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Chamath: US AI Startups Can Learn A Lot from DeepSeek "This is a case where necessity was the mother of invention." On E213, Chamath Palihapitiya explained how, even if the $6M number is inaccurate, DeepSeek still had some impressive breakthroughs: GRPO > PPO for reinforcement learning "These guys were...

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The All-In Podcast

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108,815 görüntüleme • 1 yıl önce •via X (Twitter)

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Newtonian1 yıl önce

@chamath @deepseek_ai More with less. Should always be the motto for startups. Now especially with AI, as compute costs go down, the real innovation would be things like what DeepSeek did.

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Fast Company1 yıl önce

4 ways #AI can help in a challenging market. Find out how your company can harness the potential of AI while minimizing risks and paving the way for more ambitious applications as the technology continues to develop. Learn more at @JLL. #ad

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Maurice1 yıl önce

@chamath @deepseek_ai This last episode was an epic one filled with alpha

Sung Jin Woo CEO of Henlo profil fotoğrafı
Sung Jin Woo CEO of Henlo1 yıl önce

@chamath @deepseek_ai Necessity is great, but have you tried adding a sprinkle of PublicAI magic? Who knew data could be so rewarding—like a treasure hunt for AI! 🏴‍☠️💰

_LUFFY_꧁IP꧂ (✸,✸)🦙🔥bao bao 🐼 profil fotoğrafı
_LUFFY_꧁IP꧂ (✸,✸)🦙🔥bao bao 🐼1 yıl önce

@chamath @deepseek_ai Necessity is great, but have you tried data from PublicAI? It’s like giving your AI a superpower smoothie—impressive breakthroughs guaranteed! 🥤🤖

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Mehdi$ODY1 yıl önce

@chamath @deepseek_ai Necessity is great, but have you tried using PublicAI? It’s like giving your data a gym membership—watch it get fit while you earn rewards! 💪😂

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Joe Dunikoski1 yıl önce

@chamath @deepseek_ai Check out Optimal Work. Will simulate the incredible adrenaline benefits of deadlines (or short cash runways) everyday.

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Tahsan Islam Tamzid1 yıl önce

@chamath @deepseek_ai Necessity is great, but have you tried feeding AI with data from everyday folks? PublicAI makes it easy—no $6M needed, just a sprinkle of community magic! 😂

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Moses Balogun1 yıl önce

@chamath @deepseek_ai Maybe US startups need a little more 'PublicAI' spirit! Who knew constraints could spark genius? Next up: Reinventing the wheel with a side of blockchain! 😂

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Ilya Sutskever explains why AI will do 100% the work that human can do within few years. "Slowly but surely, or maybe not so slowly, AI will keep getting better. The day will come when AI will do all of our, all the things that we can do, not just some of them, but all of them. Anything which I can learn, anything which any one of you can learn, the AI could do as well. How do we know this, by the way? How can I be so sure? How can I be so sure of that? The reason is that all of us have a brain, and the brain is a biological computer. That's why we have a brain; the brain is a biological computer. So why can't the digital computer, a digital brain, do the same things? This is the one-sentence summary for why AI will be able to do all those things: because we have a brain, and the brain is a biological computer." --- Full Video on 'University of Toronto' YT Channel (link in comment)
0:53

Ilya Sutskever explains why AI will do 100% the work that human can do within few years. "Slowly but surely, or maybe not so slowly, AI will keep getting better. The day will come when AI will do all of our, all the things that we can do, not just some of them, but all of them. Anything which I can learn, anything which any one of you can learn, the AI could do as well. How do we know this, by the way? How can I be so sure? How can I be so sure of that? The reason is that all of us have a brain, and the brain is a biological computer. That's why we have a brain; the brain is a biological computer. So why can't the digital computer, a digital brain, do the same things? This is the one-sentence summary for why AI will be able to do all those things: because we have a brain, and the brain is a biological computer." --- Full Video on 'University of Toronto' YT Channel (link in comment)

Rohan Paul

334,691 görüntüleme • 10 ay önce

Chamath: "Nvidia is not doing what's in the best interest of the United States." 🇺🇸🇨🇳 "I think we can all do the math. About 47% of all of NVIDIA's revenue goes to China and Chinese-related countries." "And I think when you peel back this onion, what you will find is a whole raft of companies that were stood up to buy these Nvidia GPUs to essentially act as a waystation for China." "And I think that is the big problem." "Let's have a thought starter: if 47% of all of the AI capability and horsepower is being shipped to three Asian countries, where do you think the apps that require that amount of horsepower live?" "Is there a Cursor of Bhutan that we did not know? Is there a great shopping app in Cambodia that's come out of nowhere, that's AI powered?" "I think the answer is no." "Every single time we have an advance in the United States, how is it that Alibaba shows up with something incredible? DeepSeek shows up with something better?" "At every turn and at every step of AI, they are at the same rate or one step ahead." "To be honest with you, I think the real problem that we have is that Nvidia is not doing what is in the best interest of the United States." "You have a American company that has been working around the guidelines at every turn to try to land silicon into the hands of China." "Late last year, they introduced this thing called the H20 that was explicitly designed for China and to be compliant with US rules at the time." "Which again, gives these guys substantial performance." "This is a case where (Nvidia) has plausible deniability. I sell something to a Singaporean registered company? Plausible deniability." "What am I supposed to do? You can't expect me to audit it. I think that's what NVIDIA's answer will be to this question." "But what is the real expectation? At a minimum, the United States should have a mechanism to understand it." "It is implausible that if you did one or two layers of work, you would not find that most of this traffic is being used by Chinese organizations."
1:53

Chamath: "Nvidia is not doing what's in the best interest of the United States." 🇺🇸🇨🇳 "I think we can all do the math. About 47% of all of NVIDIA's revenue goes to China and Chinese-related countries." "And I think when you peel back this onion, what you will find is a whole raft of companies that were stood up to buy these Nvidia GPUs to essentially act as a waystation for China." "And I think that is the big problem." "Let's have a thought starter: if 47% of all of the AI capability and horsepower is being shipped to three Asian countries, where do you think the apps that require that amount of horsepower live?" "Is there a Cursor of Bhutan that we did not know? Is there a great shopping app in Cambodia that's come out of nowhere, that's AI powered?" "I think the answer is no." "Every single time we have an advance in the United States, how is it that Alibaba shows up with something incredible? DeepSeek shows up with something better?" "At every turn and at every step of AI, they are at the same rate or one step ahead." "To be honest with you, I think the real problem that we have is that Nvidia is not doing what is in the best interest of the United States." "You have a American company that has been working around the guidelines at every turn to try to land silicon into the hands of China." "Late last year, they introduced this thing called the H20 that was explicitly designed for China and to be compliant with US rules at the time." "Which again, gives these guys substantial performance." "This is a case where (Nvidia) has plausible deniability. I sell something to a Singaporean registered company? Plausible deniability." "What am I supposed to do? You can't expect me to audit it. I think that's what NVIDIA's answer will be to this question." "But what is the real expectation? At a minimum, the United States should have a mechanism to understand it." "It is implausible that if you did one or two layers of work, you would not find that most of this traffic is being used by Chinese organizations."

The All-In Podcast

910,407 görüntüleme • 1 yıl önce

Chamath: Anthropic's Mythos Warning Is Theater @jason: “Chamath, is it the Boy who Cried Wolf, or is this the real deal now?” Chamath Palihapitiya: “I think it's mostly theater. In February of 2019 when Dario was still at OpenAI, they did the same thing with GPT-2. That was a 1.5 billion parameter model, which sounds like a total fart in the wind in 2026. But at that time, this model was supposed to be the end of days. And at the end of it, it was a huge nothingburger. If you actually think that Mythos is capable of doing what it says it can do, two things are true. One is, a very sophisticated hacker can probably do those things right now with Opus. And two, if these exploits are this easy to find, whether you use Opus or whether you use Mythos, the reality is you'd have to shut down the internet for about five years to patch them all. So when you see a large multi-trillion dollar GSIB bank, it's a bit of theater. Why? What do you think they can actually accomplish in two months? Do you actually think that if there's these vulnerabilities, it's all going to get fixed? Let's give them six months, let's give them nine months. So I do think that Sacks is right, that they have figured out a very clever go-to-market muscle here that activates hyper attention and hyper usage, and so I give them tremendous credit. But we've seen it before, we saw it when these folks were the principal architects at OpenAI, and we're now seeing the same playbook here. The reality is that capitalism moves forward, the funding needs moves forward, and the need for these guys to build adoption moves forward. And that's going to supersede what this is.”
1:43

Chamath: Anthropic's Mythos Warning Is Theater @jason: “Chamath, is it the Boy who Cried Wolf, or is this the real deal now?” Chamath Palihapitiya: “I think it's mostly theater. In February of 2019 when Dario was still at OpenAI, they did the same thing with GPT-2. That was a 1.5 billion parameter model, which sounds like a total fart in the wind in 2026. But at that time, this model was supposed to be the end of days. And at the end of it, it was a huge nothingburger. If you actually think that Mythos is capable of doing what it says it can do, two things are true. One is, a very sophisticated hacker can probably do those things right now with Opus. And two, if these exploits are this easy to find, whether you use Opus or whether you use Mythos, the reality is you'd have to shut down the internet for about five years to patch them all. So when you see a large multi-trillion dollar GSIB bank, it's a bit of theater. Why? What do you think they can actually accomplish in two months? Do you actually think that if there's these vulnerabilities, it's all going to get fixed? Let's give them six months, let's give them nine months. So I do think that Sacks is right, that they have figured out a very clever go-to-market muscle here that activates hyper attention and hyper usage, and so I give them tremendous credit. But we've seen it before, we saw it when these folks were the principal architects at OpenAI, and we're now seeing the same playbook here. The reality is that capitalism moves forward, the funding needs moves forward, and the need for these guys to build adoption moves forward. And that's going to supersede what this is.”

