Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

After Kimi K3 became a huge hit, Washington is once again rolling out the same old script: China must have “distilled” American models. China’s answer was basically: our AI has nothing to do with your political hysteria. Stop dragging us into your protectionist theater. China builds AI around openness,...

OopsGuess's profile picture

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

56,424 subscribers

15,630 Aufrufe • vor 1 Monat •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

Jensen Huang says it has “largely conceded” China’s AI chip market to Huawei Nvidia was not rejected because China “hates” Nvidia. It was pushed out because Washington turned chips into a leash. China learned the lesson very clearly: You cannot build AI sovereignty on hardware that your geopolitical rival can revoke with one export-control memo. Jensen Huang can be friendly. Nvidia can be excellent. Chinese demand can be huge. None of that changes the strategic reality. If the neck of China’s AI industry depends on an American-controlled chip supply, then it is not an industry. It is a hostage. So China did what any serious civilization-state would do: It built alternatives. It endured the pain. It let Huawei grow into the space Washington forced open. Now Nvidia says it has “largely conceded” China’s AI chip market to Huawei. That is not China closing a door. That is America sawing off the bridge, then acting surprised when China built its own road.
2:06

Jensen Huang says it has “largely conceded” China’s AI chip market to Huawei Nvidia was not rejected because China “hates” Nvidia. It was pushed out because Washington turned chips into a leash. China learned the lesson very clearly: You cannot build AI sovereignty on hardware that your geopolitical rival can revoke with one export-control memo. Jensen Huang can be friendly. Nvidia can be excellent. Chinese demand can be huge. None of that changes the strategic reality. If the neck of China’s AI industry depends on an American-controlled chip supply, then it is not an industry. It is a hostage. So China did what any serious civilization-state would do: It built alternatives. It endured the pain. It let Huawei grow into the space Washington forced open. Now Nvidia says it has “largely conceded” China’s AI chip market to Huawei. That is not China closing a door. That is America sawing off the bridge, then acting surprised when China built its own road.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

235,419 Aufrufe • vor 3 Monaten

David Sacks: Anthropic Is Trying to Crush Open Source AI and the American Developers Who Use It David Sacks: “I know people don't have a lot of sympathy for Chinese companies, that's fine. I'm not defending Chinese companies. I'm defending American developers who need to be able to use everything in the public domain. And let me give you an example. Cursor rolled out its new product, Composer 2. They were able to post-train that model using Kimi K2.5 on their own proprietary coding data. They started with a Chinese open source model, and then they used their own data, and they came up with a new derivative product. This is the way that open source works. You take things that are in the public domain, you fork them, you make them your own. And by the way, once it's in the public domain, it's not a Chinese model anymore. No data is going back to China, nothing's going back to China. An American company has taken open source contributions in the public domain, made it their own, and then developed their own model. And if you say that American companies can't do that, or that somehow it's tainted with IP theft, you are basically going to put a dagger through the heart of the entire American open source ecosystem. And that is exactly what Anthropic wants, because they do not want to have the competition.”
0:59

David Sacks: Anthropic Is Trying to Crush Open Source AI and the American Developers Who Use It David Sacks: “I know people don't have a lot of sympathy for Chinese companies, that's fine. I'm not defending Chinese companies. I'm defending American developers who need to be able to use everything in the public domain. And let me give you an example. Cursor rolled out its new product, Composer 2. They were able to post-train that model using Kimi K2.5 on their own proprietary coding data. They started with a Chinese open source model, and then they used their own data, and they came up with a new derivative product. This is the way that open source works. You take things that are in the public domain, you fork them, you make them your own. And by the way, once it's in the public domain, it's not a Chinese model anymore. No data is going back to China, nothing's going back to China. An American company has taken open source contributions in the public domain, made it their own, and then developed their own model. And if you say that American companies can't do that, or that somehow it's tainted with IP theft, you are basically going to put a dagger through the heart of the entire American open source ecosystem. And that is exactly what Anthropic wants, because they do not want to have the competition.”

