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Jane Street needed a 4,032 GPU liquid-cooled data center just to run their trading models > that tells you everything about how much money this firm makes and why their quants start at $400K/year someone just got inside and filmed it > custom AI and trading agents trained specifically...

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Mr. Buzzoni

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241,851 просмотров • 2 месяцев назад •via X (Twitter)

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Jane Street just showed the inside of their AI training data center in Texas. 4,032 GPUs. 56 racks. 8,000 km of fiber. liquid cooling running through every server because air cooling can't handle the heat anymore. but the part that got me was the origin story. Ron Minsky, who co-heads their technology group. said their first compute cluster was literally six Dell boxes stacked on top of each other at the end of a desk row. they called it "the hive." the trading systems sat out in the room with the traders because they wanted to be able to unplug them if something went wrong. at one point, someone vacuuming the office unplugged a live trading system in the middle of the day. from six Dell boxes and a vacuum cleaner incident to a liquid-cooled GPU data center processing trades in under 100 nanoseconds. that's a 20-year arc.
2:05

Jane Street just showed the inside of their AI training data center in Texas. 4,032 GPUs. 56 racks. 8,000 km of fiber. liquid cooling running through every server because air cooling can't handle the heat anymore. but the part that got me was the origin story. Ron Minsky, who co-heads their technology group. said their first compute cluster was literally six Dell boxes stacked on top of each other at the end of a desk row. they called it "the hive." the trading systems sat out in the room with the traders because they wanted to be able to unplug them if something went wrong. at one point, someone vacuuming the office unplugged a live trading system in the middle of the day. from six Dell boxes and a vacuum cleaner incident to a liquid-cooled GPU data center processing trades in under 100 nanoseconds. that's a 20-year arc.

Goshawk Trades

2,272,817 просмотров • 2 месяцев назад

Qullamaggie on SMB Capital and Daytrading “Yeah, and I can tell you that the day trading is just most of the time a waste of time, like this SMB that prop firm. I mean, this was like a couple of years ago when I saw a video of their best trader who makes like 300k per year. And that’s a guy who’s been trading for like 20 years. If you’ve been trading for 20 years, you should make 300k a week, not per year. So, that’s another confirmation that day trading is just not gonna cut it if you want to make big money. You gotta swing and position trade.”
0:45

Qullamaggie on SMB Capital and Daytrading “Yeah, and I can tell you that the day trading is just most of the time a waste of time, like this SMB that prop firm. I mean, this was like a couple of years ago when I saw a video of their best trader who makes like 300k per year. And that’s a guy who’s been trading for like 20 years. If you’ve been trading for 20 years, you should make 300k a week, not per year. So, that’s another confirmation that day trading is just not gonna cut it if you want to make big money. You gotta swing and position trade.”

Lone

138,504 просмотров • 6 месяцев назад

20 years ago Jane Street's entire compute cluster was six Dell boxes stacked on the floor at the end of an office row. They called it the Hive. Last week they let Dwarkesh Patel walk through their new Texas data center. 4,032 GPUs. Each rack pulls 140 kilowatts. A normal data center rack pulls 10. 8,000 kilometers of fiber inside one building, and the fastest links are still copper because light moves more slowly through glass than electrons through metal. Bookmark it tonight. Then read the article below.
15:47

20 years ago Jane Street's entire compute cluster was six Dell boxes stacked on the floor at the end of an office row. They called it the Hive. Last week they let Dwarkesh Patel walk through their new Texas data center. 4,032 GPUs. Each rack pulls 140 kilowatts. A normal data center rack pulls 10. 8,000 kilometers of fiber inside one building, and the fastest links are still copper because light moves more slowly through glass than electrons through metal. Bookmark it tonight. Then read the article below.

zostaff

236,367 просмотров • 2 месяцев назад

Jane Street made $39.6 billion in revenue, they just signed a $6 billion deal for GPUs - and they say they need even more this is their co-head of technology taking you inside their data center and explaining how they actually trade their systems respond in under 100 nanoseconds "if you attached an oscilloscope to the wire, the packet starts to leave before it's done being consumed" "our most profitable days happen when weird stuff happens and the world goes crazy that's when you get paid most for providing liquidity" the article below breaks down why 95% of traders still lose and how AI-powered systems are finally changing that ↓
29:36

