downfall.

Jeeva 的头像
Jeeva1 年前

😤

相关视频

Google's former CEO Eric Schmidt on the data strategy behind the next hundred billion dollar companies: He explains that he evaluates startup ideas by looking at 5-year growth trajectories and asking whether there's a more scalable strategy available. Take a founder building an app they want to charge $10 for. Eric Schmidt's challenge: "Why not give it away for free and upsell users instead?" But the real insight is his framework for predicting which companies will dominate — and it all comes down to data. "5 years ago, I said publicly that the future will be apps that are on smartphones that use Google Maps, GPS, and do something useful. Now, what I should have said was Uber." So what does he think will define the next wave of massive companies? Systems built on Android and iOS, fast networks, and powerful machine learning, with a crucial data advantage: "They're going to use the crowd to learn something." He illustrates with this example: Pay dermatologists $1 each to categorize skin samples. Feed that into a machine learning system. Then sell the diagnostic service back to them, because a system trained on thousands of experts will outperform any individual. Schmidt summarizes the winning data strategy: "You crowdsource information in, you learn it, and then you sell it. [This] is in my view a highly likely candidate for the next hundred billion dollar corporations." The blueprint: Aggregate expert data at scale → train ML systems on that data → sell superior insights back to the market. This is how the next generation of dominant companies will be built.
1:48

Google's former CEO Eric Schmidt on the data strategy behind the next hundred billion dollar companies: He explains that he evaluates startup ideas by looking at 5-year growth trajectories and asking whether there's a more scalable strategy available. Take a founder building an app they want to charge $10 for. Eric Schmidt's challenge: "Why not give it away for free and upsell users instead?" But the real insight is his framework for predicting which companies will dominate — and it all comes down to data. "5 years ago, I said publicly that the future will be apps that are on smartphones that use Google Maps, GPS, and do something useful. Now, what I should have said was Uber." So what does he think will define the next wave of massive companies? Systems built on Android and iOS, fast networks, and powerful machine learning, with a crucial data advantage: "They're going to use the crowd to learn something." He illustrates with this example: Pay dermatologists $1 each to categorize skin samples. Feed that into a machine learning system. Then sell the diagnostic service back to them, because a system trained on thousands of experts will outperform any individual. Schmidt summarizes the winning data strategy: "You crowdsource information in, you learn it, and then you sell it. [This] is in my view a highly likely candidate for the next hundred billion dollar corporations." The blueprint: Aggregate expert data at scale → train ML systems on that data → sell superior insights back to the market. This is how the next generation of dominant companies will be built.

Big Brain AI

104,452 次观看 • 5 个月前

Eric Schmidt on how he uses 5-year plans to predict if a startup can become a $100 billion company “If you went to business school, you would’ve been taught: build a great product, organize a sales force, charge a fair price, make the customer happy.” But, as the former CEO of Google explains, that strategy is insufficiently scalable in the Internet era: “It’ll produce a reasonable business, but it’s not going to produce a huge business. It’s just too hard to hire all of those salespeople, work with every customer, and so forth. You have to have a more clever strategy.” Eric continues: “All of the really big companies have invented a new way to access information or a new way to do something [and didn’t require a large salesforce].” Eric argues that lots of the startup ideas he hears are good, but not good enough. He tells these founders to do a plan over the next five years and map your growth rate. Then try to figure out what a more scalable strategy might be. For example, if you’re building an app that you want to charge $10 for, Eric would ask: “Why can’t you give the app away for free and then upsell the users?” Another way to use a five-year plan to determine if your company can be a $100 billion company is to ask yourself what the big platforms will be five years from now and make sure your company is aligned with those platforms. In this interview from 2016, he predicts Android, iOS, and machine learning are the platforms he’d want to be aligned with over the next five years. Video source: Startup Grind (2016)
2:58

Eric Schmidt on how he uses 5-year plans to predict if a startup can become a $100 billion company “If you went to business school, you would’ve been taught: build a great product, organize a sales force, charge a fair price, make the customer happy.” But, as the former CEO of Google explains, that strategy is insufficiently scalable in the Internet era: “It’ll produce a reasonable business, but it’s not going to produce a huge business. It’s just too hard to hire all of those salespeople, work with every customer, and so forth. You have to have a more clever strategy.” Eric continues: “All of the really big companies have invented a new way to access information or a new way to do something [and didn’t require a large salesforce].” Eric argues that lots of the startup ideas he hears are good, but not good enough. He tells these founders to do a plan over the next five years and map your growth rate. Then try to figure out what a more scalable strategy might be. For example, if you’re building an app that you want to charge $10 for, Eric would ask: “Why can’t you give the app away for free and then upsell the users?” Another way to use a five-year plan to determine if your company can be a $100 billion company is to ask yourself what the big platforms will be five years from now and make sure your company is aligned with those platforms. In this interview from 2016, he predicts Android, iOS, and machine learning are the platforms he’d want to be aligned with over the next five years. Video source: Startup Grind (2016)

