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Sequoia Partner Dean Meyer says there are two major risks to relying on a Chinese open-source ecosystem: dependency and security. "The first risk is dependency. The framing we have at Sequoia is we're only as good as our next investment. In some sense, the analogy is you're only as...

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39,085 просмотров • 25 дней назад •via X (Twitter)

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Sriram Krishnan on why Chinese models can distill off American models but American startups can't: "First of all, every model we have today is distilled off of all human knowledge. If you go back to the original GPT or the original Claude, they all had to derive off crawling the internet, crawling off all of our blogs and tweets and content. They kind of consume human knowledge to bootstrap that." "I'm going to steal this from Dean Meyer of Sequoia, who had a fantastic post yesterday. The situation which is bad today is that some of these models from other countries can train off American models, whereas if you are an American open weight model, it may be really confusing or challenging on whether you can distill off of other American models." "We kind of have a really uneven ecosystem here, where if you're a Chinese model, you could probably get a bunch of reasoning traces. But if you are a new Valley startup and you want to use some reasoning traces, you don't know what the legal situation is." "If you look at any American open source model today, they are using Chinese models as a teacher, or in a way as a part of the fine-tuning process. How do we make sure that is protected and enshrined, so if you're an American model company, you have the same level playing field as the Chinese models?" Sriram Krishnan
3:48

Sriram Krishnan on why Chinese models can distill off American models but American startups can't: "First of all, every model we have today is distilled off of all human knowledge. If you go back to the original GPT or the original Claude, they all had to derive off crawling the internet, crawling off all of our blogs and tweets and content. They kind of consume human knowledge to bootstrap that." "I'm going to steal this from Dean Meyer of Sequoia, who had a fantastic post yesterday. The situation which is bad today is that some of these models from other countries can train off American models, whereas if you are an American open weight model, it may be really confusing or challenging on whether you can distill off of other American models." "We kind of have a really uneven ecosystem here, where if you're a Chinese model, you could probably get a bunch of reasoning traces. But if you are a new Valley startup and you want to use some reasoning traces, you don't know what the legal situation is." "If you look at any American open source model today, they are using Chinese models as a teacher, or in a way as a part of the fine-tuning process. How do we make sure that is protected and enshrined, so if you're an American model company, you have the same level playing field as the Chinese models?" Sriram Krishnan

MTS

71,286 просмотров • 1 месяц назад

Alloy Therapeutics Founder & CEO Errik B. Anderson believes we will cure every disease that is curable in the next three decades. "We are living in a world where we will cure everything that is curable in the next three decades, maybe even faster than that." "It's really just a question of how fast can we accelerate and give as many people as possible access to these incredible tools." "[During the dot-com boom], there were a lot of the same criticisms that we're hearing in the tech space right now as it relates to biotech. We did see the flow of investment coming in, and many things went bankrupt." "But the things that didn't go bankrupt changed the world, and that exact same thing is happening today and you're going to see an incredible number of winners. The tech space is going to go conquer biology as much as it has in other places."
1:32

Alloy Therapeutics Founder & CEO Errik B. Anderson believes we will cure every disease that is curable in the next three decades. "We are living in a world where we will cure everything that is curable in the next three decades, maybe even faster than that." "It's really just a question of how fast can we accelerate and give as many people as possible access to these incredible tools." "[During the dot-com boom], there were a lot of the same criticisms that we're hearing in the tech space right now as it relates to biotech. We did see the flow of investment coming in, and many things went bankrupt." "But the things that didn't go bankrupt changed the world, and that exact same thing is happening today and you're going to see an incredible number of winners. The tech space is going to go conquer biology as much as it has in other places."