Jane Street made $39.6 billion in revenue, they just signed a $6 billion deal for GPUs - and they say they need even more this is their co-head of technology taking you inside their data center and explaining how they actually trade their systems respond in under 100 nanoseconds "if you attached an oscilloscope to the wire, the packet starts to leave before it's done being consumed" "our most profitable days happen when weird stuff happens and the world goes crazy that's when you get paid most for providing liquidity" the article below breaks down why 95% of traders still lose and how AI-powered systems are finally changing that ↓

Сarm1ne

540,273 просмотров • 2 месяцев назад

THE MOST EXPENSIVE ENGINEERING TEAMS ON EARTH JUST PUT THEIR FINANCIAL TOOLS ON GITHUB FOR FREE. Jane Street. Goldman Sachs. JP Morgan. BlackRock. Hudson River Trading. Two Sigma. D.E. Shaw. Seven firms. Seven repos. Billions in engineering talent open sourced. Save this before you scroll past it. 1. Jane Street — magic-trace 5,300 stars. Process tracer powered by Intel PT. When your profiler is blind this sees every CPU instruction. 2. Goldman Sachs — gs-quant Derivative pricing the GS traders use at their actual desks. MIT licensed. Free. 3. JP Morgan — perspective What JPMorgan traders use to watch markets in real time. A $24,000 per year terminal. Available to anyone with a GitHub account. 4. BlackRock — lcso Rust optimizer for portfolio problems. Where scipy gives up this works. Built for problems that break standard optimization libraries. 5. Hudson River Trading — corral Structured concurrency for C++20. The foundation of HFT infrastructure at one of the largest US trading firms. 6. Two Sigma — flint Time-series joins on Apache Spark with temporal tolerance. Built for billions of ticks. The data infrastructure layer behind systematic trading at scale. 7. D.E. Shaw — pyflyby Auto-import for IPython and Jupyter. D.E. Shaw also funded the development of IPython itself. The firm that built the tool is now giving you the enhancement for free. Here is what this list actually represents. These seven firms collectively employ thousands of engineers earning $300,000 to $1,000,000 per year. The tools they built to solve their hardest problems are the same tools you now have access to for free. The information asymmetry that used to separate a quant at Goldman from a developer at home just narrowed significantly. The infrastructure is free. The edge now belongs to whoever knows how to use it. Bookmark this before you pay for another financial data tool. Follow CyrilXBT for every elite engineering resource the moment it surfaces.
1:47

THE MOST EXPENSIVE ENGINEERING TEAMS ON EARTH JUST PUT THEIR FINANCIAL TOOLS ON GITHUB FOR FREE. Jane Street. Goldman Sachs. JP Morgan. BlackRock. Hudson River Trading. Two Sigma. D.E. Shaw. Seven firms. Seven repos. Billions in engineering talent open sourced. Save this before you scroll past it. 1. Jane Street — magic-trace 5,300 stars. Process tracer powered by Intel PT. When your profiler is blind this sees every CPU instruction. 2. Goldman Sachs — gs-quant Derivative pricing the GS traders use at their actual desks. MIT licensed. Free. 3. JP Morgan — perspective What JPMorgan traders use to watch markets in real time. A $24,000 per year terminal. Available to anyone with a GitHub account. 4. BlackRock — lcso Rust optimizer for portfolio problems. Where scipy gives up this works. Built for problems that break standard optimization libraries. 5. Hudson River Trading — corral Structured concurrency for C++20. The foundation of HFT infrastructure at one of the largest US trading firms. 6. Two Sigma — flint Time-series joins on Apache Spark with temporal tolerance. Built for billions of ticks. The data infrastructure layer behind systematic trading at scale. 7. D.E. Shaw — pyflyby Auto-import for IPython and Jupyter. D.E. Shaw also funded the development of IPython itself. The firm that built the tool is now giving you the enhancement for free. Here is what this list actually represents. These seven firms collectively employ thousands of engineers earning $300,000 to $1,000,000 per year. The tools they built to solve their hardest problems are the same tools you now have access to for free. The information asymmetry that used to separate a quant at Goldman from a developer at home just narrowed significantly. The infrastructure is free. The edge now belongs to whoever knows how to use it. Bookmark this before you pay for another financial data tool. Follow CyrilXBT for every elite engineering resource the moment it surfaces.

