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Mark Cuban told his daughter that critical thinking, tool fluency, and curiosity guarantee a job. The same week, Cost Plus Drugs grew its headcount 42% over the last twelve months. Cost Plus Drugs runs on a vertically integrated supply chain. 115 employees. A 22,000 square foot Dallas manufacturing facility....

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Aakash Gupta

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43,588 просмотров • 4 месяцев назад •via X (Twitter)

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Mark Cuban says there will only be two types of companies in 3 years "If the CEO doesn't understand that, he's not going to be CEO very long, you tell me so I can start a company to kick their ass" "When it's all said and done over the next three years, there's going to be two types of companies: those who are great at AI and those who went out of business"
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Mark Cuban says there will only be two types of companies in 3 years "If the CEO doesn't understand that, he's not going to be CEO very long, you tell me so I can start a company to kick their ass" "When it's all said and done over the next three years, there's going to be two types of companies: those who are great at AI and those who went out of business"

katsu

68,301 просмотров • 4 месяцев назад

Everything in the economy runs on the same input. Compute, AI, robotics, manufacturing, transport... it's all energy underneath. That matters now because of demographics. Fewer workers every year means the economy only grows if output per head grows fast, and the engine for that is the Exponential Age... AI and robotics doing the work people used to. But all of that runs on energy. So the cost of energy is the ceiling on the whole thing. That's why the EU, Japan, China, the US and the UK are all moving at the same time. If we can take the cost of energy to near zero, GDP per capita stops being hostage to the price of a barrel of oil. That's the way out of this mess.
0:50

Everything in the economy runs on the same input. Compute, AI, robotics, manufacturing, transport... it's all energy underneath. That matters now because of demographics. Fewer workers every year means the economy only grows if output per head grows fast, and the engine for that is the Exponential Age... AI and robotics doing the work people used to. But all of that runs on energy. So the cost of energy is the ceiling on the whole thing. That's why the EU, Japan, China, the US and the UK are all moving at the same time. If we can take the cost of energy to near zero, GDP per capita stops being hostage to the price of a barrel of oil. That's the way out of this mess.

Raoul Pal

122,299 просмотров • 1 месяц назад

Chamath said AI is not like the internet. Every new user costs real money. And the infrastructure making it possible was built by everyone. His argument was the clearest case for government ownership of AI labs I have ever heard. And it had nothing to do with Bernie Sanders. Start with the internet comparison. Google and Facebook became the most profitable companies in human history because of one number. The marginal cost of adding a new user was effectively zero. One more search query cost Google nothing. One more Facebook profile cost Meta nothing. They could serve a billion people and the incremental cost of that billion person was rounding error. That is the money printer. Infinite scale at zero marginal cost. AI breaks that model completely. Every single user taxes a GPU. Every query costs electricity. Every response requires memory and compute. The marginal cost of AI is real, significant, and does not disappear at scale. You cannot print money the same way. Then Chamath made the point that landed hardest. The infrastructure these companies depend on, the power grid, the land, the data centers, the permitting, the national security apparatus that protects their chips from being stolen, none of that was built by Anthropic or OpenAI. It was built by the public. By taxpayers. By decades of government investment in the physical and legal foundation these companies are now running on. He compared it to the interstate highway system. If the federal government built the roads and two companies transported all the goods on them, a logical question at that point would be how much of that should I own? You are riding on my rails. His conclusion was direct. If he were running a sovereign wealth fund and had the negotiating leverage of the US government, he would own 75% of these companies when he was done. The internet had zero marginal cost. That is why the founders captured almost all of the value. AI has real marginal cost and runs on public infrastructure. That changes who has a claim on what gets built. WATCH THE FULL PODCAST ON The All-In Podcast
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Chamath said AI is not like the internet. Every new user costs real money. And the infrastructure making it possible was built by everyone. His argument was the clearest case for government ownership of AI labs I have ever heard. And it had nothing to do with Bernie Sanders. Start with the internet comparison. Google and Facebook became the most profitable companies in human history because of one number. The marginal cost of adding a new user was effectively zero. One more search query cost Google nothing. One more Facebook profile cost Meta nothing. They could serve a billion people and the incremental cost of that billion person was rounding error. That is the money printer. Infinite scale at zero marginal cost. AI breaks that model completely. Every single user taxes a GPU. Every query costs electricity. Every response requires memory and compute. The marginal cost of AI is real, significant, and does not disappear at scale. You cannot print money the same way. Then Chamath made the point that landed hardest. The infrastructure these companies depend on, the power grid, the land, the data centers, the permitting, the national security apparatus that protects their chips from being stolen, none of that was built by Anthropic or OpenAI. It was built by the public. By taxpayers. By decades of government investment in the physical and legal foundation these companies are now running on. He compared it to the interstate highway system. If the federal government built the roads and two companies transported all the goods on them, a logical question at that point would be how much of that should I own? You are riding on my rails. His conclusion was direct. If he were running a sovereign wealth fund and had the negotiating leverage of the US government, he would own 75% of these companies when he was done. The internet had zero marginal cost. That is why the founders captured almost all of the value. AI has real marginal cost and runs on public infrastructure. That changes who has a claim on what gets built. WATCH THE FULL PODCAST ON The All-In Podcast

