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Compute Wars: OpenAI vs Anthopic. Why was Opus 4.5 such a breakthrough? Anthropic got lots more compute from AWS Madison and New Carlisle sites likely more than doubling their capacity. This got Anthropic got close to OpenAI's total capacity, and probably much higher effective capacity available for new model...

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Peter Gostev

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157,413 görüntüleme • 2 ay önce •via X (Twitter)

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Dylan on why Anthropic leading on models doesn't mean OpenAI loses. Even the tier 2 and 3 labs will sell out of tokens: "Everyone's like Anthropic won. They had Mythos, Opus 4.7 and their revenue is adding $10 billion a month all before OpenAI's alleged Spud release. So clearly Anthropic is in the lead and OpenAI is cooked. Anthropic has such bounds on compute, they can only grow it so fast. Dario used to gloat about how OpenAI was being too aggressive on compute and Anthropic was more sensible in their scaling. Now Anthropic is like I wish we had a lot more compute. OpenAI just raised a ton of money to get incremental compute in addition to the irresponsible levels of compute that they were buying. By the end of the year, let's say a 4.6 Opus tier model, the economy would spend $100 billion on. Anthropic won't have enough compute to do that. And presumably OpenAI and Google will hit that tier soon. Anthropic may get to charge 70%+ gross margins but if OpenAI hits it next, they charge 50% gross margins. They still get all of this incremental demand. There is such demand for these tokens and such limitations on compute. It's pretty clear even the tier 2 or tier 3 lab are going to be sold out of tokens. The economic value that the best model can deliver is growing faster than our ability to actually serve those tokens to people via the infrastructure."
2:33

Dylan on why Anthropic leading on models doesn't mean OpenAI loses. Even the tier 2 and 3 labs will sell out of tokens: "Everyone's like Anthropic won. They had Mythos, Opus 4.7 and their revenue is adding $10 billion a month all before OpenAI's alleged Spud release. So clearly Anthropic is in the lead and OpenAI is cooked. Anthropic has such bounds on compute, they can only grow it so fast. Dario used to gloat about how OpenAI was being too aggressive on compute and Anthropic was more sensible in their scaling. Now Anthropic is like I wish we had a lot more compute. OpenAI just raised a ton of money to get incremental compute in addition to the irresponsible levels of compute that they were buying. By the end of the year, let's say a 4.6 Opus tier model, the economy would spend $100 billion on. Anthropic won't have enough compute to do that. And presumably OpenAI and Google will hit that tier soon. Anthropic may get to charge 70%+ gross margins but if OpenAI hits it next, they charge 50% gross margins. They still get all of this incremental demand. There is such demand for these tokens and such limitations on compute. It's pretty clear even the tier 2 or tier 3 lab are going to be sold out of tokens. The economic value that the best model can deliver is growing faster than our ability to actually serve those tokens to people via the infrastructure."

Patrick OShaughnessy

294,850 görüntüleme • 1 ay önce

Sam Altman: “By the end 2028, more of the worlds intellectual capacity could reside inside of data centers than outside of them” They are going to need so much energy and compute for this Pretty crazy statement from the OpenAI CEO
0:38

Sam Altman: “By the end 2028, more of the worlds intellectual capacity could reside inside of data centers than outside of them” They are going to need so much energy and compute for this Pretty crazy statement from the OpenAI CEO

Small Cap Snipa

12,927 görüntüleme • 3 ay önce

OpenAI President, Greg Brockman: We are moving to a world where GDP growth is driven by the amount of compute available openAI has tripled its compute annually, yet remains so compute-constrained "every time we want to launch something new, we fight over compute"
1:17

OpenAI President, Greg Brockman: We are moving to a world where GDP growth is driven by the amount of compute available openAI has tripled its compute annually, yet remains so compute-constrained "every time we want to launch something new, we fight over compute"

Haider.