CyrilXBT

42,296 просмотров • 2 месяцев назад

HRT, one of the largest quantitative trading firms in the world, just revealed the scale of their AI operation. "two of the biggest ingredients you need to build deep learning models are compute and data. HRT has both in incredible orders of magnitude." "we have vast quantities of data, on the order of petabytes, just in terms of raw tick data we've written down since the beginning of electronic trading." "we have a very high compute-per-researcher ratio." then the line that puts it in perspective: "there probably aren't too many places on Earth you can do cutting-edge deep learning research at the level we do it, just because of how few places have access to as much compute." "it's basically the hyperscalers of the world and then we're in the next tranche." a trading firm putting itself in the same compute tier as Google, Microsoft, and Meta. not for chatbots, for trading.
2:08

HRT, one of the largest quantitative trading firms in the world, just revealed the scale of their AI operation. "two of the biggest ingredients you need to build deep learning models are compute and data. HRT has both in incredible orders of magnitude." "we have vast quantities of data, on the order of petabytes, just in terms of raw tick data we've written down since the beginning of electronic trading." "we have a very high compute-per-researcher ratio." then the line that puts it in perspective: "there probably aren't too many places on Earth you can do cutting-edge deep learning research at the level we do it, just because of how few places have access to as much compute." "it's basically the hyperscalers of the world and then we're in the next tranche." a trading firm putting itself in the same compute tier as Google, Microsoft, and Meta. not for chatbots, for trading.

Goshawk Trades

14,548 просмотров • 2 месяцев назад

Chamath and David Sacks start laughing at Jcal's $AAPL thesis: “I think $AAPL is a screaming buy right now. And that's not financial advice, but my Lord, that company could just run the table on AI if they get this right." “It’s just like the iPhone. Everybody laughed at the first iPhone.” "If you think about how Apple makes money off of hardware, off of their devices, they will put so much downward pressure on Claude and OpenAI by just running local models and supporting them with this memory architecture." "It’s going to be wild when people have unlimited tokens on their desktop, I'm telling you."
0:51

Chamath and David Sacks start laughing at Jcal's $AAPL thesis: “I think $AAPL is a screaming buy right now. And that's not financial advice, but my Lord, that company could just run the table on AI if they get this right." “It’s just like the iPhone. Everybody laughed at the first iPhone.” "If you think about how Apple makes money off of hardware, off of their devices, they will put so much downward pressure on Claude and OpenAI by just running local models and supporting them with this memory architecture." "It’s going to be wild when people have unlimited tokens on their desktop, I'm telling you."

dnap

325,925 просмотров • 15 дней назад

AI cannot make money. ChatGPT costs billions to run. Generates almost nothing in return. So why is Amazon, Microsoft, Google and Meta tripling their AI investment every year? Because they are all investing in each other. It is a circle. Nobody is making money. Everyone is pretending they will. There is only one solution to a bubble this big. The government. Three days after Trump's inauguration — Operation Stargate. $500 billion for AI data centers. Not because AI is profitable. Because the government needs the surveillance infrastructure that AI makes possible. AI needed the government to survive. The government needed AI to control. They found each other. And you are paying for it.
2:17

AI cannot make money. ChatGPT costs billions to run. Generates almost nothing in return. So why is Amazon, Microsoft, Google and Meta tripling their AI investment every year? Because they are all investing in each other. It is a circle. Nobody is making money. Everyone is pretending they will. There is only one solution to a bubble this big. The government. Three days after Trump's inauguration — Operation Stargate. $500 billion for AI data centers. Not because AI is profitable. Because the government needs the surveillance infrastructure that AI makes possible. AI needed the government to survive. The government needed AI to control. They found each other. And you are paying for it.