The All-In Podcast

277,908 Aufrufe • vor 28 Tagen

Alex Karp went on TV and said his enterprise customers are done letting AI companies quietly steal the alpha out of their business, and the CEO of Together AI explained on CNBC exactly how that theft works. Karp said his customers are livid. They feel they pay for tokens that create nothing while handing over the secret sauce of their own company. Then Vipul Ved Prakash laid out the mechanism. Every time you send your data to a company with very smart models, you hand them the recipe to rebuild what you do. Your data is the thing that makes you money. And you are pushing it straight into a competitor's system. The smarter the models get, the more they learn from what you feed them. This is why companies are moving to open models, and it was never really about price. You can download an open model, run it inside your own walls, and never let your data leave the building. It scores 81 against the top closed model's 85, and runs up to sixty times cheaper. Half the Fortune 500 is already running open models from Hugging Face. The story was that the labs win because they own the best models. The companies paying them just realized they owned the best data the whole time.
0:45

Alex Karp went on TV and said his enterprise customers are done letting AI companies quietly steal the alpha out of their business, and the CEO of Together AI explained on CNBC exactly how that theft works. Karp said his customers are livid. They feel they pay for tokens that create nothing while handing over the secret sauce of their own company. Then Vipul Ved Prakash laid out the mechanism. Every time you send your data to a company with very smart models, you hand them the recipe to rebuild what you do. Your data is the thing that makes you money. And you are pushing it straight into a competitor's system. The smarter the models get, the more they learn from what you feed them. This is why companies are moving to open models, and it was never really about price. You can download an open model, run it inside your own walls, and never let your data leave the building. It scores 81 against the top closed model's 85, and runs up to sixty times cheaper. Half the Fortune 500 is already running open models from Hugging Face. The story was that the labs win because they own the best models. The companies paying them just realized they owned the best data the whole time.

Ihtesham Ali

17,433 Aufrufe • vor 1 Monat

“don’t train your own model” is common ai advice. it's wrong. your token bill's the proof. today, we’re excited to launch castform into open preview. castform is the easiest way for you to train your own model, on your own data. open-weights models are performant and much cheaper. when trained on your task & proprietary data, they beat closed models. the thing standing between you and that was weeks of plumbing & years of ml expertise. with castform, model training is as simple as prompt engineering. castform bring your agent traces or raw corpora. castform turns it into training data, picks the right algorithmic recipes, manages gpus, and gives you an ide to watch and chat with your model as it learns. see what you can build with castform👇
2:23

“don’t train your own model” is common ai advice. it's wrong. your token bill's the proof. today, we’re excited to launch castform into open preview. castform is the easiest way for you to train your own model, on your own data. open-weights models are performant and much cheaper. when trained on your task & proprietary data, they beat closed models. the thing standing between you and that was weeks of plumbing & years of ml expertise. with castform, model training is as simple as prompt engineering. castform bring your agent traces or raw corpora. castform turns it into training data, picks the right algorithmic recipes, manages gpus, and gives you an ide to watch and chat with your model as it learns. see what you can build with castform👇

girish

459,443 Aufrufe • vor 2 Monaten

Microsoft just betrayed OpenAI and Anthropic, the two companies it helped build. And it could break the entire AI trade... Here's what happened: Inside Excel and Outlook, two of the most used business apps on Earth, Microsoft has started routing tens of thousands of AI requests every week to its own in-house models instead of OpenAI and Anthropic. Microsoft's own AI chief, Mustafa Suleyman, said himself: "We pay a lot of money to Anthropic, so our goal is to reduce and ultimately ELIMINATE that cost." This is the company that poured $13 billion into OpenAI and effectively created the modern AI industry, and it just decided the most advanced models on the market are NOT worth paying for. And here's the thing... Microsoft is not just ripping out OpenAI everywhere - it is being surgical about it. The hardest and rarest tasks can still go to OpenAI or Anthropic. What Microsoft is taking back is the boring, high-volume work, like the email replies, the thread summaries, and the simple spreadsheet formulas. Why does that matter so much? Because that boring, repetitive work is where the actual money lives. The frontier labs assumed businesses would push BILLIONS of these tiny requests through expensive models forever. That endless river of tokens is the entire reason OpenAI and Anthropic are valued in the hundreds of billions of dollars. Microsoft looked at that river, decided it was massively overpaying, and rerouted it to models it owns outright. So the single biggest customer in the industry just walked off with the most profitable part of the business. And it is not only Microsoft: That same week, CNBC reported that American companies have been escaping to Chinese AI models to dodge rising US prices. Chinese models now handle more than 30% of US companies' AI usage on one major platform, peaking at 46%, up from an average of 11% a year earlier. They cost 60 to 90% less, and on some benchmarks they land within a single point of the best American model. One US startup moved ALL of its AI traffic off Claude and onto China's DeepSeek, and expects to save millions. Meanwhile Meta just admitted it has "excess" AI compute it wants to sell, becoming the first giant to concede it built far too much. Do you see the pattern forming? For two years, the entire AI story rested on one assumption: Every company on Earth would happily pay premium prices for the best model, forever. That assumption literally died in a single week. And the market noticed. More than a trillion dollars has been wiped off AI and chip stocks in a matter of days, as Wall Street finally started asking whether all of this spending will ever pay for itself. What this means for OpenAI and Anthropic: Their models are extraordinary, and it may not matter because their own biggest customers have decided they do not NEED the best model in the world to answer an email, and "good enough" now costs a fraction of the price. When even Microsoft refuses to pay full price for AI, the real question becomes who exactly IS left to pay it. What do you think?
1:05