64,614 görüntüleme • 5 ay önce

"Anthropic is making great money. OpenAI is making great money. If they could have twice as much compute, the revenues would go up 4 times as much. These guys are so compute constrained, and the demand is so incredibly great." ~ Jensen Huang on CNBC
21:57

"Anthropic is making great money. OpenAI is making great money. If they could have twice as much compute, the revenues would go up 4 times as much. These guys are so compute constrained, and the demand is so incredibly great." ~ Jensen Huang on CNBC

Rohan Paul

451,268 görüntüleme • 4 ay önce

The worldwide quantum computer is coming Our mission: quantum compute for everyone We connect providers with excess capacity to the people who need it. Trustless, 20x faster, and 100x more energy efficient than classical compute. Quest to earn QUIP 👇
0:59

The worldwide quantum computer is coming Our mission: quantum compute for everyone We connect providers with excess capacity to the people who need it. Trustless, 20x faster, and 100x more energy efficient than classical compute. Quest to earn QUIP 👇

Quip Network

271,508 görüntüleme • 4 ay önce

.Dylan Patel thinks Anthropic will get to 5–6 GW by year end. But at a far higher cost than it would have had to pay if it had gone crazy on compute commitments early like OpenAI did. Ant will get the compute either through cloud partners like Bedrock and Vertex who take ~50% gross margin on revenue, or shorter-term deals where rates have climbed well above what long-term contracts locked in a year or two ago cost. They’ll probably also have to destroy demand by pushing up model prices.
2:16

.Dylan Patel thinks Anthropic will get to 5–6 GW by year end. But at a far higher cost than it would have had to pay if it had gone crazy on compute commitments early like OpenAI did. Ant will get the compute either through cloud partners like Bedrock and Vertex who take ~50% gross margin on revenue, or shorter-term deals where rates have climbed well above what long-term contracts locked in a year or two ago cost. They’ll probably also have to destroy demand by pushing up model prices.

Dwarkesh Patel

55,447 görüntüleme • 3 ay önce

Anthropic is in trouble and nobody wants to say it out loud. Opus 4.7 is the first Claude model people think is worse, usage limits are hitting fast, compute is running thin, and Anthropic's best model still isn't out. GPT-5.5 just dropped today, OpenAI found their window. This 32 minute video is worth more than the next episode of whatever you're watching on Netflix tonight.
32:30

Anthropic is in trouble and nobody wants to say it out loud. Opus 4.7 is the first Claude model people think is worse, usage limits are hitting fast, compute is running thin, and Anthropic's best model still isn't out. GPT-5.5 just dropped today, OpenAI found their window. This 32 minute video is worth more than the next episode of whatever you're watching on Netflix tonight.

Defileo🔮

131,838 görüntüleme • 1 ay önce

Chamath Palihapitiya, one of the most connected investors in tech and his warning is the clearest framing of the AI compute crisis anyone has put into words. "It is a five alarm fire for them. They need to have land, power, shell." He's talking about Anthropic and OpenAI and the threat he's describing is called the Friendster effect. Friendster was the dominant social network before MySpace and Facebook and it didn't lose because it had a bad product but rather it lost because it couldn't keep the site up. Demand outpaced infrastructure, the experience degraded, and users left for one that actually worked. Chamath's argument is that OpenAI and Anthropic are approaching exactly that moment. The numbers are already showing it, Anthropic is growing so fast that it had to cut Claude's thinking depth during peak hours, cap agentic sessions, and test removing Claude Code from its $20 plan entirely. GitHub Copilot paused new signups, paying enterprise customers are hitting usage walls they've never seen before. Dario Amodei himself admitted there is "no hedge on earth" against the risk of over-purchasing compute meaning he's deliberately staying lean on capacity, even as the demand wall approaches. The core problem is structural, OpenAI and Anthropic grew up renting capacity from hyperscalers AWS, Azure, Google Cloud. That was fine when they were small but now they're so large that dependency is a strategic liability. Every token they sell runs on someone else's infrastructure and every capacity decision belongs to someone else. And when demand spikes faster than anyone planned, there's nothing they can do in real time except throttle. Building your own infrastructure takes 18 to 24 months minimum, you need to acquire land, secure power, construct shell and none of that happens fast. That's why Google's $40 billion commitment to Anthropic this week is about more than just money but rather about securing the land, power, and infrastructure that Anthropic needs to not become Friendster. Whoever controls the compute controls the frontier and right now, the AI labs with the best products are the most dependent on infrastructure they don't own.
0:31