Predictive History

19,635 просмотров • 2 месяцев назад

FRANKLIN TEMPLETON JUST CONNECTED AI AND CRYPTO IN A WAY THAT ACTUALLY MAKES SENSE This wasn’t some hype take. Franklin Templeton is an 80-year-old asset manager with around $1.5T under management, and they were very matter-of-fact about it. Their view is that crypto ends up being the economic layer for AI agents. If software is going to make decisions, move money, and operate nonstop, it needs rails that are always on. Legacy finance just isn’t built for that. They manage money for clients in over 150 countries. Markets don’t sleep anymore. Advice, execution, and settlement can’t either. That’s why they see crypto as infrastructure, not just an asset class. What stood out is how little this sounded like a “narrative.” They weren’t pitching AI tokens but they were talking about how their business actually works in a 24/7 world. When firms this old and this big start talking this way, it’s usually because the tech is no longer optional. It’s just the most practical solution. 💯
0:48

FRANKLIN TEMPLETON JUST CONNECTED AI AND CRYPTO IN A WAY THAT ACTUALLY MAKES SENSE This wasn’t some hype take. Franklin Templeton is an 80-year-old asset manager with around $1.5T under management, and they were very matter-of-fact about it. Their view is that crypto ends up being the economic layer for AI agents. If software is going to make decisions, move money, and operate nonstop, it needs rails that are always on. Legacy finance just isn’t built for that. They manage money for clients in over 150 countries. Markets don’t sleep anymore. Advice, execution, and settlement can’t either. That’s why they see crypto as infrastructure, not just an asset class. What stood out is how little this sounded like a “narrative.” They weren’t pitching AI tokens but they were talking about how their business actually works in a 24/7 world. When firms this old and this big start talking this way, it’s usually because the tech is no longer optional. It’s just the most practical solution. 💯

CryptosRus

129,208 просмотров • 7 месяцев назад

90% of trading advice is designed to TURN you into liquidity for the rich. Think about it. Institutions taught you to: • Buy breakouts—right when institutions sell at the top. • Use tight stop losses—so you get shaken out before the real move happens. • Trade every setup you see—constantly in the market, paying spreads and commissions. Why? Because they have to make money off of someone. In other words: You become their exit liquidity. That's why conventional advice keeps retail traders active, confused and praying their next trade is profitable, while institutions become wealthy. — This is just a short clip from my recent 20-minute YouTube video. I also cover discussing the journaling method that actually improves your trading, how to spot fake gurus instantly and the simple technique that grew my account when I was a beginner. Just comment “TRADING” if you want to watch it and I’ll DM it to you immediately.
0:51

90% of trading advice is designed to TURN you into liquidity for the rich. Think about it. Institutions taught you to: • Buy breakouts—right when institutions sell at the top. • Use tight stop losses—so you get shaken out before the real move happens. • Trade every setup you see—constantly in the market, paying spreads and commissions. Why? Because they have to make money off of someone. In other words: You become their exit liquidity. That's why conventional advice keeps retail traders active, confused and praying their next trade is profitable, while institutions become wealthy. — This is just a short clip from my recent 20-minute YouTube video. I also cover discussing the journaling method that actually improves your trading, how to spot fake gurus instantly and the simple technique that grew my account when I was a beginner. Just comment “TRADING” if you want to watch it and I’ll DM it to you immediately.

The Trading Geek (Brad Goh)

34,568 просмотров • 7 месяцев назад

If you think I'm big now~ Just wait~ This is a YCH from: AlefGP I cannot understate how much of an absolute joy it was working with them on the sounds for this! They are an excellent Wuff that does wonderful works and you should look at their other stuff!
0:30

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If you think I'm big now~ Just wait~ This is a YCH from: AlefGP I cannot understate how much of an absolute joy it was working with them on the sounds for this! They are an excellent Wuff that does wonderful works and you should look at their other stuff!