Microsoft just betrayed OpenAI and Anthropic, the two companies it helped build. And it could break the entire AI trade... Here's what happened: Inside Excel and Outlook, two of the most used business apps on Earth, Microsoft has started routing tens of thousands of AI requests every week to its own in-house models instead of OpenAI and Anthropic. Microsoft's own AI chief, Mustafa Suleyman, said himself: "We pay a lot of money to Anthropic, so our goal is to reduce and ultimately ELIMINATE that cost." This is the company that poured $13 billion into OpenAI and effectively created the modern AI industry, and it just decided the most advanced models on the market are NOT worth paying for. And here's the thing... Microsoft is not just ripping out OpenAI everywhere - it is being surgical about it. The hardest and rarest tasks can still go to OpenAI or Anthropic. What Microsoft is taking back is the boring, high-volume work, like the email replies, the thread summaries, and the simple spreadsheet formulas. Why does that matter so much? Because that boring, repetitive work is where the actual money lives. The frontier labs assumed businesses would push BILLIONS of these tiny requests through expensive models forever. That endless river of tokens is the entire reason OpenAI and Anthropic are valued in the hundreds of billions of dollars. Microsoft looked at that river, decided it was massively overpaying, and rerouted it to models it owns outright. So the single biggest customer in the industry just walked off with the most profitable part of the business. And it is not only Microsoft: That same week, CNBC reported that American companies have been escaping to Chinese AI models to dodge rising US prices. Chinese models now handle more than 30% of US companies' AI usage on one major platform, peaking at 46%, up from an average of 11% a year earlier. They cost 60 to 90% less, and on some benchmarks they land within a single point of the best American model. One US startup moved ALL of its AI traffic off Claude and onto China's DeepSeek, and expects to save millions. Meanwhile Meta just admitted it has "excess" AI compute it wants to sell, becoming the first giant to concede it built far too much. Do you see the pattern forming? For two years, the entire AI story rested on one assumption: Every company on Earth would happily pay premium prices for the best model, forever. That assumption literally died in a single week. And the market noticed. More than a trillion dollars has been wiped off AI and chip stocks in a matter of days, as Wall Street finally started asking whether all of this spending will ever pay for itself. What this means for OpenAI and Anthropic: Their models are extraordinary, and it may not matter because their own biggest customers have decided they do not NEED the best model in the world to answer an email, and "good enough" now costs a fraction of the price. When even Microsoft refuses to pay full price for AI, the real question becomes who exactly IS left to pay it. What do you think?

Ricardo

92,971 Aufrufe • vor 1 Monat

Your home is about to become an AI data center and pay off your mortgage This is not a theory. It is already happening. Nvidia partnered with homebuilders to install AI hardware directly into new homes. A white box on the wall. Internet. Power outlet. It processes AI workloads for companies around the world. You do nothing. It just runs 24/7. Homeowners get paid a fixed amount every single month. Estimates put it at $2,000 to $3,000 straight into your account. That is $36,000 a year just for a box on your wall. These guys broke down exactly why this is massive, who is behind it and how regular homeowners get in. Suburbs are quietly becoming the new AI infrastructure. And the people who got in early are already getting paid. Watch the full video. All the alpha and everything you need to know is in there.
13:21

Your home is about to become an AI data center and pay off your mortgage This is not a theory. It is already happening. Nvidia partnered with homebuilders to install AI hardware directly into new homes. A white box on the wall. Internet. Power outlet. It processes AI workloads for companies around the world. You do nothing. It just runs 24/7. Homeowners get paid a fixed amount every single month. Estimates put it at $2,000 to $3,000 straight into your account. That is $36,000 a year just for a box on your wall. These guys broke down exactly why this is massive, who is behind it and how regular homeowners get in. Suburbs are quietly becoming the new AI infrastructure. And the people who got in early are already getting paid. Watch the full video. All the alpha and everything you need to know is in there.

winkle.