TBPN

13,127 просмотров • 4 месяцев назад

NRG Strong on the lessons they can take away from their loss to Paper Rex: "I would say the major lesson we probably had was the importance of setting up the players for success. I don't think we did as well as we could today. Maybe there's one or two things we could have done better. I think the major lesson, to be fair, is that our fundamentals are strong. We didn't play badly at all today. But because of how we are as a team, it can always come down to very tight margins. We're a team that doesn't generally blow teams out. We're a team that is so, so good at grinding out rounds and doing that sort of stuff. So I think the big lesson is: we're good, our fundamentals are good, we just have to be tight, and we just can't let anything for error slip in. There are lessons to be taken from this. This wasn't a bad loss. You get bad losses sometimes. It didn't feel like, 'Oh, we don't know what went wrong.' No, we know what went wrong. It's one or two small things, and it's things that we can adapt to, and it's things that will be better under different circumstances, and things that we can make the circumstances better for as well. So yeah, I think that would be the big lesson. We just have to be tight in these circumstances and there's no room for error on our end. That's a big, big, big thing."
1:53

NRG Strong on the lessons they can take away from their loss to Paper Rex: "I would say the major lesson we probably had was the importance of setting up the players for success. I don't think we did as well as we could today. Maybe there's one or two things we could have done better. I think the major lesson, to be fair, is that our fundamentals are strong. We didn't play badly at all today. But because of how we are as a team, it can always come down to very tight margins. We're a team that doesn't generally blow teams out. We're a team that is so, so good at grinding out rounds and doing that sort of stuff. So I think the big lesson is: we're good, our fundamentals are good, we just have to be tight, and we just can't let anything for error slip in. There are lessons to be taken from this. This wasn't a bad loss. You get bad losses sometimes. It didn't feel like, 'Oh, we don't know what went wrong.' No, we know what went wrong. It's one or two small things, and it's things that we can adapt to, and it's things that will be better under different circumstances, and things that we can make the circumstances better for as well. So yeah, I think that would be the big lesson. We just have to be tight in these circumstances and there's no room for error on our end. That's a big, big, big thing."

VALO2ASIA

105,363 просмотров • 5 месяцев назад

Building nuclear reactors that are easy to replicate is a SpaceX style problem: "What we're trying to do here is build a reactor which is easy to replicate. It's a little different from mass manufacturing. Different from a Tesla style problem, more like a SpaceX style problem. You have a complicated vehicle that you need to get really good at building and deploying in a repeatable fashion. When I first started the company, we didn't have a size in mind for the first reactor. It was very explicit. We told the team we don't know how big the reactor is going to be. We don't know how powerful it's going to be. We didn't know those numbers until a year to 18 months into the company. We told ourselves we are going to discover the power level through the manufacturing process. Our instinct was as long as that number turns out to be somewhere above 15 megawatts, we should be pretty good for mass production. If you're under 15 megawatts, it's pretty hard to scale the right way. You just end up doing so many different pieces of operations that it becomes more complicated. But our feeling is above the 15 megawatt break point, you have something that can really scale. And we think this reactor ends up somewhere around 25 megawatts. 25 megawatts being the sort of scale factor where if you want a gigawatt, you just build 40 of them. The next challenge for us as we turn this on and turn the next one on is how do we get to the place where we're turning on one reactor every day and then multiple reactors every day. That's how we're going to climb into the gigawatts."
2:07

Building nuclear reactors that are easy to replicate is a SpaceX style problem: "What we're trying to do here is build a reactor which is easy to replicate. It's a little different from mass manufacturing. Different from a Tesla style problem, more like a SpaceX style problem. You have a complicated vehicle that you need to get really good at building and deploying in a repeatable fashion. When I first started the company, we didn't have a size in mind for the first reactor. It was very explicit. We told the team we don't know how big the reactor is going to be. We don't know how powerful it's going to be. We didn't know those numbers until a year to 18 months into the company. We told ourselves we are going to discover the power level through the manufacturing process. Our instinct was as long as that number turns out to be somewhere above 15 megawatts, we should be pretty good for mass production. If you're under 15 megawatts, it's pretty hard to scale the right way. You just end up doing so many different pieces of operations that it becomes more complicated. But our feeling is above the 15 megawatt break point, you have something that can really scale. And we think this reactor ends up somewhere around 25 megawatts. 25 megawatts being the sort of scale factor where if you want a gigawatt, you just build 40 of them. The next challenge for us as we turn this on and turn the next one on is how do we get to the place where we're turning on one reactor every day and then multiple reactors every day. That's how we're going to climb into the gigawatts."