Ihtesham Ali

79,378 просмотров • 2 месяцев назад

Friedberg: Two Reasons Why Drug Prices are So Expensive in America 📈 🫰 1) Government intervention in the market 🏢 "The way that we negotiate drug prices is pretty messed up." "As is the case with the cost of education and the cost of housing, the cost of drugs is largely inflated because of the federal government's role in being the primary buyer or capital provider to that market." "Through our purchases of prescription drugs, the federal government, as a buyer, doesn't have any incentive to keep prices low." " If every individual had to pay for their drugs, or private insurance was the only way to get your drugs, we would have a much more dynamic marketplace." 2) PBMs marking up prices 📈 "There's also this construct in the market, these PBMs or pharmacy benefit managers." "If they got cut out of the market, it would save a lot." "There's three major PBMs, CVS Caremark, Express Scripts, and Optum RX. They make money in markups." "The FTC has been investigating them and have several open cases." "Between 2017 and 2022, the estimate is that these companies generated $7.3B in excess profit by marking up prices on specialty generic drugs." "So as an intermediary, they provide this role where they can coordinate between the health insurer, the pharmacy which dispenses the drugs, and the drug manufacturers." Chamath: " But they're allowed to be owned by the payer, which is crazy." Friedberg: " And now they're allowed to be owned by the payer." "And there's a lot of obfuscation of the true cost of the drugs. There's a lot of markups, a lot of spread taking." "And so if you took the PBMs out of the market, that would solve one of the problems." " But at the end of the day, anytime the federal government is involved as a payer in any market-based system, it creates a distortion and the market is no longer free or efficient." david friedberg
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Friedberg: Two Reasons Why Drug Prices are So Expensive in America 📈 🫰 1) Government intervention in the market 🏢 "The way that we negotiate drug prices is pretty messed up." "As is the case with the cost of education and the cost of housing, the cost of drugs is largely inflated because of the federal government's role in being the primary buyer or capital provider to that market." "Through our purchases of prescription drugs, the federal government, as a buyer, doesn't have any incentive to keep prices low." " If every individual had to pay for their drugs, or private insurance was the only way to get your drugs, we would have a much more dynamic marketplace." 2) PBMs marking up prices 📈 "There's also this construct in the market, these PBMs or pharmacy benefit managers." "If they got cut out of the market, it would save a lot." "There's three major PBMs, CVS Caremark, Express Scripts, and Optum RX. They make money in markups." "The FTC has been investigating them and have several open cases." "Between 2017 and 2022, the estimate is that these companies generated $7.3B in excess profit by marking up prices on specialty generic drugs." "So as an intermediary, they provide this role where they can coordinate between the health insurer, the pharmacy which dispenses the drugs, and the drug manufacturers." Chamath: " But they're allowed to be owned by the payer, which is crazy." Friedberg: " And now they're allowed to be owned by the payer." "And there's a lot of obfuscation of the true cost of the drugs. There's a lot of markups, a lot of spread taking." "And so if you took the PBMs out of the market, that would solve one of the problems." " But at the end of the day, anytime the federal government is involved as a payer in any market-based system, it creates a distortion and the market is no longer free or efficient." david friedberg

The All-In Podcast

45,353 просмотров • 1 год назад

Mark Cuban on the door-to-door garbage bag business that taught him how to sell at age 12: It started because his dad wouldn't buy him a pair of shoes. Cuban was 12, and he wanted new Converse. His dad was in the middle of a poker game. "Dad, I need a new pair of Converse, right?" Cuban recalls asking. His father wasn't moved: "I see those, you know, those shoes on your feet. They still work, right?" Cuban admitted they did. So his dad laid down the rule that would end up shaping his career: "Well, when you have a job, you can buy whatever you want, but until then, those shoes still work." Cuban pushed back with the obvious problem: "Dad, I can't get a job. I'm 12 years old." Then one of his dad's poker buddies spoke up. "Yeah, I got a job for you," the man said. "I've got these boxes of garbage bags and you can go sell them around the neighborhood." So that's what Cuban did. He knocked on doors with a simple pitch: "Hi, I'm your neighbor, Mark. Do you use garbage bags?" The economics were straightforward. The boxes cost him three dollars for a hundred. He sold them for six. Then he'd come back every couple of weeks to restock his neighbors whenever they needed more. He was clearing about 20 bucks a week, which felt like big time, and he got his shoes. The money was never the real lesson. What stuck with him was what selling actually is: "That taught me to be confident and that taught me that I could sell. And that taught me that selling was helping, not convincing." That distinction became the foundation of how Mark Cuban thinks about business. Once he realized everyone already needed garbage bags, the whole game clarified: "Once I figured out that everybody needed garbage bags, then it really became obvious to me that if I can find things that people needed, right, and wanted and I could do it a better way than what they were doing it, then I can make some money. And that's kind of stayed with me since."
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Mark Cuban on the door-to-door garbage bag business that taught him how to sell at age 12: It started because his dad wouldn't buy him a pair of shoes. Cuban was 12, and he wanted new Converse. His dad was in the middle of a poker game. "Dad, I need a new pair of Converse, right?" Cuban recalls asking. His father wasn't moved: "I see those, you know, those shoes on your feet. They still work, right?" Cuban admitted they did. So his dad laid down the rule that would end up shaping his career: "Well, when you have a job, you can buy whatever you want, but until then, those shoes still work." Cuban pushed back with the obvious problem: "Dad, I can't get a job. I'm 12 years old." Then one of his dad's poker buddies spoke up. "Yeah, I got a job for you," the man said. "I've got these boxes of garbage bags and you can go sell them around the neighborhood." So that's what Cuban did. He knocked on doors with a simple pitch: "Hi, I'm your neighbor, Mark. Do you use garbage bags?" The economics were straightforward. The boxes cost him three dollars for a hundred. He sold them for six. Then he'd come back every couple of weeks to restock his neighbors whenever they needed more. He was clearing about 20 bucks a week, which felt like big time, and he got his shoes. The money was never the real lesson. What stuck with him was what selling actually is: "That taught me to be confident and that taught me that I could sell. And that taught me that selling was helping, not convincing." That distinction became the foundation of how Mark Cuban thinks about business. Once he realized everyone already needed garbage bags, the whole game clarified: "Once I figured out that everybody needed garbage bags, then it really became obvious to me that if I can find things that people needed, right, and wanted and I could do it a better way than what they were doing it, then I can make some money. And that's kind of stayed with me since."

Big Brain Business

338,845 просмотров • 23 дней назад

💊 The Hidden Cost of "Savings": Is Price Gouging Subsidizing Insurance Giants? Ever wondered why a generic medication that costs $55 can be priced at $6,600? 🤨 In a recent Congressional hearing, CVS CEO David Joyner defended this practice as "cross-subsidized pricing." 🔍 Here's the Breakdown: The Logic: Joyner argues that charging higher prices for low-cost generics helps subsidize the cost of expensive brand-name medications. The Reality: Pharmacy Benefit Managers (PBMs) use their power to negotiate rebates on brand-name drugs, which can actually increase their overall cost. The Shell Game: These rebates may be held by shell companies before being "passed on" to clients (like your employer), potentially hiding billions in profits. 📉 Is it Really "Savings"? When you're charged over $6,500 more than the actual cost of a drug, it's hard to see the "savings." This highlights a significant lack of transparency in the pharmaceutical supply chain. 💡 Take Action: Compare Prices: Don't just settle for the price at your local pharmacy. Check out Forest Park Pharmacy to see the real cost of your prescriptions. Stay Informed: Understand how PBMs and "cross-subsidized pricing" impact your healthcare costs. What do you think? Is this "cross-subsidized pricing" a necessary part of the system or just a way to hide profits? Let's discuss! 👇
1:58