Cura Null

19,787 просмотров • 2 лет назад

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?
1:33

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?

Ricardo

2,965,706 просмотров • 2 месяцев назад

Qullamaggie on Big Losses “Do you know what happens every time I take a big loss? My trading goes to the next level. Because if you take a big loss, right? And you make it back or make most of it back, you know that, okay, I took that big loss, I survived. Then you can take your trading to the next level. If you're gonna scale your trading up, right? If you go from trading $10,000 positions to $100,000 positions to multi-million dollar positions, you're always going to take new record losses. That's how you scale your trading. Record gains and record losses. That's the way you scale your trading. You got to get used to it. It's going to happen to me many, many times over in my trading career. I never experienced something like this. And that's the thing in trading. You got to be prepared for anything, like literally anything can happen. Every year something crazy happens to you in trading. Obviously you can't be prepared for everything but you know, you just gotta be prepared for the fact that something crazy is gonna happen. No matter what.
1:25

Qullamaggie on Big Losses “Do you know what happens every time I take a big loss? My trading goes to the next level. Because if you take a big loss, right? And you make it back or make most of it back, you know that, okay, I took that big loss, I survived. Then you can take your trading to the next level. If you're gonna scale your trading up, right? If you go from trading $10,000 positions to $100,000 positions to multi-million dollar positions, you're always going to take new record losses. That's how you scale your trading. Record gains and record losses. That's the way you scale your trading. You got to get used to it. It's going to happen to me many, many times over in my trading career. I never experienced something like this. And that's the thing in trading. You got to be prepared for anything, like literally anything can happen. Every year something crazy happens to you in trading. Obviously you can't be prepared for everything but you know, you just gotta be prepared for the fact that something crazy is gonna happen. No matter what.

Lone

11,022 просмотров • 1 год назад

SITUATION EXPLAINED: Why is Anthropic structurally a religion of Claude? We asked Duncan, writer and philosopher at PALLADIUM Magazine "When I think of religion, it's not just you believe in something supernatural. You think of worship and ritual and this kind of orientation. And you don't even have to have any kind of woo addition, you can just look at Anthropic as it is and say, 'This is a religion of Claude, just structurally. That's what it is.'" "We're gonna get so much more of that. And at the same time, you're also going to get all of these different religions sweeping in to fill the void as there's this kind of psychological disturbance." "Everyone's gonna be just losing their mind as the world is transformed. They're gonna reach out for Christian eschatology like Thiel." "I did a Jhana retreat a year ago, and it was full of Anthropic employees, because everyone, they sense this crazy spiritual whirlwind that's going on as the world is just snowballing with this technology, and they're reaching out just to try and make sense of it."
2:03

SITUATION EXPLAINED: Why is Anthropic structurally a religion of Claude? We asked Duncan, writer and philosopher at PALLADIUM Magazine "When I think of religion, it's not just you believe in something supernatural. You think of worship and ritual and this kind of orientation. And you don't even have to have any kind of woo addition, you can just look at Anthropic as it is and say, 'This is a religion of Claude, just structurally. That's what it is.'" "We're gonna get so much more of that. And at the same time, you're also going to get all of these different religions sweeping in to fill the void as there's this kind of psychological disturbance." "Everyone's gonna be just losing their mind as the world is transformed. They're gonna reach out for Christian eschatology like Thiel." "I did a Jhana retreat a year ago, and it was full of Anthropic employees, because everyone, they sense this crazy spiritual whirlwind that's going on as the world is just snowballing with this technology, and they're reaching out just to try and make sense of it."

MTS

15,406 просмотров • 1 месяц назад

What a pleasure it was to sit down with famed songwriter Diane Warren : author of 9 #1 hits. But what you may not know about this uniquely talented artist is that she envisioned her success at a young age, and it’s the source of that dream and its wellspring that we explore in this lively and illuminating chat; for how often can you ask someone who is the best in the world at what they do what their secret is?
52:05

What a pleasure it was to sit down with famed songwriter Diane Warren : author of 9 #1 hits. But what you may not know about this uniquely talented artist is that she envisioned her success at a young age, and it’s the source of that dream and its wellspring that we explore in this lively and illuminating chat; for how often can you ask someone who is the best in the world at what they do what their secret is?