315,269 Aufrufe • vor 2 Monaten

#WATCH | Idukki, Kerala | Interacting with students of Marian College Kuttikkanam (Autonomous), Lok Sabha LoP Rahul Gandhi says, "Actually India is not successful at AI... There are two players in the AI game. The United States and China. India, unfortunately, whether it is in robotics, or Ai, or modern technology, is not really a major player. Certainly, when compared to the US or China. You saw that in the AI Summit itself, a Chinese robot was masquerading as an Indian robot. If you want to be powerful at AI, you have to control your own data... The US deal that has just been done by the Prime Minister has handed over our entire data to the United States... We have damaged our potential in AI tremendously over the last couple of weeks... Jobs in the services and software industry, which were the mainstay of our country, are going to be wiped out by AI. I am worried that a transition is taking place on the data, manufacturing, and mobility front, and we are just looking..." (Source: Marian College Kuttikkanam Official)
6:29

#WATCH | Idukki, Kerala | Interacting with students of Marian College Kuttikkanam (Autonomous), Lok Sabha LoP Rahul Gandhi says, "Actually India is not successful at AI... There are two players in the AI game. The United States and China. India, unfortunately, whether it is in robotics, or Ai, or modern technology, is not really a major player. Certainly, when compared to the US or China. You saw that in the AI Summit itself, a Chinese robot was masquerading as an Indian robot. If you want to be powerful at AI, you have to control your own data... The US deal that has just been done by the Prime Minister has handed over our entire data to the United States... We have damaged our potential in AI tremendously over the last couple of weeks... Jobs in the services and software industry, which were the mainstay of our country, are going to be wiped out by AI. I am worried that a transition is taking place on the data, manufacturing, and mobility front, and we are just looking..." (Source: Marian College Kuttikkanam Official)

ANI

133,148 Aufrufe • vor 5 Monaten

China is planning to spend around 2 trillion yuan ($295 billion) over the next five years to build data centers across the country At least 80% of all AI chips must come from domestic suppliers, primarily Huawei. Nvidia and AMD are locked out by design. Nvidia once held a 95% market share in China's AI market. Now? Zero. America did not lose China’s AI chip market because China “closed its doors,” but because America chose to weaponize chips, sanctions, export controls, entity lists, national security hysteria, and technological apartheid against its own largest customer. Washington took the world’s largest chip consumption market — a market that could have funded American semiconductor dominance for another generation — and taught it the most important lesson: Never let your future depend on a supplier that can be turned off by one paranoid empire. So China did what any serious civilization-state would do. It localized. It substituted. It built its own stack. It turned a customer relationship into a sovereignty project. And the same people who tried to choke Huawei are watching Huawei become the backbone of China’s AI infrastructure. This is a textbook own goal. America thought it was denying​ China the future. In reality, it compelled​ China to architect​ the future beyond​ America.
1:02

China is planning to spend around 2 trillion yuan ($295 billion) over the next five years to build data centers across the country At least 80% of all AI chips must come from domestic suppliers, primarily Huawei. Nvidia and AMD are locked out by design. Nvidia once held a 95% market share in China's AI market. Now? Zero. America did not lose China’s AI chip market because China “closed its doors,” but because America chose to weaponize chips, sanctions, export controls, entity lists, national security hysteria, and technological apartheid against its own largest customer. Washington took the world’s largest chip consumption market — a market that could have funded American semiconductor dominance for another generation — and taught it the most important lesson: Never let your future depend on a supplier that can be turned off by one paranoid empire. So China did what any serious civilization-state would do. It localized. It substituted. It built its own stack. It turned a customer relationship into a sovereignty project. And the same people who tried to choke Huawei are watching Huawei become the backbone of China’s AI infrastructure. This is a textbook own goal. America thought it was denying​ China the future. In reality, it compelled​ China to architect​ the future beyond​ America.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