Startup Archive

58,465 次观看 • 1 年前

Former Google CEO Eric Schmidt explains how he uses 5-year plans to predict if a startup can become a $100B+ company “If you went to business school, you would’ve been taught: build a great product, organize a sales force, charge a fair price, make the customer happy.” But Eric explains that strategy is insufficiently scalable in the Internet era. “It’ll produce a reasonable business, but it’s not going to produce a huge business. It’s just too hard to hire all of those salespeople, work with every customer, and so forth. You have to have a more clever strategy.” He continues: “All of the really big companies have invented a new way to access information or a new way to do something that didn’t require [a large salesforce].” Eric argues that lots of the startup ideas he hears are good, but not good enough. He tells these founders to create a 5-year plan and map their growth rate. Then try to figure out what a more scalable strategy might be. For example, if you’re building an app that you want to charge $10 for, Eric asks: “Why can’t you give the app away for free and then upsell the users?" This is similar to the advice of Peter Thiel who famously asks founders: “How can you achieve your 10 year plan in the next 6 months?” Thinking big and optimizing for scalability is one key factor that separates the ultra successful companies from the rest. Another way to use a five-year plan to determine if your company can be a $100B+ company is to ask yourself what the big platforms will be five years from now and make sure your company is aligned with those platforms. In this interview from 2016 and he predicted that Android, iOS, and machine learning would be the dominant platforms of the next five years.
2:59

Former Google CEO Eric Schmidt explains how he uses 5-year plans to predict if a startup can become a $100B+ company “If you went to business school, you would’ve been taught: build a great product, organize a sales force, charge a fair price, make the customer happy.” But Eric explains that strategy is insufficiently scalable in the Internet era. “It’ll produce a reasonable business, but it’s not going to produce a huge business. It’s just too hard to hire all of those salespeople, work with every customer, and so forth. You have to have a more clever strategy.” He continues: “All of the really big companies have invented a new way to access information or a new way to do something that didn’t require [a large salesforce].” Eric argues that lots of the startup ideas he hears are good, but not good enough. He tells these founders to create a 5-year plan and map their growth rate. Then try to figure out what a more scalable strategy might be. For example, if you’re building an app that you want to charge $10 for, Eric asks: “Why can’t you give the app away for free and then upsell the users?" This is similar to the advice of Peter Thiel who famously asks founders: “How can you achieve your 10 year plan in the next 6 months?” Thinking big and optimizing for scalability is one key factor that separates the ultra successful companies from the rest. Another way to use a five-year plan to determine if your company can be a $100B+ company is to ask yourself what the big platforms will be five years from now and make sure your company is aligned with those platforms. In this interview from 2016 and he predicted that Android, iOS, and machine learning would be the dominant platforms of the next five years.

Startup Archive

611,873 次观看 • 2 年前

🇺🇸 EX-GOOGLE BOSS: AI WILL REPLACE MOST PROGRAMMERS IN A YEAR—SUPERINTELLIGENCE COULD ARRIVE IN SIX Former Google CEO, Eric Schmidt: "We believe that in the next year, the vast majority of programmers will be replaced by AI. Within three to five years, we’ll see AGI—systems as smart as the best humans. And in six years, artificial superintelligence—smarter than all of us combined. This is happening fast, and society isn’t ready." Source: Eric Schmidt vitrupo
2:31

🇺🇸 EX-GOOGLE BOSS: AI WILL REPLACE MOST PROGRAMMERS IN A YEAR—SUPERINTELLIGENCE COULD ARRIVE IN SIX Former Google CEO, Eric Schmidt: "We believe that in the next year, the vast majority of programmers will be replaced by AI. Within three to five years, we’ll see AGI—systems as smart as the best humans. And in six years, artificial superintelligence—smarter than all of us combined. This is happening fast, and society isn’t ready." Source: Eric Schmidt vitrupo