Ti Morse

58,568 просмотров • 1 месяц назад

#WATCH | Delhi: On India-US trade deal, Rajesh Agrawal, Secretary, Ministry of Commerce & Industry says, "We are very optimistic and very hopeful that we should find a solution within this calendar year. But as you know, in any trade negotiations, even if there is one sticking point or issue on the mind of even one of the partners, the trade deal may not meet that deadline. The overall position is well set to deliver it in the next few weeks or months as soon as we can. But let's see, it's a call that will have to be taken at multiple levels. At the levels of negotiator, I think we are in a zone where we can say it is something that we can achieve in a very short while of time. There's not much to negotiate...As a country, we have always stood for our own sensitivities and our own uniqueness. So there are areas which are non-negotiable from our perspective..." (Source: FICCI/YouTube)
1:27

#WATCH | Delhi: On India-US trade deal, Rajesh Agrawal, Secretary, Ministry of Commerce & Industry says, "We are very optimistic and very hopeful that we should find a solution within this calendar year. But as you know, in any trade negotiations, even if there is one sticking point or issue on the mind of even one of the partners, the trade deal may not meet that deadline. The overall position is well set to deliver it in the next few weeks or months as soon as we can. But let's see, it's a call that will have to be taken at multiple levels. At the levels of negotiator, I think we are in a zone where we can say it is something that we can achieve in a very short while of time. There's not much to negotiate...As a country, we have always stood for our own sensitivities and our own uniqueness. So there are areas which are non-negotiable from our perspective..." (Source: FICCI/YouTube)

ANI

13,721 просмотров • 8 месяцев назад

Sequoia's Dean Meyer: "If distillation is real, the question is, how do we address the asymmetry?" "Western companies aren't going to set up 35,000 proxy accounts to steal from Anthropic." "There *is* a structural asymmetry, and it's something we have to think about." "The gap between closed and open source has closed a lot." "And the key conversation online, over the past week, was distillation the reason for this? Or is there some other, mysterious reason?" "The truth is, from the conversations we've had, is that it's somewhere in the middle." "Whether it's 20% or 40%, it doesn't really matter as much. But it's meaningful that we know it's happening." "We know from the labs that there's 10s of millions of queries through these large-scale proxy distillation accounts." "We also know, if you speak to anyone who's leading in synthetic data gen on pre- or post-training at the labs, they will tell you that even if you do hardcore KYC, and then just get access to the output (let's assume you just get the output from the prompt), it is still extremely valuable." "That is 100% true. We know distillation is real."
3:21

Sequoia's Dean Meyer: "If distillation is real, the question is, how do we address the asymmetry?" "Western companies aren't going to set up 35,000 proxy accounts to steal from Anthropic." "There *is* a structural asymmetry, and it's something we have to think about." "The gap between closed and open source has closed a lot." "And the key conversation online, over the past week, was distillation the reason for this? Or is there some other, mysterious reason?" "The truth is, from the conversations we've had, is that it's somewhere in the middle." "Whether it's 20% or 40%, it doesn't really matter as much. But it's meaningful that we know it's happening." "We know from the labs that there's 10s of millions of queries through these large-scale proxy distillation accounts." "We also know, if you speak to anyone who's leading in synthetic data gen on pre- or post-training at the labs, they will tell you that even if you do hardcore KYC, and then just get access to the output (let's assume you just get the output from the prompt), it is still extremely valuable." "That is 100% true. We know distillation is real."

TBPN

43,027 просмотров • 25 дней назад

Asked Joe Mazzulla what he thinks the story of this Celtics team has been: “The story's not done. We are only a product of what we do tomorrow, what we do the next day, and that's just the story. And if we would have lost this game by 1, tomorrow’s film session has to be as detailed and as disciplined as it is going to be with the result that we had. And so that's the story. It's not done yet, and we haven't done anything. All we've done is stick to the process of winning on both ends of the floor, put our head down, don’t overreact to a good win or to a bad loss. And, get better in the next game. So, still plenty of stuff we can get better from tonight. We gave up an ATO lob to LeBron, we gave up two back-cuts, we over-helped a few three point shooters. We got to understand this is when we're at our best, and this is what we have to get better playing against a good Phoenix team who's tough, they kill the margins as well. And then we got a back-to-back. So the story is, it's just not done — and we just got to keep sticking to that process.”
1:54

