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Cannot believe this is available for free on the internet Brad Gerstner sits down with Sunny Madra at Stanford University to discuss the economics of AI chips, GPUs, NVIDIA and tokens Sunny is by far one of the most impressive serial entrepreneurs of our time > Co-founded Xtreme Labs,... show more

Boring_Business

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Asked @pieterbot on AOL why NVIDIA acquired Groq Inc And they apparently did not, they just did a licensing deal for $20B Possibly to avoid antitrust laws (so Nvidia doesn't get a monopoly) "In a Christmas Eve deal, Nvidia has entered into a nonexclusive agreement to license technology from artificial intelligence chip start-up Groq, according to a statement on Groq’s website. Groq founder Jonathan Ross and sunny madra, Groq’s president, will leave the company and join Nvidia, bringing other engineering talent with them, according to the statement. Groq will remain an independent company, but it isn’t clear if Nvidia is taking an equity stake."

Asked @pieterbot on AOL why NVIDIA acquired Groq Inc And they apparently did not, they just did a licensing deal for $20B Possibly to avoid antitrust laws (so Nvidia doesn't get a monopoly) "In a Christmas Eve deal, Nvidia has entered into a nonexclusive agreement to license technology from artificial intelligence chip start-up Groq, according to a statement on Groq’s website. Groq founder Jonathan Ross and sunny madra, Groq’s president, will leave the company and join Nvidia, bringing other engineering talent with them, according to the statement. Groq will remain an independent company, but it isn’t clear if Nvidia is taking an equity stake."

@levelsio

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This 40 minute lecture at Stanford by Apoorv Agarwal on the Economics of AI supercycle is worth a watch Apoorv is currently a Partner at Altimeter and is directly involved in some of their key AI investments, including OpenAI and Glean Still find it incredible that the internet gives us access to this level of information directly. A course I will definitely be following along Sourced from MS&E 435 Stanford University

This 40 minute lecture at Stanford by Apoorv Agarwal on the Economics of AI supercycle is worth a watch Apoorv is currently a Partner at Altimeter and is directly involved in some of their key AI investments, including OpenAI and Glean Still find it incredible that the internet gives us access to this level of information directly. A course I will definitely be following along Sourced from MS&E 435 Stanford University

Boring_Business

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Early on, Jonathan Ross foresaw the unprecedented demand for compute of the 2020s. After pioneering Google's TPUs, he founded Groq, a "Language" Processing Unit dedicated for inference. After joining NVIDIA, he is betting on the GPU+LPU combo to power the agentic chains of AI calling AI calling AI. This interview is part of my larger series on dedicated AI chips, so drop any suggestions/questions below. Thank you NVIDIA for hosting us at your HQ! 00:00 Intro 01:00 The Google TPU & Groq origin story 02:41 How is Groq different from a GPU? 04:43 Static scheduling makes Groq faster 05:47 Does Groq work with Mixture-of-Experts? 09:27 Are LPUs limited to text models? 11:03 Diffusion models 13:41 NVIDIA Vera Rubin: the GPU+LPU combo 15:26 Will Groq still be sold as a standalone chip? 16:49 How does agentic AI impact inference economics? 19:21 Will AI replace CUDA kernel engineers? 21:08 Will AI democratize hardware design? 26:11 Jevon's paradox: An endless demand for compute 29:04 What should kids learn in the AI age?

Early on, Jonathan Ross foresaw the unprecedented demand for compute of the 2020s. After pioneering Google's TPUs, he founded Groq, a "Language" Processing Unit dedicated for inference. After joining NVIDIA, he is betting on the GPU+LPU combo to power the agentic chains of AI calling AI calling AI. This interview is part of my larger series on dedicated AI chips, so drop any suggestions/questions below. Thank you NVIDIA for hosting us at your HQ! 00:00 Intro 01:00 The Google TPU & Groq origin story 02:41 How is Groq different from a GPU? 04:43 Static scheduling makes Groq faster 05:47 Does Groq work with Mixture-of-Experts? 09:27 Are LPUs limited to text models? 11:03 Diffusion models 13:41 NVIDIA Vera Rubin: the GPU+LPU combo 15:26 Will Groq still be sold as a standalone chip? 16:49 How does agentic AI impact inference economics? 19:21 Will AI replace CUDA kernel engineers? 21:08 Will AI democratize hardware design? 26:11 Jevon's paradox: An endless demand for compute 29:04 What should kids learn in the AI age?