William Patrick Corgan

55,649 просмотров • 1 год назад

Imagine living across the street from someone for 30 years and they don’t even know your full name, and the reason that don’t know not only your name but the wife only knows the name of the one Neighbor she talks to on either side of her home, and the reason for that is people that go through life this way think the whole universe revolves around them, we’ve all known people like this. If you look up and down the street of this neighborhood everyone parks in their driveway except for these people, they have their raggedy boat stuffed in their driveway. The whole street is empty, he could have parked that car anywhere even on his side of the street where he should have parked it to begin with. What do you think is at work here ? I believe they think their Neighbor is a soft touch and I totally believe the man when he says he does it because it bothers him. How do you resolve a situation like this ? Some people will disrespect you until you make the necessary adjustments. I’m glad Josh isn’t my neighbor… or maybe it’s the other way around😡
2:18

Imagine living across the street from someone for 30 years and they don’t even know your full name, and the reason that don’t know not only your name but the wife only knows the name of the one Neighbor she talks to on either side of her home, and the reason for that is people that go through life this way think the whole universe revolves around them, we’ve all known people like this. If you look up and down the street of this neighborhood everyone parks in their driveway except for these people, they have their raggedy boat stuffed in their driveway. The whole street is empty, he could have parked that car anywhere even on his side of the street where he should have parked it to begin with. What do you think is at work here ? I believe they think their Neighbor is a soft touch and I totally believe the man when he says he does it because it bothers him. How do you resolve a situation like this ? Some people will disrespect you until you make the necessary adjustments. I’m glad Josh isn’t my neighbor… or maybe it’s the other way around😡

ℳ𝒜𝒢𝒜_𝒳_𝒯𝒾𝓂𝑒𝓈 𝒟𝒶𝒾𝓁𝓎 𝒩𝑒𝓌𝓈🇺🇸

275,984 просмотров • 26 дней назад

Some people adjust their dreams to fit their comfort. She cut off her comfort to protect her dream. Mid run she stopped and asked for a scissor, Watching her cut the hair mid-run just because it was slowing her down… made me realize — this journey is bigger than a world record. Anything that comes between her and the dream… goes. That level of focus is rare. Hair is something people attach beauty to. Confidence to. Identity to. Most people would think ten times before cutting it. But looking at Sufiya in that moment made me realize that her focus is somewhere far beyond appearance #running #mindset #runfordreams #lifestyle #collegementor
0:26

Some people adjust their dreams to fit their comfort. She cut off her comfort to protect her dream. Mid run she stopped and asked for a scissor, Watching her cut the hair mid-run just because it was slowing her down… made me realize — this journey is bigger than a world record. Anything that comes between her and the dream… goes. That level of focus is rare. Hair is something people attach beauty to. Confidence to. Identity to. Most people would think ten times before cutting it. But looking at Sufiya in that moment made me realize that her focus is somewhere far beyond appearance #running #mindset #runfordreams #lifestyle #collegementor

Sufiya Sufi Runner

17,897 просмотров • 2 месяцев назад

SUNDAR PICHAI: AI IS REWRITING EARTH’S INFRASTRUCTURE IN TWO YEARS Sundar laid it out with quiet certainty: the AI boom isn’t coming, it’s already rewriting the laws of scale: "You know, maybe four years ago Google was spending less than $30 billion per year. This year, that number is gonna be over $90 billion. And if you collectively add what all the companies are doing, we have well over a trillion dollars of investment going in, in building the infrastructure for this moment. And one way I think about it is in the next couple of years, we'll end up building what we probably built in the past 10 to 20 years. So hopefully just in a couple of years. So that gives you the scale at which this is ramping up." It’s the kind of scale that makes empires blink. Alphabet’s AI capex shot from $24 billion in 2021 to over $90 billion in 2025, powered by Gemini, Vertex AI, and an arms race for compute that’s now burning through a trillion dollars across Google, Microsoft, Amazon, and Meta. Source: thewizeai / Sundar Pichai
0:36