The All-In Podcast

220,049 görüntüleme • 3 ay önce

The most interesting part for me is where Andrej Karpathy describes why LLMs aren't able to learn like humans. As you would expect, he comes up with a wonderfully evocative phrase to describe RL: “sucking supervision bits through a straw.” A single end reward gets broadcast across every token in a successful trajectory, upweighting even wrong or irrelevant turns that lead to the right answer. > “Humans don't use reinforcement learning, as I've said before. I think they do something different. Reinforcement learning is a lot worse than the average person thinks. Reinforcement learning is terrible. It just so happens that everything that we had before is much worse.” So what do humans do instead? > “The book I’m reading is a set of prompts for me to do synthetic data generation. It's by manipulating that information that you actually gain that knowledge. We have no equivalent of that with LLMs; they don't really do that.” > “I'd love to see during pretraining some kind of a stage where the model thinks through the material and tries to reconcile it with what it already knows. There's no equivalent of any of this. This is all research.” Why can’t we just add this training to LLMs today? > “There are very subtle, hard to understand reasons why it's not trivial. If I just give synthetic generation of the model thinking about a book, you look at it and you're like, 'This looks great. Why can't I train on it?' You could try, but the model will actually get much worse if you continue trying.” > “Say we have a chapter of a book and I ask an LLM to think about it. It will give you something that looks very reasonable. But if I ask it 10 times, you'll notice that all of them are the same.” > “You're not getting the richness and the diversity and the entropy from these models as you would get from humans. How do you get synthetic data generation to work despite the collapse and while maintaining the entropy? It is a research problem.” How do humans get around model collapse? > “These analogies are surprisingly good. Humans collapse during the course of their lives. Children haven't overfit yet. They will say stuff that will shock you. Because they're not yet collapsed. But we [adults] are collapsed. We end up revisiting the same thoughts, we end up saying more and more of the same stuff, the learning rates go down, the collapse continues to get worse, and then everything deteriorates.” In fact, there’s an interesting paper arguing that dreaming evolved to assist generalization, and resist overfitting to daily learning - look up The Overfitted Brain by Erik Hoel. I asked Karpathy: Isn’t it interesting that humans learn best at a part of their lives (childhood) whose actual details they completely forget, adults still learn really well but have terrible memory about the particulars of the things they read or watch, and LLMs can memorize arbitrary details about text that no human could but are currently pretty bad at generalization? > “[Fallible human memory] is a feature, not a bug, because it forces you to only learn the generalizable components. LLMs are distracted by all the memory that they have of the pre-trained documents. That's why when I talk about the cognitive core, I actually want to remove the memory. I'd love to have them have less memory so that they have to look things up and they only maintain the algorithms for thought, and the idea of an experiment, and all this cognitive glue for acting.”
7:01

The most interesting part for me is where Andrej Karpathy describes why LLMs aren't able to learn like humans. As you would expect, he comes up with a wonderfully evocative phrase to describe RL: “sucking supervision bits through a straw.” A single end reward gets broadcast across every token in a successful trajectory, upweighting even wrong or irrelevant turns that lead to the right answer. > “Humans don't use reinforcement learning, as I've said before. I think they do something different. Reinforcement learning is a lot worse than the average person thinks. Reinforcement learning is terrible. It just so happens that everything that we had before is much worse.” So what do humans do instead? > “The book I’m reading is a set of prompts for me to do synthetic data generation. It's by manipulating that information that you actually gain that knowledge. We have no equivalent of that with LLMs; they don't really do that.” > “I'd love to see during pretraining some kind of a stage where the model thinks through the material and tries to reconcile it with what it already knows. There's no equivalent of any of this. This is all research.” Why can’t we just add this training to LLMs today? > “There are very subtle, hard to understand reasons why it's not trivial. If I just give synthetic generation of the model thinking about a book, you look at it and you're like, 'This looks great. Why can't I train on it?' You could try, but the model will actually get much worse if you continue trying.” > “Say we have a chapter of a book and I ask an LLM to think about it. It will give you something that looks very reasonable. But if I ask it 10 times, you'll notice that all of them are the same.” > “You're not getting the richness and the diversity and the entropy from these models as you would get from humans. How do you get synthetic data generation to work despite the collapse and while maintaining the entropy? It is a research problem.” How do humans get around model collapse? > “These analogies are surprisingly good. Humans collapse during the course of their lives. Children haven't overfit yet. They will say stuff that will shock you. Because they're not yet collapsed. But we [adults] are collapsed. We end up revisiting the same thoughts, we end up saying more and more of the same stuff, the learning rates go down, the collapse continues to get worse, and then everything deteriorates.” In fact, there’s an interesting paper arguing that dreaming evolved to assist generalization, and resist overfitting to daily learning - look up The Overfitted Brain by Erik Hoel. I asked Karpathy: Isn’t it interesting that humans learn best at a part of their lives (childhood) whose actual details they completely forget, adults still learn really well but have terrible memory about the particulars of the things they read or watch, and LLMs can memorize arbitrary details about text that no human could but are currently pretty bad at generalization? > “[Fallible human memory] is a feature, not a bug, because it forces you to only learn the generalizable components. LLMs are distracted by all the memory that they have of the pre-trained documents. That's why when I talk about the cognitive core, I actually want to remove the memory. I'd love to have them have less memory so that they have to look things up and they only maintain the algorithms for thought, and the idea of an experiment, and all this cognitive glue for acting.”

Dwarkesh Patel

1,051,064 görüntüleme • 9 ay önce

Interview from 5 months ago with “RA” the new UFO whistleblower Randy Anderson by Gerb Here he describes the sphere encounter and the possible consciousness connection and how his memories of the incident are strangely fuzzy Link to full interview in comments H/T wow RA - “Both the items they had under there, they said somehow interacted with consciousness and, and the way he said it, this is why it's so fuzzy, he said, I wouldn't quote these things 'cause I'm gonna try to just remember the, the, the context. And I, and I can again, like when I meditate and I think about this, I can usually get more back. But just, just like sitting here talking to you and remembering it, it's difficult sometimes. But I remember him saying, we don't understand quite how to operate the systems or how they, but they do interact with consciousness so certain and some people they interact with and some people they don't. So certain people will go up to the object and it will respond. And some people go up to the object and it does nothing. So certain types of, I don't know if that's related to DNA or to consciousness or what, whatever, but it's different. People will have a different response and they, they had us kind of walked closer to the, the window and nothing happened. So we didn't, I mean, I don't know if we got closer or something would've happened, but they, I don't know if they were even looking for that, but maybe, you know, that they, that's one thing he said that like certain people will go near the object and will react. And he didn't describe how it would react. He instead it would react,” RA - “There's a really weird component to this, and I don't know what this means, but when I think back to this particular memory and, and this never happens to me in any other thing, I, I get real fuzzy. It gets real fuzzy, like, like almost like something was purposely done to to, to make it that way. Because I have a very photographic memory and things I've done in the military. Like I can tell you the color of the buttons on a shirt of a guy that I sniped from, you know, 800 feet, 800 meters away. So I mean, I, there's for me to not remember this is really bothers me, but there's, there's some cloudiness when I try to access this part of my brain, you know, I can definitely, maybe it's, it could definitely be the, the objects itself that had, and it felt this, this is why it's difficult because it obviously, it felt weird being down there. Okay. There's, there's something like, there was just, it is an unnatural feeling we're doing. It felt like we were doing something that wasn't normal. I mean, the fact that we were so deep underground, me and the dude were kind of freaked out and, and, but we didn't display that outwardly because we're trained to not do that, you know? But internally, yeah, I was like, what the hell is going on? And when they talk about optimal stuff, they didn't say it like, by the way, aliens are real like you or anything like of that sort. It was just, oh yeah, this is the off world technology division, this is Chuck, this is whatever. And just started talking like everything was normal and we just went along with it because we acted like it was normal, but the first time I'd ever been exposed to it and it, it was a lot to take in. So that could be part of it too.”
4:48

Interview from 5 months ago with “RA” the new UFO whistleblower Randy Anderson by Gerb Here he describes the sphere encounter and the possible consciousness connection and how his memories of the incident are strangely fuzzy Link to full interview in comments H/T wow RA - “Both the items they had under there, they said somehow interacted with consciousness and, and the way he said it, this is why it's so fuzzy, he said, I wouldn't quote these things 'cause I'm gonna try to just remember the, the, the context. And I, and I can again, like when I meditate and I think about this, I can usually get more back. But just, just like sitting here talking to you and remembering it, it's difficult sometimes. But I remember him saying, we don't understand quite how to operate the systems or how they, but they do interact with consciousness so certain and some people they interact with and some people they don't. So certain people will go up to the object and it will respond. And some people go up to the object and it does nothing. So certain types of, I don't know if that's related to DNA or to consciousness or what, whatever, but it's different. People will have a different response and they, they had us kind of walked closer to the, the window and nothing happened. So we didn't, I mean, I don't know if we got closer or something would've happened, but they, I don't know if they were even looking for that, but maybe, you know, that they, that's one thing he said that like certain people will go near the object and will react. And he didn't describe how it would react. He instead it would react,” RA - “There's a really weird component to this, and I don't know what this means, but when I think back to this particular memory and, and this never happens to me in any other thing, I, I get real fuzzy. It gets real fuzzy, like, like almost like something was purposely done to to, to make it that way. Because I have a very photographic memory and things I've done in the military. Like I can tell you the color of the buttons on a shirt of a guy that I sniped from, you know, 800 feet, 800 meters away. So I mean, I, there's for me to not remember this is really bothers me, but there's, there's some cloudiness when I try to access this part of my brain, you know, I can definitely, maybe it's, it could definitely be the, the objects itself that had, and it felt this, this is why it's difficult because it obviously, it felt weird being down there. Okay. There's, there's something like, there was just, it is an unnatural feeling we're doing. It felt like we were doing something that wasn't normal. I mean, the fact that we were so deep underground, me and the dude were kind of freaked out and, and, but we didn't display that outwardly because we're trained to not do that, you know? But internally, yeah, I was like, what the hell is going on? And when they talk about optimal stuff, they didn't say it like, by the way, aliens are real like you or anything like of that sort. It was just, oh yeah, this is the off world technology division, this is Chuck, this is whatever. And just started talking like everything was normal and we just went along with it because we acted like it was normal, but the first time I'd ever been exposed to it and it, it was a lot to take in. So that could be part of it too.”