Julia Turc

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Kevin Ryan was CEO of DoubleClick which sold to Google for $3.1B. Then he co-founded successful companies like MongoDB, Business Insider, Zola and others. One of the most interesting under-the-radar founders and operators in tech. Full episode below

Kevin Ryan was CEO of DoubleClick which sold to Google for $3.1B. Then he co-founded successful companies like MongoDB, Business Insider, Zola and others. One of the most interesting under-the-radar founders and operators in tech. Full episode below

logan bartlett

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New episode on Jimmy Iovine—one of my favorite living entrepreneurs Jimmy went from sweeping the floor in a recording studio to becoming one the most successful record producers, founded Interscope, and sold Beats for billions. His 50 year career covered in 50 minutes!

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David Senra

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Nvidia just made its biggest acquisition ever... A small startup. On Christmas Eve. While everyone was distracted. The startup is Groq. They make AI chips that run faster than Nvidia's. In September, Groq raised $750 million at a $6.9 billion valuation. Investors included BlackRock, Samsung, Cisco, and Donald Trump Jr.'s fund 1789 Capital. Yesterday, Nvidia paid $20 billion for them. That's a 3x markup in 90 days. Trump Jr. just made a fortune overnight. But the money isn't even the craziest part... Nvidia dominates AI chips. They have 90%+ market share. All of big tech depends on them. So why would they pay 3X for a tiny competitor? Let me explain: Groq was building inference chips that threatened Nvidia's monopoly. Faster processing. Lower costs. Better architecture. If Groq succeeded, they'd crack open the market. So Nvidia did what monopolies always do: bought them before they became a threat. They're buying silence - not innovation. And this isn't a one-off. In September, Nvidia spent $900 million on Enfabrica, another AI chip startup. Same playbook. They committed $100 billion to OpenAI with a requirement that OpenAI deploy 10 gigawatts of Nvidia products. Now $20 billion for Groq. Nvidia isn't competing anymore. They're consolidating. They're using their cash pile to swallow every potential rival before they grow. The founder and CEO of Groq, Jonathan Ross, is joining Nvidia. So is the president and the entire leadership team. Groq's cloud business will keep running independently. But the tech, the IP, the competitive advantage? All Nvidia's now. This is the largest acquisition Nvidia has EVER made. Their previous record was $7 billion for Mellanox in 2019. They just tripled that. And nobody's questioning why. Everyone's celebrating "innovation" and "consolidation" and "strategic partnerships." But what actually happened is this: Nvidia looked at the one company that could challenge their monopoly and paid whatever it took to kill them. $20 billion is cheap insurance when you're worth trillions. The only question left is who's next.

Nvidia just made its biggest acquisition ever... A small startup. On Christmas Eve. While everyone was distracted. The startup is Groq. They make AI chips that run faster than Nvidia's. In September, Groq raised $750 million at a $6.9 billion valuation. Investors included BlackRock, Samsung, Cisco, and Donald Trump Jr.'s fund 1789 Capital. Yesterday, Nvidia paid $20 billion for them. That's a 3x markup in 90 days. Trump Jr. just made a fortune overnight. But the money isn't even the craziest part... Nvidia dominates AI chips. They have 90%+ market share. All of big tech depends on them. So why would they pay 3X for a tiny competitor? Let me explain: Groq was building inference chips that threatened Nvidia's monopoly. Faster processing. Lower costs. Better architecture. If Groq succeeded, they'd crack open the market. So Nvidia did what monopolies always do: bought them before they became a threat. They're buying silence - not innovation. And this isn't a one-off. In September, Nvidia spent $900 million on Enfabrica, another AI chip startup. Same playbook. They committed $100 billion to OpenAI with a requirement that OpenAI deploy 10 gigawatts of Nvidia products. Now $20 billion for Groq. Nvidia isn't competing anymore. They're consolidating. They're using their cash pile to swallow every potential rival before they grow. The founder and CEO of Groq, Jonathan Ross, is joining Nvidia. So is the president and the entire leadership team. Groq's cloud business will keep running independently. But the tech, the IP, the competitive advantage? All Nvidia's now. This is the largest acquisition Nvidia has EVER made. Their previous record was $7 billion for Mellanox in 2019. They just tripled that. And nobody's questioning why. Everyone's celebrating "innovation" and "consolidation" and "strategic partnerships." But what actually happened is this: Nvidia looked at the one company that could challenge their monopoly and paid whatever it took to kill them. $20 billion is cheap insurance when you're worth trillions. The only question left is who's next.