Asked Joe Mazzulla what he thinks the story of this Celtics team has been: “The story's not done. We are only a product of what we do tomorrow, what we do the next day, and that's just the story. And if we would have lost this game by 1, tomorrow’s film session has to be as detailed and as disciplined as it is going to be with the result that we had. And so that's the story. It's not done yet, and we haven't done anything. All we've done is stick to the process of winning on both ends of the floor, put our head down, don’t overreact to a good win or to a bad loss. And, get better in the next game. So, still plenty of stuff we can get better from tonight. We gave up an ATO lob to LeBron, we gave up two back-cuts, we over-helped a few three point shooters. We got to understand this is when we're at our best, and this is what we have to get better playing against a good Phoenix team who's tough, they kill the margins as well. And then we got a back-to-back. So the story is, it's just not done — and we just got to keep sticking to that process.”

Noa Dalzell 🏀

54,475 просмотров • 6 месяцев назад

The Onion Theory of Risk by Marc Andreessen: "I think the single biggest thing entrepreneurs are missing, both on fundraising and how they run their companies, is the relationship between risk and cash. The relationship between risk and raising cash, and then the relationship between risk and spending cash. So I've always been a fan of something that Andy Ratcliffe taught me years ago, which he called the onion theory of risk. Um, which basically is, you can think about a startup like on day one, um, as having every conceivable kind of risk, right? And you can basically just make a list of the risks. And so you've got, you know, founding team risk. You know, do the founders, are the founders gonna be able to work together? Do you have the right founders? You're gonna have product risk. You know, can you build a product? You'll have technical risk, right? Which is maybe you need a machine learning breakthrough or something to make it work. Are you gonna be able to do that? Um, you'll have, you know, launch risk. Will the launch go well? You'll have, you know, market acceptance risk. You'll have revenue risk. A big risk you get into in a lot of businesses that have a sales force is, can you actually sell the product for enough money to actually pay for the cost of sale? So you have the cost of sale risk. If you're a consumer product, you'll have a viral growth risk. Well, you get the thing of viral growth. And so, a startup at the very beginning is basically just this long list of risks. And then the way that I always think about running a startup is also the way I think about raising money, which is it's a process of peeling away layers of risk as you go. And so you raise seed money in order to peel away the first two or three risks. The founding team risk, the product risk, and maybe the initial launch risk. You raise the A round to peel away the next level of product risk. Maybe you peel away some recruiting risk because you get your full engineering team built. Maybe you peel away some customer risk because you get your first five beta customers. And so basically the way to think about it is you're peeling away risk as you go. You're peeling away risk by achieving milestones. And then as you achieve milestones, you're both making progress in your business, and you're justifying raising more capital. And so you come in, and you pitch somebody like us, and you say you're raising a B round. The best way to do that with us is you say, okay, I raised a seed round, I achieved these milestones, I eliminated these risks. I raised the A round, I achieved these milestones, and I eliminated these risks. Now I'm gonna raise a B round. Here are my milestones, here are my risks. And then by the time I go to raise a seed round, here's the state that I'll be in. And then you calibrate the amount of money that you raise to spend to the risks that you're pulling out of the business. And I go through all this, in a sense this sounds kind of obvious, but I go through all this because it's a systematic way to think about how the money gets raised and deployed. As compared to so much of what's happening, especially these days, which is just, my God, let me go raise as much money as I can. Let me go build the fancy offices, let me go hire as many people as I can, and just kind of hope for the best."
2:21