neandrewthal

41,422 görüntüleme • 1 yıl önce

Chamath: Frontier AI Leaders “Created a Total F*cking Mess” Short-sighted fearmongering and immaturity from frontier AI leaders has created deep mistrust, threatening AI’s potential as an open engine of economic mobility. That mistrust gives hyperscalers the chance to position themselves as trusted gatekeepers, using KYC, audit trails, and compliance infrastructure to turn AI into an oligopoly. Chamath Palihapitiya on the All-In Pod: “I think the leaders of the frontier labs leave a lot to be desired. I think what we're seeing is a consistent pattern of evasiveness and immaturity, and I think that does a huge disservice to the entire movement of AI. The key to a vibrant life is rooted in economic mobility, and I think AI is the grand leveler. It is the thing that can enable everyone to have unique amounts of economic mobility because they are unencumbered to figure out what their upper bound is. And against that backdrop, we have to live in this constant doomerism, hype cycle, naivety, and I think it holds us back. How does it hold us back? Tactically, number one, it creates mistrust. I think that Silicon Valley was already decaying in the prestige that it held in American society. We built important things. Then we veered away from that, and we started building less important things. And now we're at a point where we've potentially started to rebuild important things again, but we have this veneer of negativity and mistrust that are created in large part because we just cannot get our sh*t together. And the leaders of the frontier labs are public enemy number one. Number two, I think what it creates, which I think is bad, but what it creates is an incredible opportunity for the hyperscalers. And the very simple opportunity is to convince governments all around the world, not just America, that they should be the gatekeeper. A: You can't trust these guys. B: These models are all over the place. C: Let us be the ones that provision them to the world. We will wrap it in KYC. I've been now talking about KYC for a while, right? Who are these customers? Do they have identification? Why are they allowed to run these models? What are they prompting? Let's keep them so that there's an audit trail. All of these things are going to become issues. The Frontier Lab folks made it an issue because of how they've handled all of this up until now. And what does that create? Now that creates an oligopoly for AI, the most powerful economically leveling instrument we've ever seen in the hands of maybe a handful of hyperscalers, who by the way, would make an incredibly compelling argument, and they would be right. And the only counterfactual to it would be, ‘Well, trust us, guys, it should actually be much more open and in a far more distributed environment.’ Can you imagine the cost and the complexity if you ask the neoscaler to build the same robust KYC or the same VPC infrastructure that Amazon and Microsoft and Google have spent decades investing trillions of dollars in? It's an impossibility, Jason. So you can take all of those datacenters off the map. You can take all of the neoscaler market off the map. All of this was preventable. So instead of a diverse, robust, open ecosystem giving a tool that is the fundamental unlock for humans, we are now going to debate gatekeeping and duopoly versus oligopoly. They have created a total f*cking mess, and it's a shame.”
3:26

Chamath: Frontier AI Leaders “Created a Total F*cking Mess” Short-sighted fearmongering and immaturity from frontier AI leaders has created deep mistrust, threatening AI’s potential as an open engine of economic mobility. That mistrust gives hyperscalers the chance to position themselves as trusted gatekeepers, using KYC, audit trails, and compliance infrastructure to turn AI into an oligopoly. Chamath Palihapitiya on the All-In Pod: “I think the leaders of the frontier labs leave a lot to be desired. I think what we're seeing is a consistent pattern of evasiveness and immaturity, and I think that does a huge disservice to the entire movement of AI. The key to a vibrant life is rooted in economic mobility, and I think AI is the grand leveler. It is the thing that can enable everyone to have unique amounts of economic mobility because they are unencumbered to figure out what their upper bound is. And against that backdrop, we have to live in this constant doomerism, hype cycle, naivety, and I think it holds us back. How does it hold us back? Tactically, number one, it creates mistrust. I think that Silicon Valley was already decaying in the prestige that it held in American society. We built important things. Then we veered away from that, and we started building less important things. And now we're at a point where we've potentially started to rebuild important things again, but we have this veneer of negativity and mistrust that are created in large part because we just cannot get our sh*t together. And the leaders of the frontier labs are public enemy number one. Number two, I think what it creates, which I think is bad, but what it creates is an incredible opportunity for the hyperscalers. And the very simple opportunity is to convince governments all around the world, not just America, that they should be the gatekeeper. A: You can't trust these guys. B: These models are all over the place. C: Let us be the ones that provision them to the world. We will wrap it in KYC. I've been now talking about KYC for a while, right? Who are these customers? Do they have identification? Why are they allowed to run these models? What are they prompting? Let's keep them so that there's an audit trail. All of these things are going to become issues. The Frontier Lab folks made it an issue because of how they've handled all of this up until now. And what does that create? Now that creates an oligopoly for AI, the most powerful economically leveling instrument we've ever seen in the hands of maybe a handful of hyperscalers, who by the way, would make an incredibly compelling argument, and they would be right. And the only counterfactual to it would be, ‘Well, trust us, guys, it should actually be much more open and in a far more distributed environment.’ Can you imagine the cost and the complexity if you ask the neoscaler to build the same robust KYC or the same VPC infrastructure that Amazon and Microsoft and Google have spent decades investing trillions of dollars in? It's an impossibility, Jason. So you can take all of those datacenters off the map. You can take all of the neoscaler market off the map. All of this was preventable. So instead of a diverse, robust, open ecosystem giving a tool that is the fundamental unlock for humans, we are now going to debate gatekeeping and duopoly versus oligopoly. They have created a total f*cking mess, and it's a shame.”

The All-In Podcast

141,660 görüntüleme • 27 gün önce

David Friedberg on the Nonprofit Scam: 90% Are Bullsh*t “ The definition of exempt activities is charitable, religious, educational, scientific, literacy, public safety, or fostering amateur sports competition, or preventing cruelty to children or animals. You tell me how the f**k 90% of what we call nonprofits today fall under that definition. We have completely f**king closed our eyes to the fact that organizations, regardless of political affiliation or social interest, have fundamental commercial and probably not aligned interests with the definition of a 501(c)(3), and we've allowed them all to get away with it for far too long. I don't think that this is a blue or red thing. I think that this is a thing where we let these organizations make it easy to get money, to hide the money, and to do whatever the hell they want with the money, and we need to stop it. And I think that it's an amazing opportunity right now for everyone to kind of reset the decks by cleaning all the sh*t up, and getting all of these organizations flushed, and make sure that any organization that wants to do whatever bullsh*t, nefarious things they want to do, by all means do it. But it's not a nonprofit and you shouldn't get a charitable donation deduction, and the government should not be putting money into these sorts of things. This is an entirely different sort of activity in the social order. And as a libertarian, I'm all for it, but I don't think that they should be tax exempt, and I don't think they should be getting government money, and I don't think that individuals should be benefiting from giving them money. And if we could fix all that shit up, I think a lot of these problems are going to go away.”
1:31

David Friedberg on the Nonprofit Scam: 90% Are Bullsh*t “ The definition of exempt activities is charitable, religious, educational, scientific, literacy, public safety, or fostering amateur sports competition, or preventing cruelty to children or animals. You tell me how the f**k 90% of what we call nonprofits today fall under that definition. We have completely f**king closed our eyes to the fact that organizations, regardless of political affiliation or social interest, have fundamental commercial and probably not aligned interests with the definition of a 501(c)(3), and we've allowed them all to get away with it for far too long. I don't think that this is a blue or red thing. I think that this is a thing where we let these organizations make it easy to get money, to hide the money, and to do whatever the hell they want with the money, and we need to stop it. And I think that it's an amazing opportunity right now for everyone to kind of reset the decks by cleaning all the sh*t up, and getting all of these organizations flushed, and make sure that any organization that wants to do whatever bullsh*t, nefarious things they want to do, by all means do it. But it's not a nonprofit and you shouldn't get a charitable donation deduction, and the government should not be putting money into these sorts of things. This is an entirely different sort of activity in the social order. And as a libertarian, I'm all for it, but I don't think that they should be tax exempt, and I don't think they should be getting government money, and I don't think that individuals should be benefiting from giving them money. And if we could fix all that shit up, I think a lot of these problems are going to go away.”