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The Manhattan Institute, which is funded by Zionist billionaire Paul Singer, presented Ben Shapiro with their "City Journal Award" two weeks ago in Florida. Tickets to the event for VIPs sold for $250,000. The Paul E. Singer Foundation and Bill Ackman's "The Carob Trust" (founded to combat "anti-Semitism") were listed as top donors.

The Manhattan Institute, which is funded by Zionist billionaire Paul Singer, presented Ben Shapiro with their "City Journal Award" two weeks ago in Florida. Tickets to the event for VIPs sold for $250,000. The Paul E. Singer Foundation and Bill Ackman's "The Carob Trust" (founded to combat "anti-Semitism") were listed as top donors.

Chris Menahan 🇺🇸

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🌟 The Star of the Show 🌟 This 1964 #Shelby Cobra Daytona Coupe is one of six created to defeat Ferrari’s 250 GTO. #SOLD for $42,905,000, the most valuable car ever sold by Gooding Christie's and a record at auction for a Shelby and for all American cars. #PebbleBeachAuctions

🌟 The Star of the Show 🌟 This 1964 #Shelby Cobra Daytona Coupe is one of six created to defeat Ferrari’s 250 GTO. #SOLD for $42,905,000, the most valuable car ever sold by Gooding Christie's and a record at auction for a Shelby and for all American cars. #PebbleBeachAuctions

Gooding Christie's

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🚨Announcing the 2nd Winner of the Golden Ticket 🚨 Tross! Founded by Padam and Meet, Tross is building the data and API layer for AI Agents in Healthcare. What really makes them stand apart is that they had already spent time in the US market, generated early revenue and validated the problem statement before even applying to us for their first ever round. Padam has already sold a startup before and Meet is one of the most capable CTOs we’ve met. Having worked together at BharatX, they’ve also figured out how to win together. This is exactly what we look for at All In Capital - Insane hustle to win customers and great co-founder chemistry. Currently Padam and Meet are on their second trip to the US and are presenting Tross at global health conferences across the country. Best of luck guys and we are here to do whatever we can to help you win!

🚨Announcing the 2nd Winner of the Golden Ticket 🚨 Tross! Founded by Padam and Meet, Tross is building the data and API layer for AI Agents in Healthcare. What really makes them stand apart is that they had already spent time in the US market, generated early revenue and validated the problem statement before even applying to us for their first ever round. Padam has already sold a startup before and Meet is one of the most capable CTOs we’ve met. Having worked together at BharatX, they’ve also figured out how to win together. This is exactly what we look for at All In Capital - Insane hustle to win customers and great co-founder chemistry. Currently Padam and Meet are on their second trip to the US and are presenting Tross at global health conferences across the country. Best of luck guys and we are here to do whatever we can to help you win!

Kushal Bhagia 🇮🇳

25,666 Aufrufe • vor 1 Monat

In 1993, Jensen Huang co-founded Nvidia. To incorporate and price the shares, a lawyer asked Huang for any money he had in his wallet. He gave $200 for 20% of Nvidia. Today, he has a 3.6% stake (worth ~$72B after Nvidia crossed $2T market cap). Lesson: Always keep cash on hand.

In 1993, Jensen Huang co-founded Nvidia. To incorporate and price the shares, a lawyer asked Huang for any money he had in his wallet. He gave $200 for 20% of Nvidia. Today, he has a 3.6% stake (worth ~$72B after Nvidia crossed $2T market cap). Lesson: Always keep cash on hand.