The Onion Theory of Risk by Marc Andreessen: "I think the single biggest thing entrepreneurs are missing, both on fundraising and how they run their companies, is the relationship between risk and cash. The relationship between risk and raising cash, and then the relationship between risk and spending cash. So I've always been a fan of something that Andy Ratcliffe taught me years ago, which he called the onion theory of risk. Um, which basically is, you can think about a startup like on day one, um, as having every conceivable kind of risk, right? And you can basically just make a list of the risks. And so you've got, you know, founding team risk. You know, do the founders, are the founders gonna be able to work together? Do you have the right founders? You're gonna have product risk. You know, can you build a product? You'll have technical risk, right? Which is maybe you need a machine learning breakthrough or something to make it work. Are you gonna be able to do that? Um, you'll have, you know, launch risk. Will the launch go well? You'll have, you know, market acceptance risk. You'll have revenue risk. A big risk you get into in a lot of businesses that have a sales force is, can you actually sell the product for enough money to actually pay for the cost of sale? So you have the cost of sale risk. If you're a consumer product, you'll have a viral growth risk. Well, you get the thing of viral growth. And so, a startup at the very beginning is basically just this long list of risks. And then the way that I always think about running a startup is also the way I think about raising money, which is it's a process of peeling away layers of risk as you go. And so you raise seed money in order to peel away the first two or three risks. The founding team risk, the product risk, and maybe the initial launch risk. You raise the A round to peel away the next level of product risk. Maybe you peel away some recruiting risk because you get your full engineering team built. Maybe you peel away some customer risk because you get your first five beta customers. And so basically the way to think about it is you're peeling away risk as you go. You're peeling away risk by achieving milestones. And then as you achieve milestones, you're both making progress in your business, and you're justifying raising more capital. And so you come in, and you pitch somebody like us, and you say you're raising a B round. The best way to do that with us is you say, okay, I raised a seed round, I achieved these milestones, I eliminated these risks. I raised the A round, I achieved these milestones, and I eliminated these risks. Now I'm gonna raise a B round. Here are my milestones, here are my risks. And then by the time I go to raise a seed round, here's the state that I'll be in. And then you calibrate the amount of money that you raise to spend to the risks that you're pulling out of the business. And I go through all this, in a sense this sounds kind of obvious, but I go through all this because it's a systematic way to think about how the money gets raised and deployed. As compared to so much of what's happening, especially these days, which is just, my God, let me go raise as much money as I can. Let me go build the fancy offices, let me go hire as many people as I can, and just kind of hope for the best."

Founder Mode

106,909 просмотров • 7 месяцев назад

Amplitude CEO Spenser Skates says the SaaSpocalypse is real, and your old moat is dead. The only moat now is speed of innovation: "You have to be pushing the bleeding edge of what capabilities are. If you create a company that can do that, that's what customers will buy." "What the SaaSpocalypse has gotten right is - if you look at the median SaaS company, their innovation has actually slowed to a standstill." "It's crazy how little they ship in terms of net new products." "Speed of using the bleeding edge of these model capabilities is all that matters. You're even seeing it in the foundational model companies. Opus was the hottest thing a week ago, then it Codex literally launched the same day, saying, 'We're even better, and we're faster and we're on Cerebras chips.' I think all that matters is the rate of improvement." "It's like sushi. Buyers are always going to want the best thing. So if you're keeping up with innovating the best thing, you will be able to charge a premium. It's fine that the 7/11 gas station now sells sushi. It's not going to put Jiro in Japan out of business." "The lesson is - there is no moat anymore from what we've built. There's only a moat if we're able to deliver the most bleeding edge capability."
2:07

Amplitude CEO Spenser Skates says the SaaSpocalypse is real, and your old moat is dead. The only moat now is speed of innovation: "You have to be pushing the bleeding edge of what capabilities are. If you create a company that can do that, that's what customers will buy." "What the SaaSpocalypse has gotten right is - if you look at the median SaaS company, their innovation has actually slowed to a standstill." "It's crazy how little they ship in terms of net new products." "Speed of using the bleeding edge of these model capabilities is all that matters. You're even seeing it in the foundational model companies. Opus was the hottest thing a week ago, then it Codex literally launched the same day, saying, 'We're even better, and we're faster and we're on Cerebras chips.' I think all that matters is the rate of improvement." "It's like sushi. Buyers are always going to want the best thing. So if you're keeping up with innovating the best thing, you will be able to charge a premium. It's fine that the 7/11 gas station now sells sushi. It's not going to put Jiro in Japan out of business." "The lesson is - there is no moat anymore from what we've built. There's only a moat if we're able to deliver the most bleeding edge capability."