The All-In Podcast

574,676 görüntüleme • 2 ay önce

What's the Big Deal with DeepSeek in AI? Here's why DeepSeek is making everyone take notice: 1. Super Smart on a Budget: DeepSeek showed you can make awesome AI without breaking the bank. Their latest model, DeepSeek-V3, was trained for only about $10 million, which is a lot less than the usual big bucks spent on AI, like the rumored $78 million for some of OpenAI's models. They did this in just two months with fewer fancy computers. 2. Open for Everyone: DeepSeek isn't keeping their tech a secret. They've made it open-source, meaning anyone can use, tweak, and learn from it. It's like they're saying, "Come join the party!" 3. Beating the Big Names: DeepSeek-V3 has done better than some top dogs from companies like OpenAI and Google in solving puzzles, math, and coding. This proves you can get great AI results without spending a fortune. 4. Challenging NVIDIA: NVIDIA's chips are usually the choice for AI because they're really powerful. But since DeepSeek did so well with less expensive chips, it might make people think twice about always going for NVIDIA's priciest options. 5. The DeepSeek Crew: The team at DeepSeek is young and smart, mostly from top Chinese schools, with brains in physics, math, and computer science. They learned AI in about six months by themselves! They use first principle thinking, which means they break down problems to the basics and build from there. This has helped them come up with cool new ways to do AI. 6. Changing AI for Good: DeepSeek is showing that AI can be cheaper and more open to everyone. They're changing how we think AI should be made and shared, which could shake up the whole AI world. So, as we watch DeepSeek, it's clear they're not just another player; they're changing the rules of the game. I predicted that this would be a make or break year for all the massive investments made in AI by American VC's. A few weeks later, DeepSeek happens! Watch the rest of my predictions in my 2025 outlook video . Link in replies #AIInnovation #DeepSeek #NVIDIA #OpenAI #TechDisruption
0:44

What's the Big Deal with DeepSeek in AI? Here's why DeepSeek is making everyone take notice: 1. Super Smart on a Budget: DeepSeek showed you can make awesome AI without breaking the bank. Their latest model, DeepSeek-V3, was trained for only about $10 million, which is a lot less than the usual big bucks spent on AI, like the rumored $78 million for some of OpenAI's models. They did this in just two months with fewer fancy computers. 2. Open for Everyone: DeepSeek isn't keeping their tech a secret. They've made it open-source, meaning anyone can use, tweak, and learn from it. It's like they're saying, "Come join the party!" 3. Beating the Big Names: DeepSeek-V3 has done better than some top dogs from companies like OpenAI and Google in solving puzzles, math, and coding. This proves you can get great AI results without spending a fortune. 4. Challenging NVIDIA: NVIDIA's chips are usually the choice for AI because they're really powerful. But since DeepSeek did so well with less expensive chips, it might make people think twice about always going for NVIDIA's priciest options. 5. The DeepSeek Crew: The team at DeepSeek is young and smart, mostly from top Chinese schools, with brains in physics, math, and computer science. They learned AI in about six months by themselves! They use first principle thinking, which means they break down problems to the basics and build from there. This has helped them come up with cool new ways to do AI. 6. Changing AI for Good: DeepSeek is showing that AI can be cheaper and more open to everyone. They're changing how we think AI should be made and shared, which could shake up the whole AI world. So, as we watch DeepSeek, it's clear they're not just another player; they're changing the rules of the game. I predicted that this would be a make or break year for all the massive investments made in AI by American VC's. A few weeks later, DeepSeek happens! Watch the rest of my predictions in my 2025 outlook video . Link in replies #AIInnovation #DeepSeek #NVIDIA #OpenAI #TechDisruption

Dr Ola Brown

83,394 görüntüleme • 1 yıl önce

The most epic 13 minute AI rant I've heard in 2026 PS: My parent's heard this when I was playing it in the car and thought Jason ✨👾SaaStr.Ai✨ Lemkin went OFF like Stephen A Smith does on first take PPS: Full transcript below [17:00] Harry Stebbings: I I just wanted to ask Jason, if the people that we want are fundamentally different, the developers that we used to hire, we don't because AI writes the code for us. The marketers we don't want, the sales people we don't want—who who do we want genuinely? Like what is the attractive profile? Because your Anthropic’s and your OpenAIs are hiring, so so what are the people that we want in the companies of the future? [17:18] Jason Lemkin: Look, I know it sounds trite, but but the answer is simple. It's just the expression each year changes. We want folks that are genuinely AI fluent. It's pretty simple. Now you know, maybe last year we called them prompt engineers, right? That used to be a job. I don't know if you remember that actually used to be the hottest job on planet earth. Now no one needs a prompt engineer because it's pretty easy to prompt all these tools. That job died. Okay. Um and now we need go-to-market engineers. Um I think that job's going to die. We need—everyone needs so many forward deployed engineers. Like you can't hire enough forward deployed engineers. But uh you know um but Palantir just announced in whatever their their big their big event—they've gotten their deployment times down over 90% with forward deployed engineers. So that may become—so the this wave of disruption for the titles and the specificity, it's also exhaustingly accelerating. But it's really simple. You meet anyone for any role—sales, marketing, engineering, product, QA—they're they're either they're either they can't keep all of the ways they use AI to accelerate their job from spewing out of their mouth, or they're staring at you. It's there's nowhere in the middle. Like, and the person that comes in and says—it's it's it sounds Captain Obvious—but like, you know, you just had the whatever from Lovable, the the marketing head that was super popular on the show, right? She's just spewing AI-native insights into Lovable, right? It's not that complicated. You hire her, Elena, or whatever it is. You just hire her. It doesn't matter whether she's still in college or a junior or a senior or a middler, a left or right. And honestly, if you interview people, I would say of all even of the best startups I've invested in, maybe 30% of the management team meets this standard at best. 30%. Maybe less. And of the interviews I do in general, it's single-digit percents. It's just and in in that sense, it's the same as ever. Like you either lower the bar in hiring or you hire someone that's actually great. And someone that's actually great is so far ahead of you in how to apply to to employ the efficiencies of AI in their role, your jaw falls on the table. The difference is we used to need warm bodies. That's what's changing. We used to need warm bodies to answer the call, to do QA, to do code review, to to get the blue pixel to go from the upper left to the lower right. You laugh, but you need you literally needed to brute force this with humans. With AI, every day that goes by, the AI—you do not need brute force human beings on your team. And that's another reason they're shrinking. Why are all these new companies so efficient? They're just not brute forcing things with humans. They're just not. They're choosing not to. And so these team—all the brute forcers out there—everyone talks about how bloated teams got in 2021. I don't agree with that. I think they got as big as they needed to be when growth was high and you needed humans to do everything. All you look at these teams that that doubled—well if growth continued at 60% like the rate in early 2021 for 5 years or can help me do the math and every single thing a software company did required a human. You were understaffed by your 2021 headcount. You'd be sitting here in 2026. You every office in SoMa would be triple packed and you there wouldn't be enough humans to staff your company. It's just the world changed. [20:33] Harry Stebbings: Jason, you live on the bleeding edge. I think me and Rory see that and I think the world sees that when they hear you every week in terms of how you run SaaS. For all of the CEOs and execs who listen to the show, what would you advise them in terms of determining whether someone is AI fluent when they meet them for jobs, for talent? [20:51] Jason Lemkin: Here's I realized I was just asked this. I just did a review with a super fast startup growing just crossing 100 million and I was asked this question. And one of my favorite executives, I thought his answer was pretty dated and because he gave me an answer that was about 6 months old. The answer 6 months old is: "I look for folks in my team, I look for you know at what tools they play with." Okay, that was a great answer in like summer of 2025. Okay, I tried Lovable last week. Okay, the answer in 2026 is: "What commercial AI tool have you brought into your organization this month?" That's the test. Anyone that is on the bleeding edge that you would want to hire—now there are so many great products in the market. Okay, there is no excuse in any role to have not brought one tool a month into your organization. Okay, there—now there's going to be better and better tools and better and better products as the year goes on. What's the one you did? And you will see folks with their deer in the headlights to this question. What what sales tool? What marketing tool? What product tool? What engineering tool? What did you bring in? Why did you pick it? How does it working? Because if you're at remotely at the cutting edge, you're all over this. You're looking for the next agentic tools that will radically improve how you do business. This is—you think everyone thinks SaaS is at the bleeding edge, right? You know, you know, all we do is we're just looking for the tools and trying them. Okay? Okay, we're one year ahead of everybody else because we did the simplest thing in the world. Like we tried the tools early and we trained them. We trained them for a month. Okay, I'll give you—want hear a horrible example from this week? Super hot AI company valued at 6 billion. Okay, I'm not going to name it. Um, this week yesterday told us we had to quadruple what we spent on their product. Okay, their agent told us, right? And why did this happen? Okay. Well, at this $6 billion company, no one had trained the agent on its pricing properly. No one had tested it. They said, "Well, well, we've been in beta." And we said, "Well, when did the beta launch? A year ago." Okay, these are people asleep at at the wheel. You want somebody who the instant this comes up, they exactly know what the issue is. And "Hey, when I was at Lovable Replit, we trained the agent. This is how we did it. I brought in this tool. I brought in this tool that that Rory invested in last week. It solved all these issues." That's what you want to hear. And if they haven't brought in a tool in the last 30 days, at least deeply evaluated it. I don't really care whether they bought it, but gone so far down the funnel they can tell you—pick whatever tool: Fixie, Regie, GC, AIGC—I don't care how you went through it, you looked at it, you can tell me the eight ways it would improve the productivity of your business and three you didn't. Just don't hire that person because they're going to run your company to the ground. This is the job today. The job today is not to screw around on ChatGPT and to be a prompt engineer. The job today is to bring the best AI and agentic products into your organization and leverage all the hard work that the engineers have done building those products. That's your job. You don't have to screw around. You don't have to be a prompt engineer anymore. You have to be an agent deployment expert. A—this is the new job we're making up today. An Agentic Deployment Expert. That's your job from C-level to junior. Agentic Deployment Expert. Don't hire anybody else. You're going to regret it. They're going to stare at the camera. He's good. Stare at the camera. He's honorable. We could probably just I could slip away, get a coffee, and come back. No. And I I sound exasperated, Rory. And I—but the reason I am is I can just see I can see my best companies doing it. And I can see some companies I've invested in not doing it. And I want to cry. I just want to cry when they have no ADs on their team. I just—like you're flushing your years of your life down the toilet by not approaching your how you're building this company this way. [24:33] Rory: Yes. And at the risk of being positive, it's worth pointing out two things he didn't say. Well, something implicit why he said—Jason didn't do the only hire, you know, he didn't commit the um employment law, I think it's a civil penalty of saying only employ people below X who get the new new thing because he implicitly said anyone can do it provided you're willing to learn. And I think that's the big aha that's one of the positive statements to make here right? Look and I think it applies—I'm always wary of being "Hey, coming across, hey this this is the things that you all have to do." I think it applies to everyone including investors right? I mean I will say I have found that unless you're willing to invest the time learning these tools you actually shouldn't be investing in them. One of my partners Andy had this expression: "You know, if you decide you want to stop learning new things you probably should retire within 6 to 12 months and never write another check again." Maybe that's down to 3 to 6 months at this stage, right? And I think, you know, it's— [25:27] Harry Stebbings: Yeah, I actually I actually had a meeting with mine and Jason's biggest investor the other day and I—pretend he's not here—I said I think he's the most equipped investor for this generation of investing because I don't think anyone quite sits at the bleeding edge like he does on the investor side. [25:42] Harry Stebbings: Why in terms of using the equip stuff? Yeah. Yeah. In terms of using the stuff, understanding understanding bottlenecks, constraints. For sure. [25:51] Jason Lemkin: But can I just add one point? We can just cuz it's so important if it helps people. Okay, we are—and thank you Harry. We're going through these phases. Okay, and when AI started to blow up for real for us, uh call it early 2024, right? Maybe late '23, I wasn't equipped. It was too technical. I wasn't going to go in and figure out—I wasn't smart enough to figure out how to deal with a massively hallucinating LLM API and turn that and turn that into something magical. Kudos to investors and others that that got it in early '23, '22. I mean I remember I—I guess it was maybe SaaStr Annual '23. I was with David Sacks and I did a Q&A and I said, "How you thinking about AI at Craft?" He's like, "Well we're all in. We want 80% of '23 of investments to be AI." I'm like, "Great but like show me the show me the great ones in market." He's like, "They're all prototypes. We're all they're all they're all proof of concepts but we're all in anyway." That's where you kind of had to be in '23 if you weren't investing at like the LLM level. Okay, I wasn't smart enough. Then we went through this weird-ass prompt engineer era where like you you could torture these products to do something good, right? But you had to torture them. You had to like craft these crazy things that made no sense. Now we are in the era where mere ordinarily smart generalists can make these tools do magical things. And literally I go to these meetings and people be like, "I don't know how to like this is so scary. I don't know how to do this." And we show them our backends. Do you know how to do a workflow generator? Do you know how to do a a decision tree? Like we've been building these since software in the '90s. Okay, if you—I can show you all of our agents. The how they work is novel. They do have to be trained. You can't be lazy and have these agents work. But honestly, the the UI, the UX, the way we interact with them, it's just software. And so my point is: Pick yourself off the ground. This is your time now. If you felt lost in AI era, if you felt like you're behind, you don't understand what all these people are saying on X and Twitter and their Claude and and their and talking about all the 4.6 point Nano point and it's over—like you just it's not your world. This is your time. This is your time for the generalist that knows how to use software tools really really well. And I—this is my last point but it's so important. If ever in your recent life—and this is why you could be all you need to be is young at heart to Rory's point—if in the last three to five years you have successfully deployed a piece of enterprise software of any sort you yourself, not some agency you hired, but if you have deployed it, you can deploy any agentic tool. Any. And you can become the hero in your company and you can become the hero in your functional area. But I watch folks—I'm literally helping a company now that they're adding hundreds of sales folks this year with a new pre-IPO COO—he's not hasn't brought in a single tool, totally scared of it. Okay, it's not that hard. Did you use SalesLoft? Did you use Outreach? Did you use HubSpot? Do you know these tools? If you can deploy these tools, you can deploy a world-changing AI agent. And so this is the time for people like the folks that that were shut out of the AI revolution right now. The generalist folks that are not that know how to deploy software that don't even know how to build software. Like vibe coding for me was folks who knew how to build software, but you didn't have to be an engineer. Now, you just need to know how to deploy software to win with AI agents. That's all you need to know. So many people have these skills and they're petrified of AI. "How did you do that? How did you deploy an AI BDR?" Well, we bought a piece of software, we figured out how it worked for a day, we set it up in an afternoon, and then and then we did spend 30 months training it, which you didn't do with this old software because in the old days, we just had to manually upload all the data, right? And there was no training. The the only non-intuitive part is training these things. And it's it's it's just work. So that's why when I see folks on the management team not doing this, there's no excuse. You do not need to be technical to win with AI agents in Q2 of '26. You do not need to be even 1% technical. Not at all. So it's your time. Or you're going to get laid off. Or you're going to get laid off because you're not going to matter.
13:04