Mario Nawfal

1,458,404 次观看 • 1 年前

Sam Altman explains why “the great wave” is the most important concept for good startup ideas “This idea of the great wave - I think this is the most important concept to find good ideas out there. People wonder why startups cluster in small periods of time… The reason is that there are these great waves.” He gives the example of the internet giving rise to a number of massive companies in the late 90s and early 2000s. Then smartphones gave rise to another group of companies in the 2009-2011 period. “All of a sudden, new things are possible that were never possible before. And when that happens - because startups can move so quickly - you can do things that otherwise would never happen. Or that a big company would otherwise win on. You want to think about what the next great wave is.” In this lecture that was given in 2017, Sam predicts that the next great wave will be “machine learning applied to every vertical.” He continues: “You want to identify this - What is the big tectonic shift that’s going to happen in the next couple of years? And do something that’s enabled by that and built on that platform.” Video source: Stanford Online (2017)
0:59

Sam Altman explains why “the great wave” is the most important concept for good startup ideas “This idea of the great wave - I think this is the most important concept to find good ideas out there. People wonder why startups cluster in small periods of time… The reason is that there are these great waves.” He gives the example of the internet giving rise to a number of massive companies in the late 90s and early 2000s. Then smartphones gave rise to another group of companies in the 2009-2011 period. “All of a sudden, new things are possible that were never possible before. And when that happens - because startups can move so quickly - you can do things that otherwise would never happen. Or that a big company would otherwise win on. You want to think about what the next great wave is.” In this lecture that was given in 2017, Sam predicts that the next great wave will be “machine learning applied to every vertical.” He continues: “You want to identify this - What is the big tectonic shift that’s going to happen in the next couple of years? And do something that’s enabled by that and built on that platform.” Video source: Stanford Online (2017)

Startup Archive

12,919 次观看 • 5 个月前

Sam Altman explains why “the great wave” is the most important concept for good startup ideas “This idea of the great wave - I think this is the most important concept to find good ideas out there. People wonder why startups cluster in small periods of time… The reason is that there are these great waves.” He gives the example of the internet giving rise to a number of massive companies in the late 90s and early 2000s. Then smartphones gave rise to another group of companies in the 2009-2011 period. “All of a sudden, new things are possible that were never possible before. And when that happens - because startups can move so quickly - you can do things that otherwise would never happen. Or that a big company would otherwise win on. You want to think about what the next great wave is.” In this lecture that was given in 2017, Sam predicts that the next great wave will be “machine learning applied to every vertical.” He continues: “You want to identify this - What is the big tectonic shift that’s going to happen in the next couple of years? And do something that’s enabled by that and built on that platform.” Video source: Stanford Online (2017)
0:59

Sam Altman explains why “the great wave” is the most important concept for good startup ideas “This idea of the great wave - I think this is the most important concept to find good ideas out there. People wonder why startups cluster in small periods of time… The reason is that there are these great waves.” He gives the example of the internet giving rise to a number of massive companies in the late 90s and early 2000s. Then smartphones gave rise to another group of companies in the 2009-2011 period. “All of a sudden, new things are possible that were never possible before. And when that happens - because startups can move so quickly - you can do things that otherwise would never happen. Or that a big company would otherwise win on. You want to think about what the next great wave is.” In this lecture that was given in 2017, Sam predicts that the next great wave will be “machine learning applied to every vertical.” He continues: “You want to identify this - What is the big tectonic shift that’s going to happen in the next couple of years? And do something that’s enabled by that and built on that platform.” Video source: Stanford Online (2017)

Startup Archive

32,091 次观看 • 1 年前

Marissa Mayer on scaling Google and the internal black market CEO Eric Schmidt created for new hires “One of the things that [former Google CEO Eric Schmidt] talked about a lot was that at every order of magnitude, you should expect every process to break—and you should expect to have to completely reinvent it. It’s very different to deal with tens of people versus hundreds of people versus thousands of people” Marissa shares a story of how one time Eric reinvented Google’s hiring process in a way that initially frustrated everyone: “We had closed the year at about 200 people, and we had a plan to double the size of the company over the coming year. Eric showed up in March, looked at the plan, and said: ‘there’s just no way you guys are going to be able to double the number of employees and keep the quality and culture the way you want it to be.’” Eric then told the company that he would let them collectively hire 50 people that year—versus the 200 they were planning on hiring. And to enforce this, he created 50 laminated dollar bills with Larry Page and Sergey Brin’s faces on them and distributed them to Google’s VPs. Every new hire that year would require one “Larry & Sergey” bill. Naturally, a black market for these “Larrys & Sergeys” developed, and as Marissa describes, it became surprisingly efficient: “What would happen is the Head of Sales would have one and he would really need a new feature to make a sale. So he would [say to the engineer]: ‘look, I’m going to give you this Larry & Sergey but you have to promise you’re going to use it to hire someone who is going to build this feature to secure this revenue.’” She continues: “As painful as it was because there was way too much work to slow down our hiring like this, [the new process] was actually a really good moment for the company because it made us be really thoughtful about how we were scaling and where we were putting our resources. We had to be that much more thoughtful about what to prioritize and where the opportunities were. Yes, hypergrowth is really fun, but you also need to realize that you want that hypergrowth to happen in terms of users and revenue—and not necessarily in terms of the size of the company.”
3:02