TBPN

95,450 просмотров • 6 месяцев назад

Zack Polanski, "The problem is chaining yourself to an economic system that is so fundamentally broken" "You don't get marks or points for just being good, a gold star for doing the basics, or even just under the necessary" "We are at this urgent moment in our history where the only thing that is acceptable is what is required" "What is required is to reduce our emissions, to invest in climate adaptation, to protect nature in one of the most nature depleted countries in the world" "And to make sure we're reinvigorating communities with the truth and putting them in charge" "What is the biggest tool we have?" "It is our shared humanity" "Tackling the cost of living crisis is the same solution as tackling the climate crisis" "It's so vital at this budget that we're cutting bills and taxing billionaires" "There's an implication that all of this is transactional, and the only thing people care about is the money in their pockets" "If you're struggling, that probably is the only thing you care about" "But for so many people, they care about the future of this planet. About clean air. Green spaces" "That when people go to work they have a shared sense of purpose, that it is meaningful and that they are contributing something to society" "We are in a crisis. Climate. Equality. Air pollution. Identity. All of these problems are all interlinked" "And it all comes down to our communities and our humanity"
3:20

Zack Polanski, "The problem is chaining yourself to an economic system that is so fundamentally broken" "You don't get marks or points for just being good, a gold star for doing the basics, or even just under the necessary" "We are at this urgent moment in our history where the only thing that is acceptable is what is required" "What is required is to reduce our emissions, to invest in climate adaptation, to protect nature in one of the most nature depleted countries in the world" "And to make sure we're reinvigorating communities with the truth and putting them in charge" "What is the biggest tool we have?" "It is our shared humanity" "Tackling the cost of living crisis is the same solution as tackling the climate crisis" "It's so vital at this budget that we're cutting bills and taxing billionaires" "There's an implication that all of this is transactional, and the only thing people care about is the money in their pockets" "If you're struggling, that probably is the only thing you care about" "But for so many people, they care about the future of this planet. About clean air. Green spaces" "That when people go to work they have a shared sense of purpose, that it is meaningful and that they are contributing something to society" "We are in a crisis. Climate. Equality. Air pollution. Identity. All of these problems are all interlinked" "And it all comes down to our communities and our humanity"

Farrukh

205,108 просмотров • 9 месяцев назад

Q: Should startups always raise as much money as possible? In the clip below, Marc Andreessen shares a framework that Benchmark co-founder Andy Rachleff taught him called "The Onion Theory of Risk". You can think of a day 1 startup as having every conceivable kind of risk: founding team risk, product risk, technical risk, market acceptance risk, revenue risk, cost of sales risk, viral growth risk, etc. A startup is basically just a long list of risks, and as Marc explains: "The way I think about running a startup is the way I think about raising money. It's a process of peeling away layers of risk as you go." You raise seed money to peel away the first two or three risks (e.g. founding team risk, product risk, initial launch risk). You raise the Series A round to peel away the next layer of risks (e.g. recruiting risk, customer risk, revenue risk, cost of sales risk) And so on. Basically, you're peeling away risk as you're achieving milestones. And as you achieve milestones, you're both: making progress on your business and justifying raising more capital. So in terms of fundraising, you should be calibrating the amount of money you're raising to the risks you need to pull out of your business for you to raise your next round. For example, if you're raising your Series A round, the best way to do that is to say to investors: "I raised a seed round then achieved ____ milestones and eliminated ____ risks. Now I'm going to raise $X for the Series A to achieve ____ milestones and eliminate ____ risks. This will get the company to ____ state for the Series B round. " This seems fairly obvious, but as Marc points out, it's a much more systematic way of going about things versus just raising as much money as possible, renting fancy offices, and hiring as many people as you can to grow as fast as you can. The more money you raise, the more you dilute your ownership stake in your business so it pays to be thoughtful. Raise the capital you will need to achieve the milestones and eliminate the risks required for your next financing round. It also probably makes sense to give yourself some margin as safety because things never go exactly as planned in startup land. Follow Startup Archive for more tactical startup advice!
2:21