Trung Phan

2,695,592 Aufrufe • vor 2 Jahren

Jensen Huang just admitted the biggest AI labs can't borrow money like normal companies. So Nvidia signs for them, and they spend it on Nvidia chips. Nvidia reported Wednesday and the numbers are absurd: Revenue of $96.2 billion, up 106%, with net income of $59.7 billion, the most profitable quarter any public company has EVER posted. And Huang just told Fox Business that every chip Nvidia can make next year is already sold. Here's why this matters the most: Huang wrote this himself about his own customers: "Frontier AI labs have extraordinary demand for training and inference compute, but many are growing faster than their balance sheets and long-term credit profiles can support." Then: They "still lack the decades-long infrastructure contracts and investment-grade financing capacity needed to secure the AI factory infrastructure independently." Put simply: His customers can't get the loans. So Nvidia signs for them. There's a compute campus going up in Ohio with OpenAI as the tenant. Nvidia has tied roughly $105 billion in commitments to it. OpenAI's existing and planned commitments now come to about 12 gigawatts of Nvidia compute. CFO Colette Kress told analysts Nvidia will also provide selective credit enhancement for nearly 2 gigawatts of compute at a second frontier lab. She wouldn't say which one. Nvidia put up to $10 billion into Anthropic in November at a valuation near $350 billion, and Anthropic agreed to buy up to a gigawatt of Grace Blackwell and Vera Rubin systems in the same deal. And Nvidia isn't only guaranteeing these companies. It OWNS pieces of them. This week's filing shows $18 billion committed to equity investments for the rest of the fiscal year, and $47.9 billion already sitting in private companies as of late July. Now here's where it gets really insane: Last week, Huang sat on a CNBC set surrounded by six of Wall Street's biggest firms. Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR. They signed a memorandum to mobilise up to $500 billion in outside capital for AI data centres. Nvidia kept the option to backstop up to a quarter of those deals. And Huang used that stage to announce that Nvidia GPUs are now an asset class. Pension and credit funds can now lend against graphics cards the way they lend against office towers. Kress saw the accusation coming and got ahead of it on the earnings call: "We recognise the scale of this support, and we know some will call this circular financing. We see it differently." But look at the two things Huang says about the same companies. On the earnings call he said AI has hit its inflection point, that the tokens are productive and profitable, and that compute is now revenue. But he also said those same labs can't secure investment-grade financing on their own. A business that's inflecting into profit is exactly the business a bank lends to. Banks lend against cash flow every day. But Nvidia‘s guarantee exists because something in that first story isn't landing with the people whose job is pricing risk. Kress does have a real answer to this though. She said the second lab's credit support only complements capacity it already secured on its own, without Nvidia backing it. Vendor financing is also old and legal. Cisco did it and GE built a finance arm on it. Huang's case is that Nvidia understands these businesses better than any lender could, and he says the risk is low and his only regret is not investing more and sooner. He may be completely right. But one thing is certain: Nvidia guarantees the paper. The paper buys the chips. Nvidia books the sale. Then Nvidia tells you the order book is full for a year. That order book is the entire argument for a $5 trillion company. And Jensen Huang just explained, in his own words, that his customers couldn't have written those orders without him. Isn’t this suspicious?