Marissa Mayer on scaling Google and the internal black market CEO Eric Schmidt created for new hires “One of the things that [former Google CEO Eric Schmidt] talked about a lot was that at every order of magnitude, you should expect every process to break—and you should expect to have to completely reinvent it. It’s very different to deal with tens of people versus hundreds of people versus thousands of people” Marissa shares a story of how one time Eric reinvented Google’s hiring process in a way that initially frustrated everyone: “We had closed the year at about 200 people, and we had a plan to double the size of the company over the coming year. Eric showed up in March, looked at the plan, and said: ‘there’s just no way you guys are going to be able to double the number of employees and keep the quality and culture the way you want it to be.’” Eric then told the company that he would let them collectively hire 50 people that year—versus the 200 they were planning on hiring. And to enforce this, he created 50 laminated dollar bills with Larry Page and Sergey Brin’s faces on them and distributed them to Google’s VPs. Every new hire that year would require one “Larry & Sergey” bill. Naturally, a black market for these “Larrys & Sergeys” developed, and as Marissa describes, it became surprisingly efficient: “What would happen is the Head of Sales would have one and he would really need a new feature to make a sale. So he would [say to the engineer]: ‘look, I’m going to give you this Larry & Sergey but you have to promise you’re going to use it to hire someone who is going to build this feature to secure this revenue.’” She continues: “As painful as it was because there was way too much work to slow down our hiring like this, [the new process] was actually a really good moment for the company because it made us be really thoughtful about how we were scaling and where we were putting our resources. We had to be that much more thoughtful about what to prioritize and where the opportunities were. Yes, hypergrowth is really fun, but you also need to realize that you want that hypergrowth to happen in terms of users and revenue—and not necessarily in terms of the size of the company.”

Startup Archive

162,101 次观看 • 2 年前

Former Google CEO Eric Schmidt: “The great founders are frugal” When Eric joined Google as CEO in 2001 — two years after the company had raised a $25 million Series A — he shared an office with four engineers. He even had to lend one of the founders his car when theirs broke down. He believes this frugality is common attribute of the best founders: “I can always tell when we’re dealing with a proper founder by how they are spending their money… Whenever I go to startups that have beautiful offices and really nice chairs, I cringe.” Eric continues: “The great founders are frugal. They understand that the money needs to be used precisely for certain areas. Many of the most successful founders begin with no salary at all… If you’re not prepared to live that, you don’t really understand what being a founder is like.” Video source: Startup Grind (2016)
1:02

Former Google CEO Eric Schmidt: “The great founders are frugal” When Eric joined Google as CEO in 2001 — two years after the company had raised a $25 million Series A — he shared an office with four engineers. He even had to lend one of the founders his car when theirs broke down. He believes this frugality is common attribute of the best founders: “I can always tell when we’re dealing with a proper founder by how they are spending their money… Whenever I go to startups that have beautiful offices and really nice chairs, I cringe.” Eric continues: “The great founders are frugal. They understand that the money needs to be used precisely for certain areas. Many of the most successful founders begin with no salary at all… If you’re not prepared to live that, you don’t really understand what being a founder is like.” Video source: Startup Grind (2016)

Startup Archive

62,897 次观看 • 1 年前

Did you know that 2025 is the International Year of Quantum Science and Technology? Hear physics laureate William Phillips speak about how hard it is to predict what quantum mechanics can be used for in the future. Similarly, it was just as hard to predict what it was to be used for 100 years ago. Hear the full conversation: #NobelPrize
1:41

Did you know that 2025 is the International Year of Quantum Science and Technology? Hear physics laureate William Phillips speak about how hard it is to predict what quantum mechanics can be used for in the future. Similarly, it was just as hard to predict what it was to be used for 100 years ago. Hear the full conversation: #NobelPrize