💊 The Hidden Cost of "Savings": Is Price Gouging Subsidizing Insurance Giants? Ever wondered why a generic medication that costs $55 can be priced at $6,600? 🤨 In a recent Congressional hearing, CVS CEO David Joyner defended this practice as "cross-subsidized pricing." 🔍 Here's the Breakdown: The Logic: Joyner argues that charging higher prices for low-cost generics helps subsidize the cost of expensive brand-name medications. The Reality: Pharmacy Benefit Managers (PBMs) use their power to negotiate rebates on brand-name drugs, which can actually increase their overall cost. The Shell Game: These rebates may be held by shell companies before being "passed on" to clients (like your employer), potentially hiding billions in profits. 📉 Is it Really "Savings"? When you're charged over $6,500 more than the actual cost of a drug, it's hard to see the "savings." This highlights a significant lack of transparency in the pharmaceutical supply chain. 💡 Take Action: Compare Prices: Don't just settle for the price at your local pharmacy. Check out Forest Park Pharmacy to see the real cost of your prescriptions. Stay Informed: Understand how PBMs and "cross-subsidized pricing" impact your healthcare costs. What do you think? Is this "cross-subsidized pricing" a necessary part of the system or just a way to hide profits? Let's discuss! 👇

Forest Park Pharmacy

20,602 просмотров • 7 месяцев назад

David Friedberg: The AI Jobs Panic Is a Crock of Sh*t Why? The revenue potential outweighs the cost savings by 100x. “There is no job loss with AI. I've said it a thousand times, and I will say it again, and again, and again. What I see on the ground, and what I've seen at dozens of companies, including my company that I run, there are two sides to a business. There is revenue and there’s costs. On the cost side of the equation, AI can be used to reduce humans doing things that cost money, to some extent. The effect there, I would argue, is nominal. The real opportunity with AI is on the revenue side, where suddenly one engineer can do 100x or 1000x what they used to be able to do, meaning you can make more products at your company, whether those are agricultural seed products, or boats and ships, or software for companies, or clothing, or what have you. Because of AI, everyone has the ability to expand their revenue base to create more products, and that is the foundation of good economic prosperity. It is called productivity. We can grow productivity in this country with AI. So where I see AI being used is on the revenue side 100x more than the cost side. And in that equation, people are hiring like crazy. We cannot hire enough people. I just had a review meeting with my product and engineering team two days ago, and they're like, ‘We want to add an extra 15 headcount to our engineering squads because we have all this opportunity to do stuff that we couldn't otherwise do.’ So we are going to hire more people. And to Sacks' point, we are seeing that show up in the jobs numbers. The idea that AI is going to destroy jobs is a Luddite idea that is being disproven every single day, and I see it on the ground. It is only a matter of time before people wake up to this and they realize that this narrative that they've all been sold is a crock of sh*t.”
1:42

David Friedberg: The AI Jobs Panic Is a Crock of Sh*t Why? The revenue potential outweighs the cost savings by 100x. “There is no job loss with AI. I've said it a thousand times, and I will say it again, and again, and again. What I see on the ground, and what I've seen at dozens of companies, including my company that I run, there are two sides to a business. There is revenue and there’s costs. On the cost side of the equation, AI can be used to reduce humans doing things that cost money, to some extent. The effect there, I would argue, is nominal. The real opportunity with AI is on the revenue side, where suddenly one engineer can do 100x or 1000x what they used to be able to do, meaning you can make more products at your company, whether those are agricultural seed products, or boats and ships, or software for companies, or clothing, or what have you. Because of AI, everyone has the ability to expand their revenue base to create more products, and that is the foundation of good economic prosperity. It is called productivity. We can grow productivity in this country with AI. So where I see AI being used is on the revenue side 100x more than the cost side. And in that equation, people are hiring like crazy. We cannot hire enough people. I just had a review meeting with my product and engineering team two days ago, and they're like, ‘We want to add an extra 15 headcount to our engineering squads because we have all this opportunity to do stuff that we couldn't otherwise do.’ So we are going to hire more people. And to Sacks' point, we are seeing that show up in the jobs numbers. The idea that AI is going to destroy jobs is a Luddite idea that is being disproven every single day, and I see it on the ground. It is only a matter of time before people wake up to this and they realize that this narrative that they've all been sold is a crock of sh*t.”

The All-In Podcast

152,399 просмотров • 2 месяцев назад

A one-man trading hedge fund now costs about $100 a month in AI subscriptions. Five PhDs on a Citadel desk cost $270,000 a month, and that is the cheap end. That buys one tested idea a month. Man Group's AI writes hundreds of new signals a week, on a floor where the humans used to manage twenty in a quarter. Fifty AI agents do the reading and the writing. One of them exists only to destroy what the others build, and that one is the reason any of it works. Every job on that payroll is now an agent you can run yourself: > AI research agents reading filings, transcripts, options flow and on-chain data overnight, fifty personas at once, none of them allowed to see what the crowd is pricing > coding agent that turns one sentence of plain English into entry rules, exit rules, sizing and risk limits, then debugs itself until it runs > backtest agent that replays five years of that idea in about 12 seconds > breaker agent, an AI whose only job is killing the thing, at double the trading costs and in the ten worst markets that asset has ever seen > critic agent that reads your journal and names the mistake you keep making Nobody on that list asks for a bonus in January. $200 million is already run this way on one platform where 52,000 people mostly sit and watch the machine work. The full map of what is built and what is missing is in the article below. Bookmark & read it If you're not yet using AI in your trading and investing.
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A one-man trading hedge fund now costs about $100 a month in AI subscriptions. Five PhDs on a Citadel desk cost $270,000 a month, and that is the cheap end. That buys one tested idea a month. Man Group's AI writes hundreds of new signals a week, on a floor where the humans used to manage twenty in a quarter. Fifty AI agents do the reading and the writing. One of them exists only to destroy what the others build, and that one is the reason any of it works. Every job on that payroll is now an agent you can run yourself: > AI research agents reading filings, transcripts, options flow and on-chain data overnight, fifty personas at once, none of them allowed to see what the crowd is pricing > coding agent that turns one sentence of plain English into entry rules, exit rules, sizing and risk limits, then debugs itself until it runs > backtest agent that replays five years of that idea in about 12 seconds > breaker agent, an AI whose only job is killing the thing, at double the trading costs and in the ten worst markets that asset has ever seen > critic agent that reads your journal and names the mistake you keep making Nobody on that list asks for a bonus in January. $200 million is already run this way on one platform where 52,000 people mostly sit and watch the machine work. The full map of what is built and what is missing is in the article below. Bookmark & read it If you're not yet using AI in your trading and investing.