The most epic 13 minute AI rant I've heard in 2026 PS: My parent's heard this when I was playing it in the car and thought Jason ✨👾SaaStr.Ai✨ Lemkin went OFF like Stephen A Smith does on first take PPS: Full transcript below [17:00] Harry Stebbings: I I just wanted to ask Jason, if the people that we want are fundamentally different, the developers that we used to hire, we don't because AI writes the code for us. The marketers we don't want, the sales people we don't want—who who do we want genuinely? Like what is the attractive profile? Because your Anthropic’s and your OpenAIs are hiring, so so what are the people that we want in the companies of the future? [17:18] Jason Lemkin: Look, I know it sounds trite, but but the answer is simple. It's just the expression each year changes. We want folks that are genuinely AI fluent. It's pretty simple. Now you know, maybe last year we called them prompt engineers, right? That used to be a job. I don't know if you remember that actually used to be the hottest job on planet earth. Now no one needs a prompt engineer because it's pretty easy to prompt all these tools. That job died. Okay. Um and now we need go-to-market engineers. Um I think that job's going to die. We need—everyone needs so many forward deployed engineers. Like you can't hire enough forward deployed engineers. But uh you know um but Palantir just announced in whatever their their big their big event—they've gotten their deployment times down over 90% with forward deployed engineers. So that may become—so the this wave of disruption for the titles and the specificity, it's also exhaustingly accelerating. But it's really simple. You meet anyone for any role—sales, marketing, engineering, product, QA—they're they're either they're either they can't keep all of the ways they use AI to accelerate their job from spewing out of their mouth, or they're staring at you. It's there's nowhere in the middle. Like, and the person that comes in and says—it's it's it sounds Captain Obvious—but like, you know, you just had the whatever from Lovable, the the marketing head that was super popular on the show, right? She's just spewing AI-native insights into Lovable, right? It's not that complicated. You hire her, Elena, or whatever it is. You just hire her. It doesn't matter whether she's still in college or a junior or a senior or a middler, a left or right. And honestly, if you interview people, I would say of all even of the best startups I've invested in, maybe 30% of the management team meets this standard at best. 30%. Maybe less. And of the interviews I do in general, it's single-digit percents. It's just and in in that sense, it's the same as ever. Like you either lower the bar in hiring or you hire someone that's actually great. And someone that's actually great is so far ahead of you in how to apply to to employ the efficiencies of AI in their role, your jaw falls on the table. The difference is we used to need warm bodies. That's what's changing. We used to need warm bodies to answer the call, to do QA, to do code review, to to get the blue pixel to go from the upper left to the lower right. You laugh, but you need you literally needed to brute force this with humans. With AI, every day that goes by, the AI—you do not need brute force human beings on your team. And that's another reason they're shrinking. Why are all these new companies so efficient? They're just not brute forcing things with humans. They're just not. They're choosing not to. And so these team—all the brute forcers out there—everyone talks about how bloated teams got in 2021. I don't agree with that. I think they got as big as they needed to be when growth was high and you needed humans to do everything. All you look at these teams that that doubled—well if growth continued at 60% like the rate in early 2021 for 5 years or can help me do the math and every single thing a software company did required a human. You were understaffed by your 2021 headcount. You'd be sitting here in 2026. You every office in SoMa would be triple packed and you there wouldn't be enough humans to staff your company. It's just the world changed. [20:33] Harry Stebbings: Jason, you live on the bleeding edge. I think me and Rory see that and I think the world sees that when they hear you every week in terms of how you run SaaS. For all of the CEOs and execs who listen to the show, what would you advise them in terms of determining whether someone is AI fluent when they meet them for jobs, for talent? [20:51] Jason Lemkin: Here's I realized I was just asked this. I just did a review with a super fast startup growing just crossing 100 million and I was asked this question. And one of my favorite executives, I thought his answer was pretty dated and because he gave me an answer that was about 6 months old. The answer 6 months old is: "I look for folks in my team, I look for you know at what tools they play with." Okay, that was a great answer in like summer of 2025. Okay, I tried Lovable last week. Okay, the answer in 2026 is: "What commercial AI tool have you brought into your organization this month?" That's the test. Anyone that is on the bleeding edge that you would want to hire—now there are so many great products in the market. Okay, there is no excuse in any role to have not brought one tool a month into your organization. Okay, there—now there's going to be better and better tools and better and better products as the year goes on. What's the one you did? And you will see folks with their deer in the headlights to this question. What what sales tool? What marketing tool? What product tool? What engineering tool? What did you bring in? Why did you pick it? How does it working? Because if you're at remotely at the cutting edge, you're all over this. You're looking for the next agentic tools that will radically improve how you do business. This is—you think everyone thinks SaaS is at the bleeding edge, right? You know, you know, all we do is we're just looking for the tools and trying them. Okay? Okay, we're one year ahead of everybody else because we did the simplest thing in the world. Like we tried the tools early and we trained them. We trained them for a month. Okay, I'll give you—want hear a horrible example from this week? Super hot AI company valued at 6 billion. Okay, I'm not going to name it. Um, this week yesterday told us we had to quadruple what we spent on their product. Okay, their agent told us, right? And why did this happen? Okay. Well, at this $6 billion company, no one had trained the agent on its pricing properly. No one had tested it. They said, "Well, well, we've been in beta." And we said, "Well, when did the beta launch? A year ago." Okay, these are people asleep at at the wheel. You want somebody who the instant this comes up, they exactly know what the issue is. And "Hey, when I was at Lovable Replit, we trained the agent. This is how we did it. I brought in this tool. I brought in this tool that that Rory invested in last week. It solved all these issues." That's what you want to hear. And if they haven't brought in a tool in the last 30 days, at least deeply evaluated it. I don't really care whether they bought it, but gone so far down the funnel they can tell you—pick whatever tool: Fixie, Regie, GC, AIGC—I don't care how you went through it, you looked at it, you can tell me the eight ways it would improve the productivity of your business and three you didn't. Just don't hire that person because they're going to run your company to the ground. This is the job today. The job today is not to screw around on ChatGPT and to be a prompt engineer. The job today is to bring the best AI and agentic products into your organization and leverage all the hard work that the engineers have done building those products. That's your job. You don't have to screw around. You don't have to be a prompt engineer anymore. You have to be an agent deployment expert. A—this is the new job we're making up today. An Agentic Deployment Expert. That's your job from C-level to junior. Agentic Deployment Expert. Don't hire anybody else. You're going to regret it. They're going to stare at the camera. He's good. Stare at the camera. He's honorable. We could probably just I could slip away, get a coffee, and come back. No. And I I sound exasperated, Rory. And I—but the reason I am is I can just see I can see my best companies doing it. And I can see some companies I've invested in not doing it. And I want to cry. I just want to cry when they have no ADs on their team. I just—like you're flushing your years of your life down the toilet by not approaching your how you're building this company this way. [24:33] Rory: Yes. And at the risk of being positive, it's worth pointing out two things he didn't say. Well, something implicit why he said—Jason didn't do the only hire, you know, he didn't commit the um employment law, I think it's a civil penalty of saying only employ people below X who get the new new thing because he implicitly said anyone can do it provided you're willing to learn. And I think that's the big aha that's one of the positive statements to make here right? Look and I think it applies—I'm always wary of being "Hey, coming across, hey this this is the things that you all have to do." I think it applies to everyone including investors right? I mean I will say I have found that unless you're willing to invest the time learning these tools you actually shouldn't be investing in them. One of my partners Andy had this expression: "You know, if you decide you want to stop learning new things you probably should retire within 6 to 12 months and never write another check again." Maybe that's down to 3 to 6 months at this stage, right? And I think, you know, it's— [25:27] Harry Stebbings: Yeah, I actually I actually had a meeting with mine and Jason's biggest investor the other day and I—pretend he's not here—I said I think he's the most equipped investor for this generation of investing because I don't think anyone quite sits at the bleeding edge like he does on the investor side. [25:42] Harry Stebbings: Why in terms of using the equip stuff? Yeah. Yeah. In terms of using the stuff, understanding understanding bottlenecks, constraints. For sure. [25:51] Jason Lemkin: But can I just add one point? We can just cuz it's so important if it helps people. Okay, we are—and thank you Harry. We're going through these phases. Okay, and when AI started to blow up for real for us, uh call it early 2024, right? Maybe late '23, I wasn't equipped. It was too technical. I wasn't going to go in and figure out—I wasn't smart enough to figure out how to deal with a massively hallucinating LLM API and turn that and turn that into something magical. Kudos to investors and others that that got it in early '23, '22. I mean I remember I—I guess it was maybe SaaStr Annual '23. I was with David Sacks and I did a Q&A and I said, "How you thinking about AI at Craft?" He's like, "Well we're all in. We want 80% of '23 of investments to be AI." I'm like, "Great but like show me the show me the great ones in market." He's like, "They're all prototypes. We're all they're all they're all proof of concepts but we're all in anyway." That's where you kind of had to be in '23 if you weren't investing at like the LLM level. Okay, I wasn't smart enough. Then we went through this weird-ass prompt engineer era where like you you could torture these products to do something good, right? But you had to torture them. You had to like craft these crazy things that made no sense. Now we are in the era where mere ordinarily smart generalists can make these tools do magical things. And literally I go to these meetings and people be like, "I don't know how to like this is so scary. I don't know how to do this." And we show them our backends. Do you know how to do a workflow generator? Do you know how to do a a decision tree? Like we've been building these since software in the '90s. Okay, if you—I can show you all of our agents. The how they work is novel. They do have to be trained. You can't be lazy and have these agents work. But honestly, the the UI, the UX, the way we interact with them, it's just software. And so my point is: Pick yourself off the ground. This is your time now. If you felt lost in AI era, if you felt like you're behind, you don't understand what all these people are saying on X and Twitter and their Claude and and their and talking about all the 4.6 point Nano point and it's over—like you just it's not your world. This is your time. This is your time for the generalist that knows how to use software tools really really well. And I—this is my last point but it's so important. If ever in your recent life—and this is why you could be all you need to be is young at heart to Rory's point—if in the last three to five years you have successfully deployed a piece of enterprise software of any sort you yourself, not some agency you hired, but if you have deployed it, you can deploy any agentic tool. Any. And you can become the hero in your company and you can become the hero in your functional area. But I watch folks—I'm literally helping a company now that they're adding hundreds of sales folks this year with a new pre-IPO COO—he's not hasn't brought in a single tool, totally scared of it. Okay, it's not that hard. Did you use SalesLoft? Did you use Outreach? Did you use HubSpot? Do you know these tools? If you can deploy these tools, you can deploy a world-changing AI agent. And so this is the time for people like the folks that that were shut out of the AI revolution right now. The generalist folks that are not that know how to deploy software that don't even know how to build software. Like vibe coding for me was folks who knew how to build software, but you didn't have to be an engineer. Now, you just need to know how to deploy software to win with AI agents. That's all you need to know. So many people have these skills and they're petrified of AI. "How did you do that? How did you deploy an AI BDR?" Well, we bought a piece of software, we figured out how it worked for a day, we set it up in an afternoon, and then and then we did spend 30 months training it, which you didn't do with this old software because in the old days, we just had to manually upload all the data, right? And there was no training. The the only non-intuitive part is training these things. And it's it's it's just work. So that's why when I see folks on the management team not doing this, there's no excuse. You do not need to be technical to win with AI agents in Q2 of '26. You do not need to be even 1% technical. Not at all. So it's your time. Or you're going to get laid off. Or you're going to get laid off because you're not going to matter.