The Nobel Prize

13,242 次观看 • 1 年前

Thought this was incredibly insightful from Sundar. Too many people are trying to figure out what the world looks like 10 years from now, while AI is moving at a pace that makes the next year itself feel so exciting Sundar Pichai (CEO of Google): "I think you can paralyze yourself thinking 10 years ahead, but we are fortunate to be in a moment where you can think a year ahead and the curve is so steep It’s exciting to just do that year ahead. Whereas in the past, you may need to sit and envision five years out. The models are going to be dramatically different in a year’s time." A lot of the same applies to investing. In a world that is so uncertain, trying to predict what valuation will be in 10 years is not a helpful exercise Instead, you should try to think about what AI capabilities will exist next year and how that impacts the companies you allocate capital towards Exciting times to live in
1:25

Thought this was incredibly insightful from Sundar. Too many people are trying to figure out what the world looks like 10 years from now, while AI is moving at a pace that makes the next year itself feel so exciting Sundar Pichai (CEO of Google): "I think you can paralyze yourself thinking 10 years ahead, but we are fortunate to be in a moment where you can think a year ahead and the curve is so steep It’s exciting to just do that year ahead. Whereas in the past, you may need to sit and envision five years out. The models are going to be dramatically different in a year’s time." A lot of the same applies to investing. In a world that is so uncertain, trying to predict what valuation will be in 10 years is not a helpful exercise Instead, you should try to think about what AI capabilities will exist next year and how that impacts the companies you allocate capital towards Exciting times to live in

Boring_Business

45,140 次观看 • 3 个月前

Why Elon didn't want to be CEO: "[Elon] is at core, an engineer and a product guy. He has this great line where he said: "I realized you couldn't be fully in control of the product unless you were also in control of the company." He says he made a moral error, early in Tesla, where he was trying to have his cake and eat it too. He wanted to control the company without running the company. And that was the 2002 to 2008 era, where Tesla was just off to a really messy start. He was providing the funding. He was chairman of the board. But Martin Eberhard was CEO. Eventually, when Tesla was on the verge of death in 2008....Elon was pushed into the position of: "I have to be CEO. I don't want to be. It comes with a lot of chores. It comes with a lot of responsibilities. But if I want this company to be successful, I have to fully internalize and take responsibility for it." And that's what he did, even though he was also in the same position at SpaceX. The fact that these companies are improbable, iconic, and that he funded and led them both in parallel...it's like running a two minute mile twice at the same time. It is such a higher degree of difficulty than most people can conceive of, and the fact that it worked is still unbelievable."
4:24

Why Elon didn't want to be CEO: "[Elon] is at core, an engineer and a product guy. He has this great line where he said: "I realized you couldn't be fully in control of the product unless you were also in control of the company." He says he made a moral error, early in Tesla, where he was trying to have his cake and eat it too. He wanted to control the company without running the company. And that was the 2002 to 2008 era, where Tesla was just off to a really messy start. He was providing the funding. He was chairman of the board. But Martin Eberhard was CEO. Eventually, when Tesla was on the verge of death in 2008....Elon was pushed into the position of: "I have to be CEO. I don't want to be. It comes with a lot of chores. It comes with a lot of responsibilities. But if I want this company to be successful, I have to fully internalize and take responsibility for it." And that's what he did, even though he was also in the same position at SpaceX. The fact that these companies are improbable, iconic, and that he funded and led them both in parallel...it's like running a two minute mile twice at the same time. It is such a higher degree of difficulty than most people can conceive of, and the fact that it worked is still unbelievable."

Ti Morse

47,497 次观看 • 2 个月前

Jeff Bezos on the insight that started Amazon: In 1994, Bezos came across a statistic that changed his life: worldwide web usage was growing at roughly 2,300% a year. "That was sort of a wakeup call for me that there was something going on," he recalls. At the time, most people hadn't even heard of the web. This was the era of 28 kilobit per second modems and dial-up access. A very different age. But the signal was clear. Something was coming. Jeff Bezos explains the realisation that followed: "I realized you could make a bookstore on the web that could hold more books than a physical bookstore could ever hold. It could truly have universal selection." His background was in computers, not books. He's quick to point out that books weren't chosen out of personal passion: "My real compass, my real passion was computers, and that's how I was involved in this world of the web back in 94. But books was a great first best product to sell online." So why books specifically? Bezos breaks down the logic: "Books were very unique and still are in one respect, and that is that there are more items in the book category than there are items in any other category. There are millions of books active and in print around the world, and the largest physical book superstores only carry about 100, 150,000 of those millions of different books." That gap between what existed and what was accessible was the opening. On the web, you could solve a real problem. People couldn't find the books they wanted, especially the narrow, niche titles with smaller audiences. "We basically built Amazon to make it possible for people to find those hard to find books."
1:57