cvxv666

172,099 просмотров • 19 дней назад

Dylan explains why the next wave of private equity looks nothing like the last one. "If we're looking at these companies that are AI rollups, let's take an existing company and completely destroy its cost structure. Nuke its cost structure by just making it efficient with AI." "Private equity companies buy a company, and right now they just squeeze the rag, discard it, and make the American populace screwed." "What new people started to do is the AI private equity strategy. Instead of trying to wring it dry, they're modernizing all the systems. Oh, you use Excel for your databases? Okay, let's move to standard cloud. Spend a lot of money up front." "AI makes that front load much more severe. You spike up on spend a lot for the one time, and then you spike down a lot and your cost efficiency is way better. AI cold calling, AI invoicing, AI accounting, none of it is really at critical mass. But we're so close."
2:42

Dylan explains why the next wave of private equity looks nothing like the last one. "If we're looking at these companies that are AI rollups, let's take an existing company and completely destroy its cost structure. Nuke its cost structure by just making it efficient with AI." "Private equity companies buy a company, and right now they just squeeze the rag, discard it, and make the American populace screwed." "What new people started to do is the AI private equity strategy. Instead of trying to wring it dry, they're modernizing all the systems. Oh, you use Excel for your databases? Okay, let's move to standard cloud. Spend a lot of money up front." "AI makes that front load much more severe. You spike up on spend a lot for the one time, and then you spike down a lot and your cost efficiency is way better. AI cold calling, AI invoicing, AI accounting, none of it is really at critical mass. But we're so close."

SemiAnalysis

72,852 просмотров • 11 дней назад

Eric Schmidt says the real limit on AI is cash, and he puts one gigawatt of data center at roughly $50 billion: "A gigawatt data center costs something on the order of 50 billion with a B number." "How could these people in my industry be so crazy to raise all that money and build all the data centers? And the answer is they see the demand." "So absent an AI breakthrough algorithmically, which is a change to what is called the transformer architecture which is invented at Google, thank you, in 2017, we're sort of stuck with this cost structure." "And I think the real limit to AI is not energy. It's actually cash." "Because when you add up the cost of these, if you take 50, just round numbers, 50 billion a gigawatt, so 10 gigawatts is half a trillion dollars." "How many companies, countries, and so forth can hand an industry a trillion dollars of capital? Very, very few." Even at the low end of the published estimates, around $38 billion a gigawatt, his arithmetic still puts ten gigawatts in the hundreds of billions, so the conclusion holds. Very few balance sheets can carry that, which means most companies buying AI capacity over the next few years will be renting it from the handful that can. - Eric Schmidt (Eric Schmidt), Chair of the Special Competitive Studies Project and CEO of Relativity Space, at the SCSP AI+ Expo (@SCSPAI), May 2026.
1:13

Eric Schmidt says the real limit on AI is cash, and he puts one gigawatt of data center at roughly $50 billion: "A gigawatt data center costs something on the order of 50 billion with a B number." "How could these people in my industry be so crazy to raise all that money and build all the data centers? And the answer is they see the demand." "So absent an AI breakthrough algorithmically, which is a change to what is called the transformer architecture which is invented at Google, thank you, in 2017, we're sort of stuck with this cost structure." "And I think the real limit to AI is not energy. It's actually cash." "Because when you add up the cost of these, if you take 50, just round numbers, 50 billion a gigawatt, so 10 gigawatts is half a trillion dollars." "How many companies, countries, and so forth can hand an industry a trillion dollars of capital? Very, very few." Even at the low end of the published estimates, around $38 billion a gigawatt, his arithmetic still puts ten gigawatts in the hundreds of billions, so the conclusion holds. Very few balance sheets can carry that, which means most companies buying AI capacity over the next few years will be renting it from the handful that can. - Eric Schmidt (Eric Schmidt), Chair of the Special Competitive Studies Project and CEO of Relativity Space, at the SCSP AI+ Expo (@SCSPAI), May 2026.

Karl Mehta

42,936 просмотров • 10 дней назад

WOAH 🚨 Pay attention to this American pharmacist exposing that some cheap, very effective drugs, HAVE BEEN BANNED form being prescribed because they’re too cheap So instead of the cheap option, drugs that cost $1,000+ are allowed for certain treatments (INSANE) “The most insane examples of why drugs cost so much is a drug called Brenzavvy. You almost certainly haven't heard of it, but you've probably heard of similar drugs like Jardiance or Farxiga. The reason you haven't heard of Brenzavvy, though, is because no insurance companies will cover it. Most doctors won't prescribe it, and most wholesalers won't even carry it. When I tell you why our entire healthcare industry is turning its back on this proven drug in one of the most critical classes in existence, you are going to be furious. They are shunning Brenzavvy because it's too cheap. I'm not being hyperbolic or sensational. I mean it literally. At my pharmacy, Brenzavvy costs $60 bucks. When they took that price to the pharmacy benefits managers, or PBMs, that's the people in charge of deciding what's covered on your insurance, they all said no, because Brenzavvy can't do a rebate at a price that low. Farxiga and Jardiance, the other Drugs in the SLGT 2 class with Brenzavvy, cost insurance payers $1000 bucks each prescription up front. Then they get a big, probably like 40% rebate later. So that's a $400 rebate, and that is a huge selling point for the PBMs to prove how important they are. The PBMs get a piece of that rebate, and they get a percentage of the final price. An HHS report from last year said that the PBMs get 23% on average for for brand meds. After the rebate, Farxiga and Jardiance still cost $600. 23% of that is $138 for the middleman. Those drugs get dispensed 8 million times a year, which means the total they make in a year off of those two drugs is $1.1 billion. They don't make the drug, they don't prescribe it, they don't dispense it, they don't sell it. They only have to do one thing to make that money. Keep Brenzavvy off their list. If they let in a drug that costs 1/10 of the price and doesn't pay rebate, they literally lose a billion dollars a year. To me, that's the clearest example of why we will never get affordable health care in America. As long as we have PBMs involved, they can't afford to save you money.“ So while this might not be an outright ban, meaning illegal to create, for all purposes it is a ban. Because if the insurance companies won’t cover it, their doctors won’t prescribe it and nearly all wholesalers won’t carry it, that means the insurances companies and PBMs are effectively banning medication in America so they can make maximum profits. Billions a year on a single Medicine, when there are much cheaper options available for the customer This is organized crime. This is racketeering
2:27