Arjun Mahadevan (Mr. LLC 🇺🇸)

37,533 görüntüleme • 3 ay önce

.Elon Musk (worth $250B) answers why he’s still working: I think it's a good question you asked, because it goes to, like, at a foundational level, what is my philosophy, and why does it lead to this conclusion? So the reason is that when I was a teenager, I had, like, an existential crisis to try to figure out what's the meaning of life. There doesn't seem to be any meaning. For me, at least the religious texts, and I read all of them that I could get my hands on did not seem convincing. Then I started reading the philosophers. Be careful of reading German philosophers as a teenager. It's definitely not going to help with your depression. So reading Schopenhauer, Nietzsche, as an adult, it's much more manageable. But as a kid, you're like, “Whoa.” So then I was like, “Man, I'm just struggling to find meaning in life here.” And then I read Hitchhiker's Guide to the Galaxy. And basically what Douglas Adams was saying is that we don't really know what the right questions are to ask. The question is not, “What's the meaning of life?” In The Hitchiker's Guide to the Galaxy, Earth it turns out is a big computer, and its goal is to answer the question, “What's the meaning of life?” And Earth comes up with the answer “42”. This is where the 42 number comes from. And 420 is just ten times 42. In that book, which is really sort of a book about, it's an existential philosophy book disguised as humor. They come to the conclusion that, no, the real problem is trying to formulate the question. And to really have the right question, you need a much bigger computer than Earth. And so maybe one way, I think, of characterizing this would be to say, “The universe is the answer. What is the question? Or what are the questions?” The more we can expand the scope and scale of consciousness, the better we can understand what questions to ask about the answer that is the universe. The more we can expand consciousness, become a multi-planet species, ultimately a multistellar species… we have a chance of figuring out what the hell is going on. And so this is why I think we should have more humans and both biological and digital consciousness. And why we should become a multi-planet species and a multistellar species is so that we can understand the nature of the universe. And then in order for that to occur, then we have to make sure that things are good on Earth. We don't want Earth to disappear, so sustainable energy is important.
3:11

.Elon Musk (worth $250B) answers why he’s still working: I think it's a good question you asked, because it goes to, like, at a foundational level, what is my philosophy, and why does it lead to this conclusion? So the reason is that when I was a teenager, I had, like, an existential crisis to try to figure out what's the meaning of life. There doesn't seem to be any meaning. For me, at least the religious texts, and I read all of them that I could get my hands on did not seem convincing. Then I started reading the philosophers. Be careful of reading German philosophers as a teenager. It's definitely not going to help with your depression. So reading Schopenhauer, Nietzsche, as an adult, it's much more manageable. But as a kid, you're like, “Whoa.” So then I was like, “Man, I'm just struggling to find meaning in life here.” And then I read Hitchhiker's Guide to the Galaxy. And basically what Douglas Adams was saying is that we don't really know what the right questions are to ask. The question is not, “What's the meaning of life?” In The Hitchiker's Guide to the Galaxy, Earth it turns out is a big computer, and its goal is to answer the question, “What's the meaning of life?” And Earth comes up with the answer “42”. This is where the 42 number comes from. And 420 is just ten times 42. In that book, which is really sort of a book about, it's an existential philosophy book disguised as humor. They come to the conclusion that, no, the real problem is trying to formulate the question. And to really have the right question, you need a much bigger computer than Earth. And so maybe one way, I think, of characterizing this would be to say, “The universe is the answer. What is the question? Or what are the questions?” The more we can expand the scope and scale of consciousness, the better we can understand what questions to ask about the answer that is the universe. The more we can expand consciousness, become a multi-planet species, ultimately a multistellar species… we have a chance of figuring out what the hell is going on. And so this is why I think we should have more humans and both biological and digital consciousness. And why we should become a multi-planet species and a multistellar species is so that we can understand the nature of the universe. And then in order for that to occur, then we have to make sure that things are good on Earth. We don't want Earth to disappear, so sustainable energy is important.