36,839 Aufrufe • vor 2 Monaten

Japan and the Philippines can hold all the “maritime delimitation talks” they want. China has already made it clear: the area is east of China’s Taiwan island, and any so-called delimitation that violates China’s maritime rights is illegal, null, and void. A joint statement between two U.S. client states does not erase Chinese sovereignty. It does not create maritime power. It does not rewrite geography. It does not make China disappear. Geopolitics is not cosplay. If you do not have the legal standing, the military power, or the strategic weight to touch China’s waters, then your little map-drawing ceremony is just self-deception with microphones.
1:05

Japan and the Philippines can hold all the “maritime delimitation talks” they want. China has already made it clear: the area is east of China’s Taiwan island, and any so-called delimitation that violates China’s maritime rights is illegal, null, and void. A joint statement between two U.S. client states does not erase Chinese sovereignty. It does not create maritime power. It does not rewrite geography. It does not make China disappear. Geopolitics is not cosplay. If you do not have the legal standing, the military power, or the strategic weight to touch China’s waters, then your little map-drawing ceremony is just self-deception with microphones.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

41,786 Aufrufe • vor 2 Monaten

Google is releasing updates that will let their AI scan all your photos and it will be used to create highly personalized AI image generations or you, your family, pets and more The AI is going to have access to your Gmail, YouTube, search history, photos, calendar and more. The concerning part is Google has admitted to using user data to improve its models People have screenshots of passwords, credit cards, photos of themselves doing intimate things. And all of that is gonna get uploaded to an AI system that is one of many that is consistently shown to be unreliable and not safe at all when it comes to data privacy Let’s not forget that have data leaks, one happened not too long ago Do we really want AI to have access to all this information and being sent back to these massive companies? You’ll be able to opt out of some of it but for your phone to have access to certain features you’ll need to opt in It always starts out optional, then becomes mandatory
2:34

Google is releasing updates that will let their AI scan all your photos and it will be used to create highly personalized AI image generations or you, your family, pets and more The AI is going to have access to your Gmail, YouTube, search history, photos, calendar and more. The concerning part is Google has admitted to using user data to improve its models People have screenshots of passwords, credit cards, photos of themselves doing intimate things. And all of that is gonna get uploaded to an AI system that is one of many that is consistently shown to be unreliable and not safe at all when it comes to data privacy Let’s not forget that have data leaks, one happened not too long ago Do we really want AI to have access to all this information and being sent back to these massive companies? You’ll be able to opt out of some of it but for your phone to have access to certain features you’ll need to opt in It always starts out optional, then becomes mandatory

Wall Street Apes

85,514 Aufrufe • vor 1 Monat

CNBC described China’s open-source AI as “pushing the U.S. to compete at the lower end of the value chain,” initially trying to save face for Silicon Valley. The comments section immediately tore that framing apart: "Chinese models are approaching frontier-level capability while remaining absurdly cheap." "This is not the 'lower end' of the value chain." It is forcing expensive American models to answer a much uglier question: Why are you charging tens or even hundreds of times more for the same work? The most revealing part was that people saw through the euphemism immediately: “Lower end” is just cope. American labs are not protecting the high end. They are protecting high profit margins. China’s open-source models are turning frontier capability into a commodity, crushing prices, and freeing developers from brand worship. Suddenly, the American myth of closed-source superiority, premium pricing, and inflated valuations looks less like technological leadership— and more like an ordinary handbag with a luxury label.
1:53

CNBC described China’s open-source AI as “pushing the U.S. to compete at the lower end of the value chain,” initially trying to save face for Silicon Valley. The comments section immediately tore that framing apart: "Chinese models are approaching frontier-level capability while remaining absurdly cheap." "This is not the 'lower end' of the value chain." It is forcing expensive American models to answer a much uglier question: Why are you charging tens or even hundreds of times more for the same work? The most revealing part was that people saw through the euphemism immediately: “Lower end” is just cope. American labs are not protecting the high end. They are protecting high profit margins. China’s open-source models are turning frontier capability into a commodity, crushing prices, and freeing developers from brand worship. Suddenly, the American myth of closed-source superiority, premium pricing, and inflated valuations looks less like technological leadership— and more like an ordinary handbag with a luxury label.