WOAH 🚨 Pay attention to this American pharmacist exposing that some cheap, very effective drugs, HAVE BEEN BANNED form being prescribed because they’re too cheap So instead of the cheap option, drugs that cost $1,000+ are allowed for certain treatments (INSANE) “The most insane examples of why drugs cost so much is a drug called Brenzavvy. You almost certainly haven't heard of it, but you've probably heard of similar drugs like Jardiance or Farxiga. The reason you haven't heard of Brenzavvy, though, is because no insurance companies will cover it. Most doctors won't prescribe it, and most wholesalers won't even carry it. When I tell you why our entire healthcare industry is turning its back on this proven drug in one of the most critical classes in existence, you are going to be furious. They are shunning Brenzavvy because it's too cheap. I'm not being hyperbolic or sensational. I mean it literally. At my pharmacy, Brenzavvy costs $60 bucks. When they took that price to the pharmacy benefits managers, or PBMs, that's the people in charge of deciding what's covered on your insurance, they all said no, because Brenzavvy can't do a rebate at a price that low. Farxiga and Jardiance, the other Drugs in the SLGT 2 class with Brenzavvy, cost insurance payers $1000 bucks each prescription up front. Then they get a big, probably like 40% rebate later. So that's a $400 rebate, and that is a huge selling point for the PBMs to prove how important they are. The PBMs get a piece of that rebate, and they get a percentage of the final price. An HHS report from last year said that the PBMs get 23% on average for for brand meds. After the rebate, Farxiga and Jardiance still cost $600. 23% of that is $138 for the middleman. Those drugs get dispensed 8 million times a year, which means the total they make in a year off of those two drugs is $1.1 billion. They don't make the drug, they don't prescribe it, they don't dispense it, they don't sell it. They only have to do one thing to make that money. Keep Brenzavvy off their list. If they let in a drug that costs 1/10 of the price and doesn't pay rebate, they literally lose a billion dollars a year. To me, that's the clearest example of why we will never get affordable health care in America. As long as we have PBMs involved, they can't afford to save you money.“ So while this might not be an outright ban, meaning illegal to create, for all purposes it is a ban. Because if the insurance companies won’t cover it, their doctors won’t prescribe it and nearly all wholesalers won’t carry it, that means the insurances companies and PBMs are effectively banning medication in America so they can make maximum profits. Billions a year on a single Medicine, when there are much cheaper options available for the customer This is organized crime. This is racketeering

Wall Street Apes

107,917 просмотров • 1 год назад

#WATCH | Mumbai, Maharashtra: On the Jevons paradox and software demand expansion, Neelkanth Mishra, Executive Director Designate of the World Bank, says, “…If you think about what the major cost of a software firm is, it is people. So, if the writing of software is getting automated, those firms will be the first to make adjustments. But on the whole, it seems that the Jevons paradox—which dictates that as the cost of writing software falls, the amount of software written goes up—is actually playing out. If an XYZ company, which is a product company, was spending, say, $100 million on writing software and can now do it for $70 million, they might need to lay off some people; that is their business priority. But if the amount of software written goes up three to four times, the number of software engineers in the ecosystem will not change… This panic and paranoia about massive job losses is something that I think is, at this stage, unfounded.”
2:48

#WATCH | Mumbai, Maharashtra: On the Jevons paradox and software demand expansion, Neelkanth Mishra, Executive Director Designate of the World Bank, says, “…If you think about what the major cost of a software firm is, it is people. So, if the writing of software is getting automated, those firms will be the first to make adjustments. But on the whole, it seems that the Jevons paradox—which dictates that as the cost of writing software falls, the amount of software written goes up—is actually playing out. If an XYZ company, which is a product company, was spending, say, $100 million on writing software and can now do it for $70 million, they might need to lay off some people; that is their business priority. But if the amount of software written goes up three to four times, the number of software engineers in the ecosystem will not change… This panic and paranoia about massive job losses is something that I think is, at this stage, unfounded.”

ANI

114,594 просмотров • 2 месяцев назад

Mark Cuban just told every software company on Earth they’re already dead. The people inside them are still building roadmaps. Cuban: “Software is dead because everything’s going to be customized to your unique utilization.” Every SaaS company was built on one bet. Software stays rigid. Humans stay adaptable. You learn the tool. You bend to it. You pay for someone else’s version of your solution. AI just inverted that. The tool bends to you or it dies. Cuban: “33 million companies aren’t going to have AI budgets, aren’t going to have AI experts.” 33 million businesses feel something shifting beneath them. None can name it. The distance between what AI can do and what small companies can access is the most mispriced gap in markets today. Not a technology problem. A translation problem. Cuban: “Learn all you can about AI but learn more on how to implement them in companies.” Everyone is racing to build intelligence. Almost nobody is racing to deploy it where the pain is deepest. The person who walks into a 40-person company and rewires their entire operation captures more value than the team that trained the model. Understanding pain is now worth more than building intelligence. Cuban: “Every single job available for kids coming out of school because every single company needs that.” The most important career of the next decade has no title. No degree path. No university knows it needs to exist yet. It belongs to whoever learns two languages fluently. The language of a business that can’t articulate what’s breaking. And the language of an AI that doesn’t know where to aim. 33 million companies. Zero translators. Whoever arrives first doesn’t enter a market. They create one.
2:14

Mark Cuban just told every software company on Earth they’re already dead. The people inside them are still building roadmaps. Cuban: “Software is dead because everything’s going to be customized to your unique utilization.” Every SaaS company was built on one bet. Software stays rigid. Humans stay adaptable. You learn the tool. You bend to it. You pay for someone else’s version of your solution. AI just inverted that. The tool bends to you or it dies. Cuban: “33 million companies aren’t going to have AI budgets, aren’t going to have AI experts.” 33 million businesses feel something shifting beneath them. None can name it. The distance between what AI can do and what small companies can access is the most mispriced gap in markets today. Not a technology problem. A translation problem. Cuban: “Learn all you can about AI but learn more on how to implement them in companies.” Everyone is racing to build intelligence. Almost nobody is racing to deploy it where the pain is deepest. The person who walks into a 40-person company and rewires their entire operation captures more value than the team that trained the model. Understanding pain is now worth more than building intelligence. Cuban: “Every single job available for kids coming out of school because every single company needs that.” The most important career of the next decade has no title. No degree path. No university knows it needs to exist yet. It belongs to whoever learns two languages fluently. The language of a business that can’t articulate what’s breaking. And the language of an AI that doesn’t know where to aim. 33 million companies. Zero translators. Whoever arrives first doesn’t enter a market. They create one.