Jeff Bezos on the insight that started Amazon: In 1994, Bezos came across a statistic that changed his life: worldwide web usage was growing at roughly 2,300% a year. "That was sort of a wakeup call for me that there was something going on," he recalls. At the time, most people hadn't even heard of the web. This was the era of 28 kilobit per second modems and dial-up access. A very different age. But the signal was clear. Something was coming. Jeff Bezos explains the realisation that followed: "I realized you could make a bookstore on the web that could hold more books than a physical bookstore could ever hold. It could truly have universal selection." His background was in computers, not books. He's quick to point out that books weren't chosen out of personal passion: "My real compass, my real passion was computers, and that's how I was involved in this world of the web back in 94. But books was a great first best product to sell online." So why books specifically? Bezos breaks down the logic: "Books were very unique and still are in one respect, and that is that there are more items in the book category than there are items in any other category. There are millions of books active and in print around the world, and the largest physical book superstores only carry about 100, 150,000 of those millions of different books." That gap between what existed and what was accessible was the opening. On the web, you could solve a real problem. People couldn't find the books they wanted, especially the narrow, niche titles with smaller audiences. "We basically built Amazon to make it possible for people to find those hard to find books."

High Signal AI

12,564 次观看 • 2 个月前

Paul Graham’s advice for future startup founders: “Just learn” “If you make a conscious effort to try and think of startup ideas, you will think of ideas that are not only bad but bad and plausible-sounding—meaning you and everybody else will be fooled by them and you’ll waste a lot of time before realizing they’re no good.” As Paul Graham explains, the way to come up with good startup ideas is to take a step back: “Instead of trying to make a conscious effort to think of startup ideas, turn your brain into the type that has startup ideas unconsciously.” You do this by: 1. Learning a lot about things that matter 2. Working on problems that interest you 3. With people you like and respect (this is incidentally how you get co-founders at the same time as the idea) “The component of entrepreneurship that really matters is domain expertise. Larry Page is Larry Page because he was an expert on search. And he became an expert on search because he was genuinely interested in it, not because of some ulterior motive.” PG continues: “At its best, starting a startup is merely an ulterior motive for curiosity, and you’ll do it best if you introduce the ulterior motive at the end of the process. So here is the ultimate advice for young, would-be startup founders reduced to two words: Just learn.” Video source: Y Combinator (2017)
2:12

Paul Graham’s advice for future startup founders: “Just learn” “If you make a conscious effort to try and think of startup ideas, you will think of ideas that are not only bad but bad and plausible-sounding—meaning you and everybody else will be fooled by them and you’ll waste a lot of time before realizing they’re no good.” As Paul Graham explains, the way to come up with good startup ideas is to take a step back: “Instead of trying to make a conscious effort to think of startup ideas, turn your brain into the type that has startup ideas unconsciously.” You do this by: 1. Learning a lot about things that matter 2. Working on problems that interest you 3. With people you like and respect (this is incidentally how you get co-founders at the same time as the idea) “The component of entrepreneurship that really matters is domain expertise. Larry Page is Larry Page because he was an expert on search. And he became an expert on search because he was genuinely interested in it, not because of some ulterior motive.” PG continues: “At its best, starting a startup is merely an ulterior motive for curiosity, and you’ll do it best if you introduce the ulterior motive at the end of the process. So here is the ultimate advice for young, would-be startup founders reduced to two words: Just learn.” Video source: Y Combinator (2017)

Startup Archive

51,157 次观看 • 4 个月前

Marc Andreessen says AI is hyper democratizing. “Is the future of the world going to be one or a small number of companies, or for that matter, governments or super AIs that kind of own and control everything?” “Or is this a technology that's going to diffuse out and be in everybody's hands?” “This is the time in which AI is actually hyper democratizing. It has spread to more individuals, both in the country and around the world in the shortest period of time of any new technology I think in history.” “The best AIs in the world are in the consumer products.” “This technology is going to be in everybody's hands. And everybody is going to be able to use it to optimize the things that they do, have it be a thought partner, assistant for building companies.” Marc Andreessen 🇺🇸
1:34