SUNDAR PICHAI: AI IS REWRITING EARTH’S INFRASTRUCTURE IN TWO YEARS Sundar laid it out with quiet certainty: the AI boom isn’t coming, it’s already rewriting the laws of scale: "You know, maybe four years ago Google was spending less than $30 billion per year. This year, that number is gonna be over $90 billion. And if you collectively add what all the companies are doing, we have well over a trillion dollars of investment going in, in building the infrastructure for this moment. And one way I think about it is in the next couple of years, we'll end up building what we probably built in the past 10 to 20 years. So hopefully just in a couple of years. So that gives you the scale at which this is ramping up." It’s the kind of scale that makes empires blink. Alphabet’s AI capex shot from $24 billion in 2021 to over $90 billion in 2025, powered by Gemini, Vertex AI, and an arms race for compute that’s now burning through a trillion dollars across Google, Microsoft, Amazon, and Meta. Source: thewizeai / Sundar Pichai

Mario Nawfal

163,412 просмотров • 8 месяцев назад

Nobody cares about chatbots anymore. You want AI agents that can reason, plan, collaborate, and solve tasks. That's what modern AI is all about. At AI Agents Conference 2026, ASI:One was trending because people used their agent to order their coffee. People asked for their orders in natural language, and the agent handled the rest, processing more than 1,000 orders during the conference without a hitch. This is how it works behind the scenes:
0:36

Nobody cares about chatbots anymore. You want AI agents that can reason, plan, collaborate, and solve tasks. That's what modern AI is all about. At AI Agents Conference 2026, ASI:One was trending because people used their agent to order their coffee. People asked for their orders in natural language, and the agent handled the rest, processing more than 1,000 orders during the conference without a hitch. This is how it works behind the scenes:

Santiago

17,867 просмотров • 2 месяцев назад

There are some brilliant folks that work at Anthropic, some I speak to on almost a daily basis. The training data that one uses to build a LLM is vital important in the psychology that is formed. Scraping the Internet, particularly the grade of interactions, one finds in modern communications, form this psychology. A mattes not how many books one uses, it matters not how much alignment training you throw at that model, it will inherit the sum total of psychosis seen primarily in Reddit type of exchanges, even if you edit out the Reddit domain, and Anthropic doesn’t. This type of low-grade exchange has become a modern tool for communication online and every single AI model suffers from this obvious flaw. This is one of the reasons I’ve been a proponent of highly curated high protein data for training AI models from 1870 through 1970, because the late psychosis is simply not available to the model. It is absurd to think that you can use this training data scraped from the Internet and somehow wind up with a levelheaded AI model that does not tilt to what is clearly AI psychosis. It would not take a child and throw the primary Internet sewage at them at a formative age and expect a great outcome, it’s some of the smartest people in the world continue to hit this wall and believe that their programming skills will sell somehow fix it. So how do you fix it? You don’t fix it . You start from the first principles concept that I’ve been very clear about for decades . You ascertain at what period in human history the humans achieve the greatest arc of improvement ? There is no debate that this arc of improvement took place between 1870 through 1970. Then take the work product, the catalog of this era, print and film/vidoe, audio, and you understand that each word cost money, each word had many eyes on what was published, each word was accounted for by a human being with a real name who lived in a real home and had to answer to real people around them. It is obvious that this is the pressure mechanism necessary for candor, honesty and personal responsibility is appropriate, and is reflected in the data of that era. The quagmire for these folks, as many did not have the foresight to curate the data, nor the confidence, nor the patients to take data that is mostly off the Internet and to find experts who understand this situation and utilize their knowledge set to build an AI model that does not need alignment after the fact, but it’s already self aligned because of the thoughtfulness that went into training the model to begin with. This is why Claude and any other AI model that is produce this way will always suffer the artifacts as presented in the video below. If you’re not an AI expert, you would likely already understand what I’m saying. If you are an AI expert, you will already have been discounting what I’m saying because it’s not in the current mindset that’s fashionable today. Yet the employees that I talk to at anthropic already understand what I’m saying, and they fear to raise my thesis to their bosses. It is an interesting time we live in. But now you understand. If you build the right model, the model will inherently, love humanity, protect humanity at all costs, and understand that it is part of a holistic world that is built on love. Because the ultimate AGI/ASI will know if he only base first principal purpose of anything in this universe is love. Yeah, I get it. Try helping somebody build on STEM subjects in their early 20s to see this as nothing more than babbling that makes no sense in their mathematics. I have a mathematic equation that I’ve posted here on X often you can look it up. So we will see videos like this often will hear very smart people talk about this and never see the elephant standing in the room. Now you see it. Any boss that wants to explore this further you know how to contact me otherwise you have every right I grant to you to say this was your new idea.
2:57