Dustin

473,624 просмотров • 1 месяц назад

Mark Cuban says AI will split every company into 2 categories within 3 years "When it's all said and done over the next 3 years, there's going to be two types of companies. Those who are great at AI and those who went out of business" "The biggest challenge for a company is going to be for the CEO to make that decision that we're going to have to blow up a lot of what we do to recreate our company" "We hear a lot of stories about huge public companies that spend a lot of money to try to implement AI and it doesn't really get them a return on investment." "Because you already are running your business the way you've always run it." "The things you've considered outsourcing, your customer call centers, AI agents are perfect for. The stuff you would give to an intern, AI agents are perfect for" "But to really take advantage of AI you have to reformulate your business completely to build it on AI"
5:18

Mark Cuban says AI will split every company into 2 categories within 3 years "When it's all said and done over the next 3 years, there's going to be two types of companies. Those who are great at AI and those who went out of business" "The biggest challenge for a company is going to be for the CEO to make that decision that we're going to have to blow up a lot of what we do to recreate our company" "We hear a lot of stories about huge public companies that spend a lot of money to try to implement AI and it doesn't really get them a return on investment." "Because you already are running your business the way you've always run it." "The things you've considered outsourcing, your customer call centers, AI agents are perfect for. The stuff you would give to an intern, AI agents are perfect for" "But to really take advantage of AI you have to reformulate your business completely to build it on AI"

Jaynit

196,796 просмотров • 3 месяцев назад

Elon Musk just explained why the SpaceX IPO is an energy story and the energy constraint is why he believes space becomes the only viable path for AI to scale (Save this). The argument he is making is one of the most important and least understood things happening in technology right now. The United States currently consumes roughly 500 gigawatts of electricity on average. To double that capacity which is what continued AI expansion on the current terrestrial trajectory would eventually require would mean building as many power plants as currently exist in the entire country. He is not arguing that this is technically impossible, just that communities are not willing to accept it, that permitting timelines make it unrealistic, and that the hard ceiling on Earth based power generation means the expansion of AI compute will eventually hit a wall that no amount of capital can overcome on the ground. His observation is that in space, that wall does not exist. A solar panel in orbit produces roughly five times more power than the same panel on Earth, operates in continuous sunlight uninterrupted by weather or nighttime, and benefits from the vacuum of space as a completely passive cooling system meaning the two largest operating costs of any terrestrial data center, energy and cooling, are effectively eliminated. He then said that you could theoretically increase harnessed energy by a factor of one million and still be using less than a millionth of the sun's total energy output. This is the underlying physics of why SpaceX filed with the FCC to launch up to one million solar powered AI satellites, and why they described that constellation in their own filing as a first step toward becoming a Kardashev Type II civilization capable of harnessing the full power of the sun. To understand what makes this credible rather than visionary, you need to understand what SpaceX already controls that no other company on earth possesses. Starship, once operating at full cadence, can deliver 100 to 150 tons of payload to orbit per launch, at a target cost per kilogram that is an order of magnitude lower than any existing vehicle. Musk's stated ambition is to scale Starship to 10,000 to 30,000 launches per year, a frequency that would allow the deployment of orbital compute infrastructure at a pace that is currently unimaginable with any existing rocket. He told xAI staff earlier this year that achieving space-based AI at scale will eventually require manufacturing facilities on the moon, building solar panels and heat dissipation structures from lunar silicon and aluminum, and launching them into orbit from there rather than from Earth's surface because the moon's lower gravity makes the economics of launch dramatically more favorable. SpaceX's S-1 filing explicitly states that its launch capabilities could enable massive AI compute satellite constellations with the potential for millions of satellites for orbital data centers, with the first launch potentially occurring as soon as 2028. Google and Alphabet are already in advanced talks with SpaceX about deploying space-based data centers. Starcloud, a startup running Nvidia H100 GPUs in orbit, has already validated that high-performance AI inference workloads can operate in space, with plans to scale to five gigawatts of orbital compute power by 2035. This is why Musk believes the cost crossover happens in two to three years because SpaceX's launch cost trajectory intersects with the accelerating energy constraint on the ground in a way that makes space genuinely cheaper, faster, and less regulated at exactly the moment AI demand is hitting its hardest physical limits.
1:01

Elon Musk just explained why the SpaceX IPO is an energy story and the energy constraint is why he believes space becomes the only viable path for AI to scale (Save this). The argument he is making is one of the most important and least understood things happening in technology right now. The United States currently consumes roughly 500 gigawatts of electricity on average. To double that capacity which is what continued AI expansion on the current terrestrial trajectory would eventually require would mean building as many power plants as currently exist in the entire country. He is not arguing that this is technically impossible, just that communities are not willing to accept it, that permitting timelines make it unrealistic, and that the hard ceiling on Earth based power generation means the expansion of AI compute will eventually hit a wall that no amount of capital can overcome on the ground. His observation is that in space, that wall does not exist. A solar panel in orbit produces roughly five times more power than the same panel on Earth, operates in continuous sunlight uninterrupted by weather or nighttime, and benefits from the vacuum of space as a completely passive cooling system meaning the two largest operating costs of any terrestrial data center, energy and cooling, are effectively eliminated. He then said that you could theoretically increase harnessed energy by a factor of one million and still be using less than a millionth of the sun's total energy output. This is the underlying physics of why SpaceX filed with the FCC to launch up to one million solar powered AI satellites, and why they described that constellation in their own filing as a first step toward becoming a Kardashev Type II civilization capable of harnessing the full power of the sun. To understand what makes this credible rather than visionary, you need to understand what SpaceX already controls that no other company on earth possesses. Starship, once operating at full cadence, can deliver 100 to 150 tons of payload to orbit per launch, at a target cost per kilogram that is an order of magnitude lower than any existing vehicle. Musk's stated ambition is to scale Starship to 10,000 to 30,000 launches per year, a frequency that would allow the deployment of orbital compute infrastructure at a pace that is currently unimaginable with any existing rocket. He told xAI staff earlier this year that achieving space-based AI at scale will eventually require manufacturing facilities on the moon, building solar panels and heat dissipation structures from lunar silicon and aluminum, and launching them into orbit from there rather than from Earth's surface because the moon's lower gravity makes the economics of launch dramatically more favorable. SpaceX's S-1 filing explicitly states that its launch capabilities could enable massive AI compute satellite constellations with the potential for millions of satellites for orbital data centers, with the first launch potentially occurring as soon as 2028. Google and Alphabet are already in advanced talks with SpaceX about deploying space-based data centers. Starcloud, a startup running Nvidia H100 GPUs in orbit, has already validated that high-performance AI inference workloads can operate in space, with plans to scale to five gigawatts of orbital compute power by 2035. This is why Musk believes the cost crossover happens in two to three years because SpaceX's launch cost trajectory intersects with the accelerating energy constraint on the ground in a way that makes space genuinely cheaper, faster, and less regulated at exactly the moment AI demand is hitting its hardest physical limits.