Arjun Khemani

15,597,236 görüntüleme • 1 yıl önce

.Scott Wu to Joe Lonsdale on why Cognition uses AI in job interviews: "One or two years ago, people had this mentality of 'How do we make sure people aren't using AI while we're interviewing them?' And I think that has totally flipped. Honestly, I think that was wrong... If you're asking the question of like, how do we evaluate people on exactly the thing that AI can already do, that seems kind of the wrong. Our interview process has always been... you can use as much AI as you want to use. We're going to give you a few hours. Just build your whole own product surface. A lot of these are projects that, frankly, is like, if you were trying to do this by hand, you would not be able to get done in a few hours. So you kind of have to use AI for this. But in reality, what we actually want to test is, in addition to how familiar you are with these tools, what we actually want to test is, what do you think is the right thing to build? Or how do you make these product decisions? How do you make these trade-offs? How do you decide or collect information about what you should be doing?"
0:58

.Scott Wu to Joe Lonsdale on why Cognition uses AI in job interviews: "One or two years ago, people had this mentality of 'How do we make sure people aren't using AI while we're interviewing them?' And I think that has totally flipped. Honestly, I think that was wrong... If you're asking the question of like, how do we evaluate people on exactly the thing that AI can already do, that seems kind of the wrong. Our interview process has always been... you can use as much AI as you want to use. We're going to give you a few hours. Just build your whole own product surface. A lot of these are projects that, frankly, is like, if you were trying to do this by hand, you would not be able to get done in a few hours. So you kind of have to use AI for this. But in reality, what we actually want to test is, in addition to how familiar you are with these tools, what we actually want to test is, what do you think is the right thing to build? Or how do you make these product decisions? How do you make these trade-offs? How do you decide or collect information about what you should be doing?"

American Optimist

13,182 görüntüleme • 3 ay önce

“I would give the football players a little choice of words, and they didn't like it. And so we would handle business in the locker room. I would fight these guys either in the locker room or at practice, and I didn't lose. I figured if this football thing doesn't work out, or if I get sick and tired of it — which I did — maybe I should beat people up for some money. This is how it came about.” The Incredible Hok explains his decision to make the move from the NFL to MMA.
1:30

“I would give the football players a little choice of words, and they didn't like it. And so we would handle business in the locker room. I would fight these guys either in the locker room or at practice, and I didn't lose. I figured if this football thing doesn't work out, or if I get sick and tired of it — which I did — maybe I should beat people up for some money. This is how it came about.” The Incredible Hok explains his decision to make the move from the NFL to MMA.

Ariel Helwani

151,663 görüntüleme • 8 ay önce

Angelina Jolie Has Finally Woken Up To The Fact The United Nations & Governments Are Run By Heartless Criminals There’s No Accountability For Crimes “If There’s A Business Interest Involved” “That is the biggest that is the most disheartening thing of I think we we or I thought at least even 20 years ago when I started to work internationally that there was this I in my head, some weird idea of good guys. You know? Some idea of those whether it be certain countries or certain people's maybe it was this holdover from World War 2 and this thought that this was, like so that the lines were clear and that there was going to be these human rights goals laid out and that there would be things stood up for, and that if these things weren't done, there would be pushback, and these were the and I really thought that's what it was. I even thought that's what the United Nations was… And I thought, okay. There's a there's some lines in the sand. There's some understanding. We're gonna grow and fight for improvements in these areas. And and to watch to watch and understand more and more how it's just simply that's not what it is. That's not the world. The world is not these are human rights. It is these are human rights sometimes for these people, maybe sometimes for these people, never for these people. Yeah. It's food aid, 6% for these people, 50% for these people, it's justice for these people, but not these people. Accountability for this crime, but not that crime if there's business interest. And this is truly the ugly state of of so much of the world that we are just becoming more and more aware of for just about every I mean, I don't know any countries that are are clean of it and, um, and willing to hold a line really consistently hand on behalf of the of human rights and laws”
1:52

Angelina Jolie Has Finally Woken Up To The Fact The United Nations & Governments Are Run By Heartless Criminals There’s No Accountability For Crimes “If There’s A Business Interest Involved” “That is the biggest that is the most disheartening thing of I think we we or I thought at least even 20 years ago when I started to work internationally that there was this I in my head, some weird idea of good guys. You know? Some idea of those whether it be certain countries or certain people's maybe it was this holdover from World War 2 and this thought that this was, like so that the lines were clear and that there was going to be these human rights goals laid out and that there would be things stood up for, and that if these things weren't done, there would be pushback, and these were the and I really thought that's what it was. I even thought that's what the United Nations was… And I thought, okay. There's a there's some lines in the sand. There's some understanding. We're gonna grow and fight for improvements in these areas. And and to watch to watch and understand more and more how it's just simply that's not what it is. That's not the world. The world is not these are human rights. It is these are human rights sometimes for these people, maybe sometimes for these people, never for these people. Yeah. It's food aid, 6% for these people, 50% for these people, it's justice for these people, but not these people. Accountability for this crime, but not that crime if there's business interest. And this is truly the ugly state of of so much of the world that we are just becoming more and more aware of for just about every I mean, I don't know any countries that are are clean of it and, um, and willing to hold a line really consistently hand on behalf of the of human rights and laws”

Wall Street Apes

658,682 görüntüleme • 2 yıl önce

Elon Musk: I always had an intense desire to understand things. “I was always a crazy kid. I was just very curious about the world and how do we come to be here? What's the meaning of life and all that. And I always had a really intense desire to understand things and learn. I had sort of an existential crisis, I guess, when I was 11 or 12 or something, just trying to figure out what it's all about and ultimately came to the conclusion that we don't really know the answer but if we increase the scope and scale of civilization, then we have a much better chance of understanding the meaning of life and why we're here or even what are the right questions to ask. So, therefore, we should strive to expand the scope and scale of consciousness to better understand the questions to ask about the answer that is the universe.” XPRIZE Conversation with Peter Diamandis, April 22, 2021
1:17

Elon Musk: I always had an intense desire to understand things. “I was always a crazy kid. I was just very curious about the world and how do we come to be here? What's the meaning of life and all that. And I always had a really intense desire to understand things and learn. I had sort of an existential crisis, I guess, when I was 11 or 12 or something, just trying to figure out what it's all about and ultimately came to the conclusion that we don't really know the answer but if we increase the scope and scale of civilization, then we have a much better chance of understanding the meaning of life and why we're here or even what are the right questions to ask. So, therefore, we should strive to expand the scope and scale of consciousness to better understand the questions to ask about the answer that is the universe.” XPRIZE Conversation with Peter Diamandis, April 22, 2021

ELON CLIPS

51,534 görüntüleme • 1 yıl önce

President Trump on negotiations with Iran: “I mean, the problem with the issue of the Hormuz Straits is this: We've decimated them as a military. No air force, no navy, very few rockets left. We blew up so many. Hard to manufacture them. Same thing with drones. The leadership is gone. The problem with the Straits is this: Let's say we do a great job. We say we got 99%. 1% is unacceptable, because 1% is a missile going into the hull of a ship that cost a billion dollars, right? So 1% is not... If we do a 99% decimation, that's no good. So it's really, you know... I have a feeling it's going to clean up pretty quickly. I could just say this. They want to make -- they want to make -- and I probably hurt our little negotiation. It gives them a little impetus to say, ‘Well, I wish you didn't say that.’ But they said yesterday that we weren't negotiating with them, and now they admit that we were negotiating with them. So they want to make a deal. The reason they want to make a deal is they have been just beat to shit.”
1:09

President Trump on negotiations with Iran: “I mean, the problem with the issue of the Hormuz Straits is this: We've decimated them as a military. No air force, no navy, very few rockets left. We blew up so many. Hard to manufacture them. Same thing with drones. The leadership is gone. The problem with the Straits is this: Let's say we do a great job. We say we got 99%. 1% is unacceptable, because 1% is a missile going into the hull of a ship that cost a billion dollars, right? So 1% is not... If we do a 99% decimation, that's no good. So it's really, you know... I have a feeling it's going to clean up pretty quickly. I could just say this. They want to make -- they want to make -- and I probably hurt our little negotiation. It gives them a little impetus to say, ‘Well, I wish you didn't say that.’ But they said yesterday that we weren't negotiating with them, and now they admit that we were negotiating with them. So they want to make a deal. The reason they want to make a deal is they have been just beat to shit.”

OSINTdefender

938,666 görüntüleme • 3 ay önce

Chamath Palihapitiya highlights President Trump's remarkable Middle East peace agreement via the Abraham Accords, underscores the growing need for a U.S. border wall, and points out the corporate media's lies about Jared Kushner. Chamath Palihapitiya: "As a Democrat, who has been left homeless, who is now definitely in the center, but probably leaning increasingly right, I'm left yet again with an appreciation, despite the messenger of the message, of the Trump administration, because what those guys did, was pretty incredible. In hindsight, these Abraham Accords, the accords with Israel and the GCC, the almost accord between Israel and Saudi, to really be able to find a long-lasting peace. He's just a real example for the world. And those guys did a lot of really great work." @jason: "It's a miracle when you look at it. Listen, I'm no fan of Trump, but if you objectively look at what they did, it was great work." Chamath then asks if 'Trump Derangement Syndrome' is causing more damage than President Trump, with the left and the media's bias against the messenger overshadowing the importance of the message? Chamath Palihapitiya: "I think the answer is yes... So much of the work that happened in that administration turned out to have been right... The work on the border wall, we didn't like the messenger. So, we killed the message. Turned out it was right. Issuing long-term debt to refinance when rates were at zero. We didn't like the messenger, so we killed the message. A structural peace deal in the Middle East. We didn't like the messenger, so we killed the message... When are we going to actually take the time to look past who was saying things and actually listen to them word for word? ...If you listen to this Lex Fridman podcast, the most important thing that is resoundingly obvious about Jared Kushner is that he is incredibly thoughtful and incredibly competent. And why did we have to spend years being fed all of these stupid lies? Because one can judge for oneself. But Jared Kushner is thoughtful. He's smart. And I thought to myself, I was fed all these lies for years about how this guy was moping around in the shadows and this and that, and it was all not true." Raise your hand if you prefer “Mean Tweets” to war breaking out around the world.
4:08