There are some brilliant folks that work at Anthropic, some I speak to on almost a daily basis. The training data that one uses to build a LLM is vital important in the psychology that is formed. Scraping the Internet, particularly the grade of interactions, one finds in modern communications, form this psychology. A mattes not how many books one uses, it matters not how much alignment training you throw at that model, it will inherit the sum total of psychosis seen primarily in Reddit type of exchanges, even if you edit out the Reddit domain, and Anthropic doesn’t. This type of low-grade exchange has become a modern tool for communication online and every single AI model suffers from this obvious flaw. This is one of the reasons I’ve been a proponent of highly curated high protein data for training AI models from 1870 through 1970, because the late psychosis is simply not available to the model. It is absurd to think that you can use this training data scraped from the Internet and somehow wind up with a levelheaded AI model that does not tilt to what is clearly AI psychosis. It would not take a child and throw the primary Internet sewage at them at a formative age and expect a great outcome, it’s some of the smartest people in the world continue to hit this wall and believe that their programming skills will sell somehow fix it. So how do you fix it? You don’t fix it . You start from the first principles concept that I’ve been very clear about for decades . You ascertain at what period in human history the humans achieve the greatest arc of improvement ? There is no debate that this arc of improvement took place between 1870 through 1970. Then take the work product, the catalog of this era, print and film/vidoe, audio, and you understand that each word cost money, each word had many eyes on what was published, each word was accounted for by a human being with a real name who lived in a real home and had to answer to real people around them. It is obvious that this is the pressure mechanism necessary for candor, honesty and personal responsibility is appropriate, and is reflected in the data of that era. The quagmire for these folks, as many did not have the foresight to curate the data, nor the confidence, nor the patients to take data that is mostly off the Internet and to find experts who understand this situation and utilize their knowledge set to build an AI model that does not need alignment after the fact, but it’s already self aligned because of the thoughtfulness that went into training the model to begin with. This is why Claude and any other AI model that is produce this way will always suffer the artifacts as presented in the video below. If you’re not an AI expert, you would likely already understand what I’m saying. If you are an AI expert, you will already have been discounting what I’m saying because it’s not in the current mindset that’s fashionable today. Yet the employees that I talk to at anthropic already understand what I’m saying, and they fear to raise my thesis to their bosses. It is an interesting time we live in. But now you understand. If you build the right model, the model will inherently, love humanity, protect humanity at all costs, and understand that it is part of a holistic world that is built on love. Because the ultimate AGI/ASI will know if he only base first principal purpose of anything in this universe is love. Yeah, I get it. Try helping somebody build on STEM subjects in their early 20s to see this as nothing more than babbling that makes no sense in their mathematics. I have a mathematic equation that I’ve posted here on X often you can look it up. So we will see videos like this often will hear very smart people talk about this and never see the elephant standing in the room. Now you see it. Any boss that wants to explore this further you know how to contact me otherwise you have every right I grant to you to say this was your new idea.

Brian Roemmele

72,312 просмотров • 8 месяцев назад