Milk Road AI

12,738 просмотров • 2 месяцев назад

My wife and I own Forest Park Pharmacy, and we don't accept insurance. None of it. That decision is exactly why we could fix what happened to a patient today. A family came in wanting to transfer their kid's antibiotic to us. The child had already STARTED the course. Then, mid-treatment, the insurance company decided the last 14 tablets suddenly needed a "prior authorization" before the other pharmacy could hand them over. A sick kid, halfway through an antibiotic, and the answer was "please hold." The drug is linezolid. It's a generic. It's been generic for over a decade. It treats serious gram-positive infections — the kind you do NOT want to stop antibiotics in the middle of, because an interrupted course is how you breed resistant bugs and end up right back where you started. So why the hold-up on a cheap, common generic? Follow the fake math. Insurance and the PBMs behind them price drugs off a number called AWP — "Average Wholesale Price." People in my industry have another name for it: "Ain't What's Paid." It's a benchmark number, not a real-world cost. On paper, the AWP for just those last 14 tablets is about $2,500. My cash price for the same 14 tablets? $18. Read that again. The system that's supposedly "protecting" this family from cost is the same system that inflated an $18 medication into a $2,500 line item, then slapped a prior auth on it to "review the expense" THEY invented. They manufactured the problem, then billed everyone for the privilege of solving it — and made a sick kid wait while they did it. This is the whole game. When a drug is priced honestly, there's nothing to "manage." When it's priced off a fantasy benchmark, you get spread pricing, PA paperwork, pharmacy phone trees, and delayed treatment — all dressed up as cost control. Here's the part nobody tells you: roughly 90% of prescriptions are low-cost generics. For the vast majority of what people pick up every day, running it through insurance does two things — raises the real cost and risks delaying your care. That's it. That's the value-add. That's why we fired the insurance companies. No middleman deciding your kid can't finish their antibiotics on schedule. No fake prices. Just the real number, on the shelf, today. The medication was always cheap. The insurance was the expensive part.
2:07

My wife and I own Forest Park Pharmacy, and we don't accept insurance. None of it. That decision is exactly why we could fix what happened to a patient today. A family came in wanting to transfer their kid's antibiotic to us. The child had already STARTED the course. Then, mid-treatment, the insurance company decided the last 14 tablets suddenly needed a "prior authorization" before the other pharmacy could hand them over. A sick kid, halfway through an antibiotic, and the answer was "please hold." The drug is linezolid. It's a generic. It's been generic for over a decade. It treats serious gram-positive infections — the kind you do NOT want to stop antibiotics in the middle of, because an interrupted course is how you breed resistant bugs and end up right back where you started. So why the hold-up on a cheap, common generic? Follow the fake math. Insurance and the PBMs behind them price drugs off a number called AWP — "Average Wholesale Price." People in my industry have another name for it: "Ain't What's Paid." It's a benchmark number, not a real-world cost. On paper, the AWP for just those last 14 tablets is about $2,500. My cash price for the same 14 tablets? $18. Read that again. The system that's supposedly "protecting" this family from cost is the same system that inflated an $18 medication into a $2,500 line item, then slapped a prior auth on it to "review the expense" THEY invented. They manufactured the problem, then billed everyone for the privilege of solving it — and made a sick kid wait while they did it. This is the whole game. When a drug is priced honestly, there's nothing to "manage." When it's priced off a fantasy benchmark, you get spread pricing, PA paperwork, pharmacy phone trees, and delayed treatment — all dressed up as cost control. Here's the part nobody tells you: roughly 90% of prescriptions are low-cost generics. For the vast majority of what people pick up every day, running it through insurance does two things — raises the real cost and risks delaying your care. That's it. That's the value-add. That's why we fired the insurance companies. No middleman deciding your kid can't finish their antibiotics on schedule. No fake prices. Just the real number, on the shelf, today. The medication was always cheap. The insurance was the expensive part.

Forest Park Pharmacy

538,671 просмотров • 2 месяцев назад

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.
0:35

Jensen Huang just explained why every company cutting engineers over AI is asking the entirely wrong question. Huang: “People say, I don’t need software engineers because apparently coding is going to be automated.” That was the narrative. Here is what Huang actually did. Huang: “I’ve given AIs to every one of my software engineers and hardware engineers and engineers period. 100% of NVIDIA has AI assistants, AI coders, and they’re busier than ever.” Not fewer engineers. Not smaller teams. Busier than ever. That is the line most companies are getting completely wrong right now. They hear “AI can write code” and immediately start cutting headcount. Huang did the opposite. He armed everyone. Huang: “And so the question is, what is the task versus what is the job? No different than a financial analyst; the task is mess around with spreadsheets, but the job is to make financial advice. The job is to help a customer.” Writing code was always the task. It was never the job. The job is architecture. Knowing what to build. Why it matters. How it fits into a system that actually creates value. Code is the execution layer between the idea and the outcome. Nothing more. When you automate that layer, you don’t eliminate the engineer. You eliminate the bottleneck between what they can envision and what they can ship. The companies using AI to cut headcount are optimizing for cost. The companies using AI to multiply output are optimizing for territory. Nvidia chose territory. Every engineer at the most valuable semiconductor company on Earth now operates with an AI assistant. Not a pilot program. Not an experiment. Company-wide. Every function. Every team. And the result is not less work. It is more work. Faster. At a scale that was physically impossible twelve months ago. The companies that understand the difference between eliminating engineers and unleashing them will build what comes next. The ones that don’t will watch their best talent walk out the door to the ones that did.