Marc Andreessen says AI is hyper democratizing. “Is the future of the world going to be one or a small number of companies, or for that matter, governments or super AIs that kind of own and control everything?” “Or is this a technology that's going to diffuse out and be in everybody's hands?” “This is the time in which AI is actually hyper democratizing. It has spread to more individuals, both in the country and around the world in the shortest period of time of any new technology I think in history.” “The best AIs in the world are in the consumer products.” “This technology is going to be in everybody's hands. And everybody is going to be able to use it to optimize the things that they do, have it be a thought partner, assistant for building companies.” Marc Andreessen 🇺🇸

a16z

79,935 次观看 • 8 个月前

Kevin Costner said he left Yellowstone over scheduling conflicts after staying for five seasons instead of the three he originally agreed to. Kevin Costner: I'm not in it. I was in it for five years. I guess I could be in it again if, um, if the planets wanted to line up, which means the storyline, the script. And then, I want to work more than once a year. Um, and to do that, the times have to be set aside for things. And when that couldn't happen, then that can't work for me anymore. Howard Stern: Well, that's a ballsy move. I mean, what a great show, what a great character you developed. Kevin Costner: That was great. Kevin Costner: Yeah, Cole is fabulous. And Kelly was great, and it was perfect. Look, I love this, I love the show. I went and sold it for them before it was a show. Taylor wrote a beautiful script. I went overseas, I stared at 300 people, and they go, "What is the show?" And I said, "I don't know. I think it could be good." "Are you going to be in it?" I said, "Uh..." I said, "I'll be in it for three years, but then I'm not sure." But I said this, "I think it's good."
2:45

Kevin Costner said he left Yellowstone over scheduling conflicts after staying for five seasons instead of the three he originally agreed to. Kevin Costner: I'm not in it. I was in it for five years. I guess I could be in it again if, um, if the planets wanted to line up, which means the storyline, the script. And then, I want to work more than once a year. Um, and to do that, the times have to be set aside for things. And when that couldn't happen, then that can't work for me anymore. Howard Stern: Well, that's a ballsy move. I mean, what a great show, what a great character you developed. Kevin Costner: That was great. Kevin Costner: Yeah, Cole is fabulous. And Kelly was great, and it was perfect. Look, I love this, I love the show. I went and sold it for them before it was a show. Taylor wrote a beautiful script. I went overseas, I stared at 300 people, and they go, "What is the show?" And I said, "I don't know. I think it could be good." "Are you going to be in it?" I said, "Uh..." I said, "I'll be in it for three years, but then I'm not sure." But I said this, "I think it's good."

Ruzy.hl

1,656,751 次观看 • 12 天前

Elon Musk was asked how fast AI is moving. His answer wasn’t about the technology. It was about the one man who got it all right and was still too conservative. Musk: “I have to give credit to Ray Kurzweil in being actually remarkably accurate in his predictions. If anything, I think he was perhaps a bit conservative in his predictions.” Kurzweil spent 30 years making forecasts that made serious people uncomfortable. He predicted timelines that sounded impossible. He was mocked for it. He was right about nearly all of them. And Musk just called him conservative. Musk: “The dedicated AI compute appears to be growing by a factor of 10 every six months.” 10x every six months. Musk: “Almost a 100x improvement per year, at least for the next few years.” Moore’s Law was a 2x improvement every two years. That single curve drove every technological shift of the last 50 years. The internet. Smartphones. Cloud computing. All of it rode a 2x curve. AI is on a 100x curve. And the current infrastructure isn’t running beside the new one. It’s becoming it. Musk: “Probably a lot of the data centers, maybe most of the data centers that currently do conventional compute, will transition to AI compute.” Everything that runs the world you know is being rewired for the world that comes next. Human beings process the future in straight lines. We take the speed of the last decade and project it forward. Exponential growth doesn’t work that way. It’s invisible until it’s everywhere. The most aggressive forecaster in the history of technology was too conservative. That’s not about Kurzweil being wrong about the direction. That’s about the human brain being wrong about the speed. The limit was never the technology. It was the organ we use to comprehend it. And that organ hasn’t been upgraded in 200,000 years.
1:01