Chamath Palihapitiya highlights President Trump's remarkable Middle East peace agreement via the Abraham Accords, underscores the growing need for a U.S. border wall, and points out the corporate media's lies about Jared Kushner. Chamath Palihapitiya: "As a Democrat, who has been left homeless, who is now definitely in the center, but probably leaning increasingly right, I'm left yet again with an appreciation, despite the messenger of the message, of the Trump administration, because what those guys did, was pretty incredible. In hindsight, these Abraham Accords, the accords with Israel and the GCC, the almost accord between Israel and Saudi, to really be able to find a long-lasting peace. He's just a real example for the world. And those guys did a lot of really great work." @jason: "It's a miracle when you look at it. Listen, I'm no fan of Trump, but if you objectively look at what they did, it was great work." Chamath then asks if 'Trump Derangement Syndrome' is causing more damage than President Trump, with the left and the media's bias against the messenger overshadowing the importance of the message? Chamath Palihapitiya: "I think the answer is yes... So much of the work that happened in that administration turned out to have been right... The work on the border wall, we didn't like the messenger. So, we killed the message. Turned out it was right. Issuing long-term debt to refinance when rates were at zero. We didn't like the messenger, so we killed the message. A structural peace deal in the Middle East. We didn't like the messenger, so we killed the message... When are we going to actually take the time to look past who was saying things and actually listen to them word for word? ...If you listen to this Lex Fridman podcast, the most important thing that is resoundingly obvious about Jared Kushner is that he is incredibly thoughtful and incredibly competent. And why did we have to spend years being fed all of these stupid lies? Because one can judge for oneself. But Jared Kushner is thoughtful. He's smart. And I thought to myself, I was fed all these lies for years about how this guy was moping around in the shadows and this and that, and it was all not true." Raise your hand if you prefer “Mean Tweets” to war breaking out around the world.

KanekoaTheGreat

1,770,574 görüntüleme • 2 yıl önce

"At school or university, the thing is to be brilliant and to get the answer right first time. And there are brilliant people who can do that, but for the rest of us, we're not brilliant. And to get there, we have to strive and we have to go through failure. And we realize that you don't get it right first time, you don't get it right second time. In my case, and I counted it, it's 5,127 times. One of the things I always want to say is that sounds like a struggle. It was a struggle, but actually it was a hugely enjoyable struggle. The debt was mounting and I had three children, a wife and a home, and then a mortgage to pay, like everybody else. But I had a real point in life, I had a real aim and I had to get there. And the failures were interesting because I'd learned from every single one of them."
0:51

"At school or university, the thing is to be brilliant and to get the answer right first time. And there are brilliant people who can do that, but for the rest of us, we're not brilliant. And to get there, we have to strive and we have to go through failure. And we realize that you don't get it right first time, you don't get it right second time. In my case, and I counted it, it's 5,127 times. One of the things I always want to say is that sounds like a struggle. It was a struggle, but actually it was a hugely enjoyable struggle. The debt was mounting and I had three children, a wife and a home, and then a mortgage to pay, like everybody else. But I had a real point in life, I had a real aim and I had to get there. And the failures were interesting because I'd learned from every single one of them."

David Senra

137,486 görüntüleme • 7 ay önce

American Surgeon shows the actual letter from UnitedHealthcare DENYING a patient in emergency condition from receiving care “This is a woman who was in the emergency room with pulmonary embolisms” “I think we all knew this would happen. I had another patient come in and share with me that UnitedHealthcare denied her inpatient's day. So this is a patient who had shortness of breath and some chest pain, and she just knew that something wasn't right in her body. She had a family history of blood clots and she'd had a deep flap surgery a couple of weeks ago. She went to the hospital and they saw her and they found that she had a life threatening condition known as pulmonary embolisms. So she was admitted to the hospital and taken care of really well by the doctors there. And they ordered all the right things. After a couple of days, she was discharged. She got a letter from UnitedHealthcare explaining that they didn't agree with the level of her care and that they would not cover it. So I'm gonna share some of the language of that letter with you, and I want you to know that my patient that we talked about previously who had her surgery denied had almost exactly the same letter shared. So there's some troubling things in this letter. I think this term is really interesting. United is saying they reviewed the request for inpatient admission. So let's all just pause and consider that. This is a woman who was in the emergency room with pulmonary embolisms, and the doctor wasn't really requesting anything. They were saying this patient needs to be in the hospital. But an insurance company sees this as a request, and that's part of this prior auth environment that we're living in. So I think it's important as patients and as physicians to just acknowledge that this is our reality now. Someone can think that there's a good medical decision for you and can write orders and wanna do the right thing for you, but your insurance company is seeing that as a request and deciding whether or not they wanna do it. One of the criteria that this insurance company used to decide whether or not to accept or deny this request was whether it's medically necessary. And it's so interesting that we're letting insurance companies and the doctors who work for insurance companies determine what's medically necessary and not just the doctor in front of the patient in the emergency room. So this is a really bold statement from UnitedHealthcare for my patient. They say you did not have to be admitted as an inpatient to the hospital for this care. I think we all need to just reflect on that. An insurance company is telling a patient and her doctor that they disagree with the plan of care to keep that patient safe. I know that this is boiling down to whether it's an inpatient admission or an observation admission, and that's really about money. But what I wanna point out to you is they're making medical decisions. This insurance company is actually weighing in and disagreeing with a doctor who made a medical decision to admit this patient for her safety. So this specific sentence, when a doctor or facility treats a patient above the recommended level of care, we cannot cover it. What the heck? That's what we do. We go above and beyond as physicians. It's clear that insurance companies don't, and they're actually saying it here.”
2:35

American Surgeon shows the actual letter from UnitedHealthcare DENYING a patient in emergency condition from receiving care “This is a woman who was in the emergency room with pulmonary embolisms” “I think we all knew this would happen. I had another patient come in and share with me that UnitedHealthcare denied her inpatient's day. So this is a patient who had shortness of breath and some chest pain, and she just knew that something wasn't right in her body. She had a family history of blood clots and she'd had a deep flap surgery a couple of weeks ago. She went to the hospital and they saw her and they found that she had a life threatening condition known as pulmonary embolisms. So she was admitted to the hospital and taken care of really well by the doctors there. And they ordered all the right things. After a couple of days, she was discharged. She got a letter from UnitedHealthcare explaining that they didn't agree with the level of her care and that they would not cover it. So I'm gonna share some of the language of that letter with you, and I want you to know that my patient that we talked about previously who had her surgery denied had almost exactly the same letter shared. So there's some troubling things in this letter. I think this term is really interesting. United is saying they reviewed the request for inpatient admission. So let's all just pause and consider that. This is a woman who was in the emergency room with pulmonary embolisms, and the doctor wasn't really requesting anything. They were saying this patient needs to be in the hospital. But an insurance company sees this as a request, and that's part of this prior auth environment that we're living in. So I think it's important as patients and as physicians to just acknowledge that this is our reality now. Someone can think that there's a good medical decision for you and can write orders and wanna do the right thing for you, but your insurance company is seeing that as a request and deciding whether or not they wanna do it. One of the criteria that this insurance company used to decide whether or not to accept or deny this request was whether it's medically necessary. And it's so interesting that we're letting insurance companies and the doctors who work for insurance companies determine what's medically necessary and not just the doctor in front of the patient in the emergency room. So this is a really bold statement from UnitedHealthcare for my patient. They say you did not have to be admitted as an inpatient to the hospital for this care. I think we all need to just reflect on that. An insurance company is telling a patient and her doctor that they disagree with the plan of care to keep that patient safe. I know that this is boiling down to whether it's an inpatient admission or an observation admission, and that's really about money. But what I wanna point out to you is they're making medical decisions. This insurance company is actually weighing in and disagreeing with a doctor who made a medical decision to admit this patient for her safety. So this specific sentence, when a doctor or facility treats a patient above the recommended level of care, we cannot cover it. What the heck? That's what we do. We go above and beyond as physicians. It's clear that insurance companies don't, and they're actually saying it here.”

Wall Street Apes

115,691 görüntüleme • 1 yıl önce

PM Frederiksen: we have to recognize, we have to understand, we have to learn that Russia will not change and they are not interested in peace, unfortunately. Can you imagine? I mean, it's like minus 25 degrees and then you attack the energy system. I mean, it's so crazy that only Russians would do such a thing. But this is how Russia is and it will not change. And I think our problem in Ukraine is still that there are still red lines when it comes to the weapons they can use to win this war. And you cannot win a war with the one hand tied on your back. We need to give them weapons so they can strike into Russia. We have had this discussion for several years. We are still discussing it. I mean, for the last three years on this conference, I have said, why are we not providing them the air defense that they need? And everybody is doing like this. They still lack air defense. You cannot protect a country without air defense. We know exactly what we need to deliver, including, of course, membership of NATO, because if they were a NATO member now, we would be in a completely different situation now. So, we know what to do. But first of all, we have to recognize, we have to understand, we have to learn that Russia will not change and they are not interested in peace, unfortunately.
1:36

PM Frederiksen: we have to recognize, we have to understand, we have to learn that Russia will not change and they are not interested in peace, unfortunately. Can you imagine? I mean, it's like minus 25 degrees and then you attack the energy system. I mean, it's so crazy that only Russians would do such a thing. But this is how Russia is and it will not change. And I think our problem in Ukraine is still that there are still red lines when it comes to the weapons they can use to win this war. And you cannot win a war with the one hand tied on your back. We need to give them weapons so they can strike into Russia. We have had this discussion for several years. We are still discussing it. I mean, for the last three years on this conference, I have said, why are we not providing them the air defense that they need? And everybody is doing like this. They still lack air defense. You cannot protect a country without air defense. We know exactly what we need to deliver, including, of course, membership of NATO, because if they were a NATO member now, we would be in a completely different situation now. So, we know what to do. But first of all, we have to recognize, we have to understand, we have to learn that Russia will not change and they are not interested in peace, unfortunately.

Anton Gerashchenko

105,935 görüntüleme • 5 ay önce