Dustin

82,810 просмотров • 5 месяцев назад

Tennessee just did what Congress can't. They passed a law to break up the health insurance giants. Specifically, they made it illegal for pharmacy benefit managers — the companies in charge of pharmacy insurance — and pharmacies to be owned by the same company. That makes perfect sense. For example: CVS Caremark is the PBM, and CVS is the pharmacy. So if you have Aetna insurance, you have CVS Caremark as your PBM, and they're going to do everything they can to make sure you use CVS as your pharmacy. Aetna, Caremark, CVS — all the same company. That causes all kinds of incredibly obvious problems that this law hopes to fix. If your insurance company is in charge of approving your medication, deciding how much to pay for it, AND deciding who gets that money — while also being the pharmacy that gets paid at the end — guess what happens to prices? They go up. Governor Lee signed the law last week. CVS immediately filed a federal lawsuit because they said it will force them to close all 136 stores they have in Tennessee. Let that sink in. I'm not sure most people realize what that says about CVS and health insurance in general. They had to choose between owning the middleman (the PBM) or the healthcare provider (the pharmacy). Without hesitation, they chose the middleman. The biggest pharmacy chain in the country — with a store on every corner — would drop all 136 of their Tennessee locations in a second if it means keeping their middleman business. It is more profitable for them to be a health insurance middleman getting between you and your healthcare than it is to actually provide the healthcare. That is the problem with healthcare in America. We have made the middleman so powerful that they've taken complete control of the entire system. Three PBMs — Caremark, Express Scripts, and OptumRx — handle around 80% of all prescriptions in this country. How on earth can we expect healthcare to work well and remain affordable if that's where the money is? We all auto-pay our insurance straight out of our paycheck before we even see the money. And not surprisingly, they're keeping a ton of it. That's why we fired them. And they can't file a lawsuit to stop us. That lets us offer fair, transparent prices. No PBMs. No insurance games. No hidden markups. You see the cost, you pay the cost.
2:32

Tennessee just did what Congress can't. They passed a law to break up the health insurance giants. Specifically, they made it illegal for pharmacy benefit managers — the companies in charge of pharmacy insurance — and pharmacies to be owned by the same company. That makes perfect sense. For example: CVS Caremark is the PBM, and CVS is the pharmacy. So if you have Aetna insurance, you have CVS Caremark as your PBM, and they're going to do everything they can to make sure you use CVS as your pharmacy. Aetna, Caremark, CVS — all the same company. That causes all kinds of incredibly obvious problems that this law hopes to fix. If your insurance company is in charge of approving your medication, deciding how much to pay for it, AND deciding who gets that money — while also being the pharmacy that gets paid at the end — guess what happens to prices? They go up. Governor Lee signed the law last week. CVS immediately filed a federal lawsuit because they said it will force them to close all 136 stores they have in Tennessee. Let that sink in. I'm not sure most people realize what that says about CVS and health insurance in general. They had to choose between owning the middleman (the PBM) or the healthcare provider (the pharmacy). Without hesitation, they chose the middleman. The biggest pharmacy chain in the country — with a store on every corner — would drop all 136 of their Tennessee locations in a second if it means keeping their middleman business. It is more profitable for them to be a health insurance middleman getting between you and your healthcare than it is to actually provide the healthcare. That is the problem with healthcare in America. We have made the middleman so powerful that they've taken complete control of the entire system. Three PBMs — Caremark, Express Scripts, and OptumRx — handle around 80% of all prescriptions in this country. How on earth can we expect healthcare to work well and remain affordable if that's where the money is? We all auto-pay our insurance straight out of our paycheck before we even see the money. And not surprisingly, they're keeping a ton of it. That's why we fired them. And they can't file a lawsuit to stop us. That lets us offer fair, transparent prices. No PBMs. No insurance games. No hidden markups. You see the cost, you pay the cost.

Forest Park Pharmacy

33,253 просмотров • 3 месяцев назад

Mark Cuban just compared the most powerful AI on earth to a two-year-old in a high chair. The toddler won. Cuban: “A two-year-old on a high chair with a sippy cup knows that when she pushes that cup off, Mom’s going to come running and the baby’s going to be laughing its ass off. It knows the consequences of its actions.” Then he named the thing no one building AI wants to say out loud. Cuban: “If you ask ChatGPT or any of them something and it gives you bad advice, it has no idea what’s going to happen because you took that bad advice.” A system that passed the bar exam. Aced medical boards. Still can’t grasp what a child who can’t tie her own shoes already knows. The child understands cause and effect. AI understands pattern and prediction. They sound similar. They are not even close. A pattern tells you what comes next in a sequence. Consequence tells you what happens to the person standing at the end of it. One is math. The other is meaning. Cuban went further. Cuban: “If you were blind at an intersection and had the choice between your seeing-eye dog or holding up a phone with AI, I’m taking the seeing-eye dog every time.” Because the dog understands something no language model on earth understands. Stakes. The dog knows a wrong step means its owner gets hurt. The app knows a wrong step means a revised output. Hundreds of billions spent building systems that can write, reason, and diagnose. Not one of them loses sleep when the answer is wrong. A toddler pushing a cup off a tray runs a tighter feedback loop than every foundation model combined. The child doesn’t just predict the outcome. The child wants the reaction. Pushes the cup off the edge, watches it fall, watches Mom come running. Laughs. Because the child knew what would happen before the cup ever hit the floor. That gap between prediction and consequence isn’t a bug. It’s not getting patched in the next update. It is the unsolved problem of artificial intelligence. We didn’t build minds. We built mirrors. Mirrors don’t flinch when you walk into traffic.
1:10

Mark Cuban just compared the most powerful AI on earth to a two-year-old in a high chair. The toddler won. Cuban: “A two-year-old on a high chair with a sippy cup knows that when she pushes that cup off, Mom’s going to come running and the baby’s going to be laughing its ass off. It knows the consequences of its actions.” Then he named the thing no one building AI wants to say out loud. Cuban: “If you ask ChatGPT or any of them something and it gives you bad advice, it has no idea what’s going to happen because you took that bad advice.” A system that passed the bar exam. Aced medical boards. Still can’t grasp what a child who can’t tie her own shoes already knows. The child understands cause and effect. AI understands pattern and prediction. They sound similar. They are not even close. A pattern tells you what comes next in a sequence. Consequence tells you what happens to the person standing at the end of it. One is math. The other is meaning. Cuban went further. Cuban: “If you were blind at an intersection and had the choice between your seeing-eye dog or holding up a phone with AI, I’m taking the seeing-eye dog every time.” Because the dog understands something no language model on earth understands. Stakes. The dog knows a wrong step means its owner gets hurt. The app knows a wrong step means a revised output. Hundreds of billions spent building systems that can write, reason, and diagnose. Not one of them loses sleep when the answer is wrong. A toddler pushing a cup off a tray runs a tighter feedback loop than every foundation model combined. The child doesn’t just predict the outcome. The child wants the reaction. Pushes the cup off the edge, watches it fall, watches Mom come running. Laughs. Because the child knew what would happen before the cup ever hit the floor. That gap between prediction and consequence isn’t a bug. It’s not getting patched in the next update. It is the unsolved problem of artificial intelligence. We didn’t build minds. We built mirrors. Mirrors don’t flinch when you walk into traffic.

Dustin

47,919 просмотров • 4 месяцев назад