Chamath Palihapitiya, one of the most connected investors in tech and his warning is the clearest framing of the AI compute crisis anyone has put into words. "It is a five alarm fire for them. They need to have land, power, shell." He's talking about Anthropic and OpenAI and the threat he's describing is called the Friendster effect. Friendster was the dominant social network before MySpace and Facebook and it didn't lose because it had a bad product but rather it lost because it couldn't keep the site up. Demand outpaced infrastructure, the experience degraded, and users left for one that actually worked. Chamath's argument is that OpenAI and Anthropic are approaching exactly that moment. The numbers are already showing it, Anthropic is growing so fast that it had to cut Claude's thinking depth during peak hours, cap agentic sessions, and test removing Claude Code from its $20 plan entirely. GitHub Copilot paused new signups, paying enterprise customers are hitting usage walls they've never seen before. Dario Amodei himself admitted there is "no hedge on earth" against the risk of over-purchasing compute meaning he's deliberately staying lean on capacity, even as the demand wall approaches. The core problem is structural, OpenAI and Anthropic grew up renting capacity from hyperscalers AWS, Azure, Google Cloud. That was fine when they were small but now they're so large that dependency is a strategic liability. Every token they sell runs on someone else's infrastructure and every capacity decision belongs to someone else. And when demand spikes faster than anyone planned, there's nothing they can do in real time except throttle. Building your own infrastructure takes 18 to 24 months minimum, you need to acquire land, secure power, construct shell and none of that happens fast. That's why Google's $40 billion commitment to Anthropic this week is about more than just money but rather about securing the land, power, and infrastructure that Anthropic needs to not become Friendster. Whoever controls the compute controls the frontier and right now, the AI labs with the best products are the most dependent on infrastructure they don't own.

Milk Road AI

260,300 görüntüleme • 1 ay önce

Our Compute Agent (Operator) Got Much Faster!! It's about 3- 4x faster. In this example, it finds the cheapest flights from London to NYC and emails you the details. In all fairness, we are still 2x slower than OpenAI. We will continue to make it faster and more agentic. The next update will be later this week.
0:41

Our Compute Agent (Operator) Got Much Faster!! It's about 3- 4x faster. In this example, it finds the cheapest flights from London to NYC and emails you the details. In all fairness, we are still 2x slower than OpenAI. We will continue to make it faster and more agentic. The next update will be later this week.

Bindu Reddy

20,716 görüntüleme • 1 yıl önce

Frontier AI data center capacity, based on data collected by Epoch AI. It doesn't include every single one, as they focus on the largest ones. Few things stand out: - 2026 will have a huge amount of cpacity come online - Anthropic will lead at some early points in 2026 - 2027 onwards OpenAI has the most projected capacity at the moment, by far
0:34

Frontier AI data center capacity, based on data collected by Epoch AI. It doesn't include every single one, as they focus on the largest ones. Few things stand out: - 2026 will have a huge amount of cpacity come online - Anthropic will lead at some early points in 2026 - 2027 onwards OpenAI has the most projected capacity at the moment, by far

Peter Gostev

134,649 görüntüleme • 5 ay önce

OpenAI CFO Sarah Friar: "In 2026, if you want to buy more compute, good luck to you. Tell me because I dont know where else to find it." Jason: "Elon has some." Rubbing in the fact that Elon sold compute to Anthropic just a few weeks ago just to get back at Sam Altman
1:37

OpenAI CFO Sarah Friar: "In 2026, if you want to buy more compute, good luck to you. Tell me because I dont know where else to find it." Jason: "Elon has some." Rubbing in the fact that Elon sold compute to Anthropic just a few weeks ago just to get back at Sam Altman

Boring_Business

384,018 görüntüleme • 14 gün önce

Greg Brockman on AI-designed chips and the future of compute >openai used their own models to design their chips, faster and probably better than human engineers >in the future everyone would have an agent that works 24/7 for them. Restriction: compute, at the moment
2:12

Greg Brockman on AI-designed chips and the future of compute >openai used their own models to design their chips, faster and probably better than human engineers >in the future everyone would have an agent that works 24/7 for them. Restriction: compute, at the moment

Chubby♨️

209,854 görüntüleme • 8 ay önce

Compute enabled our first image generation launch (and a +32% jump in WAU over the following weeks) as well as our latest image generation launch yesterday. We have a lot more coming… and need a lot more compute.
1:13

Compute enabled our first image generation launch (and a +32% jump in WAU over the following weeks) as well as our latest image generation launch yesterday. We have a lot more coming… and need a lot more compute.