Elon Musk was asked how fast AI is moving. His answer wasn’t about the technology. It was about the one man who got it all right and was still too conservative. Musk: “I have to give credit to Ray Kurzweil in being actually remarkably accurate in his predictions. If anything, I think he was perhaps a bit conservative in his predictions.” Kurzweil spent 30 years making forecasts that made serious people uncomfortable. He predicted timelines that sounded impossible. He was mocked for it. He was right about nearly all of them. And Musk just called him conservative. Musk: “The dedicated AI compute appears to be growing by a factor of 10 every six months.” 10x every six months. Musk: “Almost a 100x improvement per year, at least for the next few years.” Moore’s Law was a 2x improvement every two years. That single curve drove every technological shift of the last 50 years. The internet. Smartphones. Cloud computing. All of it rode a 2x curve. AI is on a 100x curve. And the current infrastructure isn’t running beside the new one. It’s becoming it. Musk: “Probably a lot of the data centers, maybe most of the data centers that currently do conventional compute, will transition to AI compute.” Everything that runs the world you know is being rewired for the world that comes next. Human beings process the future in straight lines. We take the speed of the last decade and project it forward. Exponential growth doesn’t work that way. It’s invisible until it’s everywhere. The most aggressive forecaster in the history of technology was too conservative. That’s not about Kurzweil being wrong about the direction. That’s about the human brain being wrong about the speed. The limit was never the technology. It was the organ we use to comprehend it. And that organ hasn’t been upgraded in 200,000 years.

Dustin

213,568 次观看 • 1 个月前

Marc Andreessen: Most successful companies started “product first” “There are products that become companies, and then there are companies that come up with a product. One of the interesting things over the years is that many of the most successful technology franchises were products first, way before they ever became companies.” In this talk, Marc gives a few examples: • His team at the University of Illinois worked on the research project that became Netscape for three years before it became a company • Bill Gates and Paul Allen were deep into PCs before there was a software business • Jobs and Wozniak built the first Apple computer as hobbyists • Mark Zuckerberg was running Facebook out of his dorm room before he ever thought of starting a company • Twitter was a side project at the failed podcasting app Odeo Marc believes that this “product becomes a company” template is successful because “it’s a demonstration that the product has to exist. The market needs the product so badly that somebody actually built it and deployed it and you can actually see evidence that people want it before there was an economic motivation to do so.” He contrasts this with the failure cases he often sees when entrepreneurs try to figure out the idea after starting a company. “It’s very easy in that process to fool yourself into believing that there’s a market because you want to find something and you have a very strong motivation to come up with an answer. It’s hard to go through that process for three months and then say, ‘you know what, we can’t come up with any good ideas.’” There are of course there exceptions. Marc gives Hewlett Packard as an example. But that’s more the exception than the rule. As Marc explains: “The moral of the story is it has to be a really good idea. That often will be an idea that is preexisting at the time you decide to start a company. And if it isn’t, be really careful because you’re walking on sharp rocks at that point with a high risk of falling off the cliff into the ocean.” Video source: Stanford eCorner (2010)
1:53

Marc Andreessen: Most successful companies started “product first” “There are products that become companies, and then there are companies that come up with a product. One of the interesting things over the years is that many of the most successful technology franchises were products first, way before they ever became companies.” In this talk, Marc gives a few examples: • His team at the University of Illinois worked on the research project that became Netscape for three years before it became a company • Bill Gates and Paul Allen were deep into PCs before there was a software business • Jobs and Wozniak built the first Apple computer as hobbyists • Mark Zuckerberg was running Facebook out of his dorm room before he ever thought of starting a company • Twitter was a side project at the failed podcasting app Odeo Marc believes that this “product becomes a company” template is successful because “it’s a demonstration that the product has to exist. The market needs the product so badly that somebody actually built it and deployed it and you can actually see evidence that people want it before there was an economic motivation to do so.” He contrasts this with the failure cases he often sees when entrepreneurs try to figure out the idea after starting a company. “It’s very easy in that process to fool yourself into believing that there’s a market because you want to find something and you have a very strong motivation to come up with an answer. It’s hard to go through that process for three months and then say, ‘you know what, we can’t come up with any good ideas.’” There are of course there exceptions. Marc gives Hewlett Packard as an example. But that’s more the exception than the rule. As Marc explains: “The moral of the story is it has to be a really good idea. That often will be an idea that is preexisting at the time you decide to start a company. And if it isn’t, be really careful because you’re walking on sharp rocks at that point with a high risk of falling off the cliff into the ocean.” Video source: Stanford eCorner (2010)

Startup Archive

35,823 次观看 • 10 个月前