Q: Should startups always raise as much money as possible? In the clip below, Marc Andreessen shares a framework that Benchmark co-founder Andy Rachleff taught him called "The Onion Theory of Risk". You can think of a day 1 startup as having every conceivable kind of risk: founding team risk, product risk, technical risk, market acceptance risk, revenue risk, cost of sales risk, viral growth risk, etc. A startup is basically just a long list of risks, and as Marc explains: "The way I think about running a startup is the way I think about raising money. It's a process of peeling away layers of risk as you go." You raise seed money to peel away the first two or three risks (e.g. founding team risk, product risk, initial launch risk). You raise the Series A round to peel away the next layer of risks (e.g. recruiting risk, customer risk, revenue risk, cost of sales risk) And so on. Basically, you're peeling away risk as you're achieving milestones. And as you achieve milestones, you're both: making progress on your business and justifying raising more capital. So in terms of fundraising, you should be calibrating the amount of money you're raising to the risks you need to pull out of your business for you to raise your next round. For example, if you're raising your Series A round, the best way to do that is to say to investors: "I raised a seed round then achieved ____ milestones and eliminated ____ risks. Now I'm going to raise $X for the Series A to achieve ____ milestones and eliminate ____ risks. This will get the company to ____ state for the Series B round. " This seems fairly obvious, but as Marc points out, it's a much more systematic way of going about things versus just raising as much money as possible, renting fancy offices, and hiring as many people as you can to grow as fast as you can. The more money you raise, the more you dilute your ownership stake in your business so it pays to be thoughtful. Raise the capital you will need to achieve the milestones and eliminate the risks required for your next financing round. It also probably makes sense to give yourself some margin as safety because things never go exactly as planned in startup land. Follow Startup Archive for more tactical startup advice!

Startup Archive

178,597 просмотров • 2 лет назад

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 просмотров • 5 месяцев назад

Q: Should startups always raise as much money as possible? In the clip below, Marc Andreessen shares a framework that Benchmark co-founder Andy Rachleff taught him called "The Onion Theory of Risk". You can think of a day 1 startup as having every conceivable kind of risk: founding team risk, product risk, technical risk, market acceptance risk, revenue risk, cost of sales risk, viral growth risk, etc. A startup is basically just a long list of risks, and as Marc explains: "The way I think about running a startup is the way I think about raising money. It's a process of peeling away layers of risk as you go." You raise seed money to peel away the first two or three risks (e.g. founding team risk, product risk, initial launch risk). You raise the Series A round to peel away the next layer of risks (e.g. recruiting risk, customer risk, revenue risk, cost of sales risk) And so on. Basically, you're peeling away risk as you're achieving milestones. And as you achieve milestones, you're both: making progress on your business and justifying raising more capital. So in terms of fundraising, you should be calibrating the amount money you're raising to the risks you need to pull out of your business for you to raise your next round. For example, if you're raising your Series A round, the best way to do that is to say to investors: "I raised a seed round then achieved ____ milestones and eliminated ____ risks. Now I'm going to raise $X for the Series A to achieve ____ milestones and eliminate ____ risks. This will get the company to ____ state for the Series B round. " This seems fairly obvious, but as Marc points out, it's a much more systematic way of going about things versus just raising as much money as possible, renting fancy offices, and hiring as many people as you can to grow as fast as you can. The more money you raise, the more you dilute your ownership stake in your business so it pays to be thoughtful. Raise the capital you will need to achieve the milestones and eliminate the risks required for your next financing round. It also probably makes sense to give yourself some margin as safety because things never go exactly as planned in startup land.
2:21

Q: Should startups always raise as much money as possible? In the clip below, Marc Andreessen shares a framework that Benchmark co-founder Andy Rachleff taught him called "The Onion Theory of Risk". You can think of a day 1 startup as having every conceivable kind of risk: founding team risk, product risk, technical risk, market acceptance risk, revenue risk, cost of sales risk, viral growth risk, etc. A startup is basically just a long list of risks, and as Marc explains: "The way I think about running a startup is the way I think about raising money. It's a process of peeling away layers of risk as you go." You raise seed money to peel away the first two or three risks (e.g. founding team risk, product risk, initial launch risk). You raise the Series A round to peel away the next layer of risks (e.g. recruiting risk, customer risk, revenue risk, cost of sales risk) And so on. Basically, you're peeling away risk as you're achieving milestones. And as you achieve milestones, you're both: making progress on your business and justifying raising more capital. So in terms of fundraising, you should be calibrating the amount money you're raising to the risks you need to pull out of your business for you to raise your next round. For example, if you're raising your Series A round, the best way to do that is to say to investors: "I raised a seed round then achieved ____ milestones and eliminated ____ risks. Now I'm going to raise $X for the Series A to achieve ____ milestones and eliminate ____ risks. This will get the company to ____ state for the Series B round. " This seems fairly obvious, but as Marc points out, it's a much more systematic way of going about things versus just raising as much money as possible, renting fancy offices, and hiring as many people as you can to grow as fast as you can. The more money you raise, the more you dilute your ownership stake in your business so it pays to be thoughtful. Raise the capital you will need to achieve the milestones and eliminate the risks required for your next financing round. It also probably makes sense to give yourself some margin as safety because things never go exactly as planned in startup land.