Jensen Huang just admitted the biggest AI labs can't borrow money like normal companies. So Nvidia signs for them, and they spend it on Nvidia chips. Nvidia reported Wednesday and the numbers are absurd: Revenue of $96.2 billion, up 106%, with net income of $59.7 billion, the most profitable quarter any public company has EVER posted. And Huang just told Fox Business that every chip Nvidia can make next year is already sold. Here's why this matters the most: Huang wrote this himself about his own customers: "Frontier AI labs have extraordinary demand for training and inference compute, but many are growing faster than their balance sheets and long-term credit profiles can support." Then: They "still lack the decades-long infrastructure contracts and investment-grade financing capacity needed to secure the AI factory infrastructure independently." Put simply: His customers can't get the loans. So Nvidia signs for them. There's a compute campus going up in Ohio with OpenAI as the tenant. Nvidia has tied roughly $105 billion in commitments to it. OpenAI's existing and planned commitments now come to about 12 gigawatts of Nvidia compute. CFO Colette Kress told analysts Nvidia will also provide selective credit enhancement for nearly 2 gigawatts of compute at a second frontier lab. She wouldn't say which one. Nvidia put up to $10 billion into Anthropic in November at a valuation near $350 billion, and Anthropic agreed to buy up to a gigawatt of Grace Blackwell and Vera Rubin systems in the same deal. And Nvidia isn't only guaranteeing these companies. It OWNS pieces of them. This week's filing shows $18 billion committed to equity investments for the rest of the fiscal year, and $47.9 billion already sitting in private companies as of late July. Now here's where it gets really insane: Last week, Huang sat on a CNBC set surrounded by six of Wall Street's biggest firms. Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR. They signed a memorandum to mobilise up to $500 billion in outside capital for AI data centres. Nvidia kept the option to backstop up to a quarter of those deals. And Huang used that stage to announce that Nvidia GPUs are now an asset class. Pension and credit funds can now lend against graphics cards the way they lend against office towers. Kress saw the accusation coming and got ahead of it on the earnings call: "We recognise the scale of this support, and we know some will call this circular financing. We see it differently." But look at the two things Huang says about the same companies. On the earnings call he said AI has hit its inflection point, that the tokens are productive and profitable, and that compute is now revenue. But he also said those same labs can't secure investment-grade financing on their own. A business that's inflecting into profit is exactly the business a bank lends to. Banks lend against cash flow every day. But Nvidia‘s guarantee exists because something in that first story isn't landing with the people whose job is pricing risk. Kress does have a real answer to this though. She said the second lab's credit support only complements capacity it already secured on its own, without Nvidia backing it. Vendor financing is also old and legal. Cisco did it and GE built a finance arm on it. Huang's case is that Nvidia understands these businesses better than any lender could, and he says the risk is low and his only regret is not investing more and sooner. He may be completely right. But one thing is certain: Nvidia guarantees the paper. The paper buys the chips. Nvidia books the sale. Then Nvidia tells you the order book is full for a year. That order book is the entire argument for a $5 trillion company. And Jensen Huang just explained, in his own words, that his customers couldn't have written those orders without him. Isn’t this suspicious?

Ricardo

61,238 Aufrufe • vor 3 Tagen

MEET THE NVIDIA KILLER: OpenAI bet $10 BILLION on this company that makes chips 20x faster than Nvidia's. If this plays out as expected, it’s over for Nvidia. Cerebras Systems just locked in 750 megawatts of computing power to OpenAI through 2028. For reference: that's equivalent to the annual power consumption of 600,000 US homes. The deal? Over $10 billion. Here's what nobody understands: Cerebras doesn't make normal chips. Nvidia sells you thousands of tiny chips that you connect together. Cerebras makes ONE chip. A single wafer-scale processor the size of a dinner plate. 900,000 AI cores. 4 trillion transistors. All on one piece of silicon. The result? When OpenAI tested it, Cerebras ran inference 20X FASTER than Nvidia GPUs. That's not incremental improvement. That's a different category of performance. But here's where the story gets wild: Four months ago, Cerebras was a struggling company. Their IPO filing revealed that 87% of their revenue came from ONE customer: G42, a UAE-based AI firm. The US government launched a national security review. G42 had ties to Huawei. Ties to China. The IPO collapsed. Investors panicked. Cerebras withdrew their filing in October 2025. Most startups would've been dead. Instead, Cerebras did the opposite. They raised $1.1 billion at an $8.1 billion valuation. Kicked G42 out of the cap table entirely. Got CFIUS clearance. Then landed the OpenAI deal. Now they're raising ANOTHER $1 billion at a $22 billion valuation. They more than DOUBLED their valuation in 4 months. From near-death to $22 billion. While getting rid of their biggest customer. Why OpenAI chose them: ChatGPT has 900 million weekly users. Sam Altman keeps saying they have a "severe shortage" of compute. They need SPEED, not just power. When you ask ChatGPT a question, there's a loop happening: You send request → model thinks → sends response back Nvidia chips are fast at training models. Cerebras chips are built specifically for inference. For real-time responses. For the exact bottleneck OpenAI is trying to solve. Sachin Katti from OpenAI said it best: "Cerebras adds a dedicated low-latency inference solution to our platform. That means faster responses, more natural interactions, and a stronger foundation to scale real-time AI to many more people." In other words: "We need this to scale ChatGPT." The competitive landscape just shifted: Nvidia announced a $100 billion deal with OpenAI in September. But it's still not finalized. Meanwhile, Cerebras closed their deal before Thanksgiving. And it's ALREADY being deployed. Here's the part that should terrify Nvidia: In December, Nvidia bought Groq for $20 billion. Groq makes fast inference chips. Just like Cerebras. So why would Nvidia spend $20 billion buying a competitor to something they supposedly already dominate? Because they know what's coming. Inference is the new battleground. And Cerebras is winning it. The IPO is coming Q2 2026. After this OpenAI deal, Cerebras now has: ✓ IBM contracts ✓ Department of Energy contracts ✓ OpenAI locked in for 3 years ✓ $22 billion valuation ✓ CFIUS clearance ✓ Zero customer concentration risk They went from 87% revenue dependency on one customer to the most diversified chip company outside Nvidia. In four months. The lesson? Smart money doesn't follow headlines. It follows where the AI leaders are actually spending. OpenAI didn't announce this deal for publicity. They need Cerebras hardware to scale ChatGPT. That's a $10 billion vote of confidence. While everyone's watching Nvidia stock, the real war is happening in inference. And the company with ONE giant chip just beat the company with thousands of tiny ones. What do you think happens when Cerebras IPOs?