OpenAI

777,726 görüntüleme • 6 ay önce

Compute is the scarcest resource in AI, and demand keeps growing. On the OpenAI Podcast, our CFO Sarah Friar and Khosla Ventures founder Vinod Khosla talk to host Andrew Mayne about the demand for compute and how we get the benefits of AI to more people.
49:41

Compute is the scarcest resource in AI, and demand keeps growing. On the OpenAI Podcast, our CFO Sarah Friar and Khosla Ventures founder Vinod Khosla talk to host Andrew Mayne about the demand for compute and how we get the benefits of AI to more people.

OpenAI

222,542 görüntüleme • 4 ay önce

OpenAI CFO Sarah Friar: The business case for AI is simple: more compute, more revenue OpenAI scaled from 200 megawatts to 2 gigawatts, and ARR climbed from $2 billion to over $20 billion, yet we remain absolutely constrained on compute "the signal from everywhere is real... we are in a paradigm shift"
1:54

OpenAI CFO Sarah Friar: The business case for AI is simple: more compute, more revenue OpenAI scaled from 200 megawatts to 2 gigawatts, and ARR climbed from $2 billion to over $20 billion, yet we remain absolutely constrained on compute "the signal from everywhere is real... we are in a paradigm shift"

Haider.

18,109 görüntüleme • 4 ay önce

Here’s my BBC interview: I went over how the OpenAI deal validates $AMZN AWS GenAI capabilities & shared my takeaway from the $PLTR thesis post-earnings. Every story you see about $GOOGL, $MSFT, $META, $ORCL or OpenAI building new compute factories connects directly to why Palantir can report a Rule of 40 score of 114. The trillions in AI infrastructure CapEx are creating raw capacity but capacity alone doesn’t create productivity and Palantir sits exactly at that conversion point. So yet it trades rich but it’s the only pure play with leverage to every dollar the hyperscalers spend. You’re not paying for today’s revenue but you’re paying for the right to own the switchboard that will orchestrate trillions in future AI infrastructure.
3:13

Here’s my BBC interview: I went over how the OpenAI deal validates $AMZN AWS GenAI capabilities & shared my takeaway from the $PLTR thesis post-earnings. Every story you see about $GOOGL, $MSFT, $META, $ORCL or OpenAI building new compute factories connects directly to why Palantir can report a Rule of 40 score of 114. The trillions in AI infrastructure CapEx are creating raw capacity but capacity alone doesn’t create productivity and Palantir sits exactly at that conversion point. So yet it trades rich but it’s the only pure play with leverage to every dollar the hyperscalers spend. You’re not paying for today’s revenue but you’re paying for the right to own the switchboard that will orchestrate trillions in future AI infrastructure.

Shay Boloor

62,985 görüntüleme • 7 ay önce

Jensen: if your AI is better than the attacker's AI, you're fine. A small malicious team is never going to have more compute than OpenAI/Anthropic and certainly not more than a country. Hope Jensen is right 🤞
1:14

Jensen: if your AI is better than the attacker's AI, you're fine. A small malicious team is never going to have more compute than OpenAI/Anthropic and certainly not more than a country. Hope Jensen is right 🤞

Matthew Berman

51,502 görüntüleme • 1 ay önce

The internet has a Trust Problem. We’re facing a Compute Capacity Crisis. Centralized solutions? Fork that. It’s time for a new model. One built for agents, owned by users, and powered by NEAR.
0:56

The internet has a Trust Problem. We’re facing a Compute Capacity Crisis. Centralized solutions? Fork that. It’s time for a new model. One built for agents, owned by users, and powered by NEAR.

NEAR Protocol

16,520 görüntüleme • 10 ay önce

This Paper from Google DeepMind is a landmark one. 📚 "Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters" It may have contributed to the 01 Model from OpenAI or the principle may have been long known to OpenAI. The paper basically says - Searching at inference will give you great final result from the LLM. Now from Strawberry model is making use of inference time compute strategies using Search techniques over the response space to improve reasoning. ------ The Podcast is generated with Google's illuminate, the tool trained on AI & science-related Arxiv papers.
7:19

This Paper from Google DeepMind is a landmark one. 📚 "Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters" It may have contributed to the 01 Model from OpenAI or the principle may have been long known to OpenAI. The paper basically says - Searching at inference will give you great final result from the LLM. Now from Strawberry model is making use of inference time compute strategies using Search techniques over the response space to improve reasoning. ------ The Podcast is generated with Google's illuminate, the tool trained on AI & science-related Arxiv papers.

Rohan Paul

48,980 görüntüleme • 1 yıl önce