Michael McGuiness

735,645 просмотров • 3 лет назад

Palantir CTO Shyam Sankar says Chinese open source models pose a "threat to American Prosperity": "These Chinese open source models are really the result of distillation attacks." "Most of this is just stolen American IP from frontier labs, and I think the frontier labs should do more to protect that IP, and that's in their own economic interest." "The gravest threat to us is not homicide, it's suicide." "It's an inability to turn these tokens into economic value and generate American prosperity for it." "You see that with the proposed moratorium in New York on data centers. Turning our back on AI would be as consequential a mistake as turning our back on the atom in the '70s." "It's just the beginning, but we're starting to see a burgeoning US open model ecosystem forming." "NVIDIA's Nemotron models are very good." "I think you're going to see in the next month a slate of announcements of other American companies, non-frontier labs, neo labs, who are putting out open weight models that companies are going to be able to cheaply fine-tune and capture their own alpha in weights they control." Via Bloomberg
1:21

Palantir CTO Shyam Sankar says Chinese open source models pose a "threat to American Prosperity": "These Chinese open source models are really the result of distillation attacks." "Most of this is just stolen American IP from frontier labs, and I think the frontier labs should do more to protect that IP, and that's in their own economic interest." "The gravest threat to us is not homicide, it's suicide." "It's an inability to turn these tokens into economic value and generate American prosperity for it." "You see that with the proposed moratorium in New York on data centers. Turning our back on AI would be as consequential a mistake as turning our back on the atom in the '70s." "It's just the beginning, but we're starting to see a burgeoning US open model ecosystem forming." "NVIDIA's Nemotron models are very good." "I think you're going to see in the next month a slate of announcements of other American companies, non-frontier labs, neo labs, who are putting out open weight models that companies are going to be able to cheaply fine-tune and capture their own alpha in weights they control." Via Bloomberg

Jawwwn

180,421 просмотров • 1 месяц назад

Q: It's thought in the paddock that your car is actually the best chassis and if you can get that extra bit of power you are the ones to beat. So are you thinking if we can just get this [Engine ADUO] we know we have an incredible car? Lewis Hamilton: "Yes absolutely, I mean the guys at the factory have done an amazing job with the car and we still have improvements to make but the car is fantastic it's just it's a battle of development through the season obviously some people bring upgrades one weekend and others the other but yeah we're just at the mercy of the lack of power that we have and I know that everyone worked really hard on the engine and reliability is obviously is very good it's just when you're lacking that straight line speed against the Merc it's very very tough but nonetheless you know we have to expect that the rest of the season that's just the way it is so we'll just try and see if we can continue to add on to the car and try and close the gap if we can go through quicker through corners in some races maybe we can get closer to a challenge in front of us." F1 2026 || Canada
1:14

Q: It's thought in the paddock that your car is actually the best chassis and if you can get that extra bit of power you are the ones to beat. So are you thinking if we can just get this [Engine ADUO] we know we have an incredible car? Lewis Hamilton: "Yes absolutely, I mean the guys at the factory have done an amazing job with the car and we still have improvements to make but the car is fantastic it's just it's a battle of development through the season obviously some people bring upgrades one weekend and others the other but yeah we're just at the mercy of the lack of power that we have and I know that everyone worked really hard on the engine and reliability is obviously is very good it's just when you're lacking that straight line speed against the Merc it's very very tough but nonetheless you know we have to expect that the rest of the season that's just the way it is so we'll just try and see if we can continue to add on to the car and try and close the gap if we can go through quicker through corners in some races maybe we can get closer to a challenge in front of us." F1 2026 || Canada

sim

23,426 просмотров • 3 месяцев назад