MEET THE NVIDIA KILLER: OpenAI bet $10 BILLION on this company that makes chips 20x faster than Nvidia's. If this plays out as expected, it’s over for Nvidia. Cerebras Systems just locked in 750 megawatts of computing power to OpenAI through 2028. For reference: that's equivalent to the annual power consumption of 600,000 US homes. The deal? Over $10 billion. Here's what nobody understands: Cerebras doesn't make normal chips. Nvidia sells you thousands of tiny chips that you connect together. Cerebras makes ONE chip. A single wafer-scale processor the size of a dinner plate. 900,000 AI cores. 4 trillion transistors. All on one piece of silicon. The result? When OpenAI tested it, Cerebras ran inference 20X FASTER than Nvidia GPUs. That's not incremental improvement. That's a different category of performance. But here's where the story gets wild: Four months ago, Cerebras was a struggling company. Their IPO filing revealed that 87% of their revenue came from ONE customer: G42, a UAE-based AI firm. The US government launched a national security review. G42 had ties to Huawei. Ties to China. The IPO collapsed. Investors panicked. Cerebras withdrew their filing in October 2025. Most startups would've been dead. Instead, Cerebras did the opposite. They raised $1.1 billion at an $8.1 billion valuation. Kicked G42 out of the cap table entirely. Got CFIUS clearance. Then landed the OpenAI deal. Now they're raising ANOTHER $1 billion at a $22 billion valuation. They more than DOUBLED their valuation in 4 months. From near-death to $22 billion. While getting rid of their biggest customer. Why OpenAI chose them: ChatGPT has 900 million weekly users. Sam Altman keeps saying they have a "severe shortage" of compute. They need SPEED, not just power. When you ask ChatGPT a question, there's a loop happening: You send request → model thinks → sends response back Nvidia chips are fast at training models. Cerebras chips are built specifically for inference. For real-time responses. For the exact bottleneck OpenAI is trying to solve. Sachin Katti from OpenAI said it best: "Cerebras adds a dedicated low-latency inference solution to our platform. That means faster responses, more natural interactions, and a stronger foundation to scale real-time AI to many more people." In other words: "We need this to scale ChatGPT." The competitive landscape just shifted: Nvidia announced a $100 billion deal with OpenAI in September. But it's still not finalized. Meanwhile, Cerebras closed their deal before Thanksgiving. And it's ALREADY being deployed. Here's the part that should terrify Nvidia: In December, Nvidia bought Groq for $20 billion. Groq makes fast inference chips. Just like Cerebras. So why would Nvidia spend $20 billion buying a competitor to something they supposedly already dominate? Because they know what's coming. Inference is the new battleground. And Cerebras is winning it. The IPO is coming Q2 2026. After this OpenAI deal, Cerebras now has: ✓ IBM contracts ✓ Department of Energy contracts ✓ OpenAI locked in for 3 years ✓ $22 billion valuation ✓ CFIUS clearance ✓ Zero customer concentration risk They went from 87% revenue dependency on one customer to the most diversified chip company outside Nvidia. In four months. The lesson? Smart money doesn't follow headlines. It follows where the AI leaders are actually spending. OpenAI didn't announce this deal for publicity. They need Cerebras hardware to scale ChatGPT. That's a $10 billion vote of confidence. While everyone's watching Nvidia stock, the real war is happening in inference. And the company with ONE giant chip just beat the company with thousands of tiny ones. What do you think happens when Cerebras IPOs?

Ricardo

28,088 Aufrufe • vor 7 Monaten

Kamala Harris: It is about reminding folks that we refuse to kneel at the foot of a tyrant. That's not what we do. We stand for the principles upon which our nation was founded. We believe in the Constitution. We believe in the power of the vote, and we are prepared when necessary to fight fire with fire.

Kamala Harris: It is about reminding folks that we refuse to kneel at the foot of a tyrant. That's not what we do. We stand for the principles upon which our nation was founded. We believe in the Constitution. We believe in the power of the vote, and we are prepared when necessary to fight fire with fire.

Acyn

71,541 Aufrufe • vor 10 Monaten

Hov breaking his own record in back-to-back nights 🐐 Jay-Z’s ‘The Blueprint’ show set the record for most tickets ever sold for a concert at Yankee Stadium—selling a total of 45,832. It broke Hov’s record set at the ‘Reasonable Doubt’ show on Friday, which sold 44,916 tickets.

Hov breaking his own record in back-to-back nights 🐐 Jay-Z’s ‘The Blueprint’ show set the record for most tickets ever sold for a concert at Yankee Stadium—selling a total of 45,832. It broke Hov’s record set at the ‘Reasonable Doubt’ show on Friday, which sold 44,916 tickets.

Complex Music

187,200 Aufrufe • vor 1 Monat

Kamala Harris: “We refuse to kneel at the foot of a tyrant. That’s not what we do. We stand for the principals upon which our nation was founded. We believe in the Constitution. We believe in the power of the vote. And we are prepared, when necessary, to fight fire with fire”

Kamala Harris: “We refuse to kneel at the foot of a tyrant. That’s not what we do. We stand for the principals upon which our nation was founded. We believe in the Constitution. We believe in the power of the vote. And we are prepared, when necessary, to fight fire with fire”

Marco Foster

56,143 Aufrufe • vor 10 Monaten

AOC: “America was founded in revolt of British aristocracy. The American Revolution was against the billionaires of their time. It’s actually the most American thing in the world for us to be fighting for the working class. It’s actually patently un-American to transform our country into a place of kings and landed gentry”

AOC: “America was founded in revolt of British aristocracy. The American Revolution was against the billionaires of their time. It’s actually the most American thing in the world for us to be fighting for the working class. It’s actually patently un-American to transform our country into a place of kings and landed gentry”

Marco Foster

801,195 Aufrufe • vor 3 Monaten

Just to illustrate the stomach-turning horrors of the corporate conditions for these dogs -- and this is all *prior to* the gruesome experiments into which these dogs are sold -- here's a video report produced by me and Leighton 明 Woodhouse: on the facilities:

Just to illustrate the stomach-turning horrors of the corporate conditions for these dogs -- and this is all prior to the gruesome experiments into which these dogs are sold -- here's a video report produced by me and Leighton 明 Woodhouse: on the facilities:

Glenn Greenwald

22,272 Aufrufe • vor 4 Monaten

Tushar Jain explains why Zcash represents crypto's original vision “I think a lot of people in the industry lost their direction a little bit. You have to look back at the principles the industry was founded on and it was founded on self-sovereignty” “Now the big thing the industry is saying is, ‘Please regulate us. Please come and issue centralized assets on our chains’” “I think Bitcoin feels pretty captured at this point. It's BlackRock, it's MicroStrategy. It's institutionally captured” “To me, Zcash is the ideals on which the industry was founded”

Tushar Jain explains why Zcash represents crypto's original vision “I think a lot of people in the industry lost their direction a little bit. You have to look back at the principles the industry was founded on and it was founded on self-sovereignty” “Now the big thing the industry is saying is, ‘Please regulate us. Please come and issue centralized assets on our chains’” “I think Bitcoin feels pretty captured at this point. It's BlackRock, it's MicroStrategy. It's institutionally captured” “To me, Zcash is the ideals on which the industry was founded”

genzcash

12,956 Aufrufe • vor 1 Monat