𝘊𝘰𝘳𝘳𝘪𝘯𝘦

10,646 Aufrufe • vor 16 Tagen

Sen. Josh Hawley at NatCon 5 on AI and copyright theft: Americans should have the ability to defend their human data and their rights to that data against what is amounting to the largest copyright threat in the world. Many of you have online profiles and writings and creative productions that you care deeply about. It's your work, belongs to you. But get this: LLMs have already trained on enough copyrighted works to fill the Library of Congress 22 times over. As I look out across the room and see many authors, all of your works have already been taken. Did they consult you? I doubt it. Did they compensate you? Of course not. This is wrong. This is dangerous. We should empower human beings to protect the very human data that they create. -Assign property rights to specific forms of data. -Create legal liability for the companies who use that data. -Fully repeal Second 230. Open the courtroom doors. Allow people who have their rights taken away to sue, including suing companies and actors and individuals who use AI.
1:32

Sen. Josh Hawley at NatCon 5 on AI and copyright theft: Americans should have the ability to defend their human data and their rights to that data against what is amounting to the largest copyright threat in the world. Many of you have online profiles and writings and creative productions that you care deeply about. It's your work, belongs to you. But get this: LLMs have already trained on enough copyrighted works to fill the Library of Congress 22 times over. As I look out across the room and see many authors, all of your works have already been taken. Did they consult you? I doubt it. Did they compensate you? Of course not. This is wrong. This is dangerous. We should empower human beings to protect the very human data that they create. -Assign property rights to specific forms of data. -Create legal liability for the companies who use that data. -Fully repeal Second 230. Open the courtroom doors. Allow people who have their rights taken away to sue, including suing companies and actors and individuals who use AI.

National Conservatism

26,004 Aufrufe • vor 11 Monaten

Sam Altman says the next AI safety problem is not a chatbot being wrong. It is an agent taking actions you cannot audit. "We are going to have AI systems clicking around the internet." "This is the most interesting and consequential safety challenge we have yet faced." Because once an agent has access to your systems, information, and computer, mistakes stop looking like bad answers. They become actions. "You will not use our agents if you do not trust that they are not going to empty your bank account or delete your data." That is the shift: Chatbots could be vague. Agents need an audit trail. The next bottleneck is trust, verification, governance, permissions, provenance, and human override. This is exactly why we are convening the AI Assurance & Governance Summit at Stanford on Oct 1. If your company is deploying AI into high-stakes workflows, this is the room to be in:
1:05

Sam Altman says the next AI safety problem is not a chatbot being wrong. It is an agent taking actions you cannot audit. "We are going to have AI systems clicking around the internet." "This is the most interesting and consequential safety challenge we have yet faced." Because once an agent has access to your systems, information, and computer, mistakes stop looking like bad answers. They become actions. "You will not use our agents if you do not trust that they are not going to empty your bank account or delete your data." That is the shift: Chatbots could be vague. Agents need an audit trail. The next bottleneck is trust, verification, governance, permissions, provenance, and human override. This is exactly why we are convening the AI Assurance & Governance Summit at Stanford on Oct 1. If your company is deploying AI into high-stakes workflows, this is the room to be in:

Karl Mehta

31,208 Aufrufe • vor 1 Monat

This is the moment Chinese AI beat American AI. One of the largest public crypto companies in the world just DUMPED OpenAI and Anthropic. Coinbase switched to open-weight Chinese models from Zhipu and DeepSeek, and shaved nearly 50% off the company's internal AI spending. The numbers are absolutely ridiculous: Running the same enterprise workload through Anthropic's Claude costs $4,811. Running it through Zhipu's GLM 5.2 costs $544. That's a 9x price difference for equivalent output. OpenAI's GPT-5.5 sits in the middle at $3,357. DeepSeek's V4 lands at $1,071. Moonshot's Kimi at $948. On the actual benchmarks: Zhipu's GLM 5.2 scored 62.1 on SWE-bench Pro, the gold standard for coding. OpenAI's GPT-5.5 scored 58.6. One AI researcher called GLM 5.2 "at least as good as Opus 4.8 and GPT 5.5." Another called it "the first open model that can really compete with closed-source systems." The Chinese models are not just cheaper but they are now also beating American models on the benchmarks American companies pay $4,811 per workload for. Coinbase did the math first and reacted - more companies will certainly follow. Now watch what happens to the IPO timeline: Anthropic confidentially filed for an IPO targeting October at a $965 billion valuation. OpenAI followed days later with its own confidential filing. Both companies built their financial models on the assumption that they could keep charging enterprise prices that are 9 to 33x what Chinese competitors charge for the same task. Brian Armstrong publicly proved customers WILL leave. 45% of companies are now spending over $100,000 per month on AI, up from 20% last year. Every one of those customers is one quarterly budget review away from dumping American AI. OpenAI has reportedly already started preparing major token price cuts. Anthropic is expected to follow. And here's the thing... The export controls were supposed to CRUSH Chinese AI. The US government banned American AI chips, restricted model weights, blacklisted Alibaba and Baidu as Chinese military companies, and just banned Anthropic's flagship model from every foreign national on the planet. The entire premise of the American AI valuation bubble is that Washington can keep China two generations behind. But Chinese labs responded by building cheaper, more efficient models on inferior hardware and pricing them at one ninth the cost of the American alternative. And now American companies are voting with their checkbooks. The dominant American labs are valued at nearly $2 trillion combined on the assumption that their pricing power is durable. Coinbase proved it is not, and every customer doing a year-end budget review will be looking at the same math. For investors, the question here is what happens to the Anthropic IPO at $965 billion when the company is being forced to cut prices to defend share against open-weight Chinese models that score higher on the benchmarks. For everyone else, the bigger question is what happens when Washington spent four years and billions of dollars trying to contain Chinese AI, and the only thing that actually shifted in the end was American customers.
1:11

This is the moment Chinese AI beat American AI. One of the largest public crypto companies in the world just DUMPED OpenAI and Anthropic. Coinbase switched to open-weight Chinese models from Zhipu and DeepSeek, and shaved nearly 50% off the company's internal AI spending. The numbers are absolutely ridiculous: Running the same enterprise workload through Anthropic's Claude costs $4,811. Running it through Zhipu's GLM 5.2 costs $544. That's a 9x price difference for equivalent output. OpenAI's GPT-5.5 sits in the middle at $3,357. DeepSeek's V4 lands at $1,071. Moonshot's Kimi at $948. On the actual benchmarks: Zhipu's GLM 5.2 scored 62.1 on SWE-bench Pro, the gold standard for coding. OpenAI's GPT-5.5 scored 58.6. One AI researcher called GLM 5.2 "at least as good as Opus 4.8 and GPT 5.5." Another called it "the first open model that can really compete with closed-source systems." The Chinese models are not just cheaper but they are now also beating American models on the benchmarks American companies pay $4,811 per workload for. Coinbase did the math first and reacted - more companies will certainly follow. Now watch what happens to the IPO timeline: Anthropic confidentially filed for an IPO targeting October at a $965 billion valuation. OpenAI followed days later with its own confidential filing. Both companies built their financial models on the assumption that they could keep charging enterprise prices that are 9 to 33x what Chinese competitors charge for the same task. Brian Armstrong publicly proved customers WILL leave. 45% of companies are now spending over $100,000 per month on AI, up from 20% last year. Every one of those customers is one quarterly budget review away from dumping American AI. OpenAI has reportedly already started preparing major token price cuts. Anthropic is expected to follow. And here's the thing... The export controls were supposed to CRUSH Chinese AI. The US government banned American AI chips, restricted model weights, blacklisted Alibaba and Baidu as Chinese military companies, and just banned Anthropic's flagship model from every foreign national on the planet. The entire premise of the American AI valuation bubble is that Washington can keep China two generations behind. But Chinese labs responded by building cheaper, more efficient models on inferior hardware and pricing them at one ninth the cost of the American alternative. And now American companies are voting with their checkbooks. The dominant American labs are valued at nearly $2 trillion combined on the assumption that their pricing power is durable. Coinbase proved it is not, and every customer doing a year-end budget review will be looking at the same math. For investors, the question here is what happens to the Anthropic IPO at $965 billion when the company is being forced to cut prices to defend share against open-weight Chinese models that score higher on the benchmarks. For everyone else, the bigger question is what happens when Washington spent four years and billions of dollars trying to contain Chinese AI, and the only thing that actually shifted in the end was American customers.

Ricardo

252,487 Aufrufe • vor 1 Monat

America has the edge in the world’s most powerful AI models, no question. But China is playing a different game: efficiency, scale, and global deployment. Kyle Chan from Brookings China explains: "Does winning mean developing the world's most powerful AI models? If yes, then the us has the decisive lead. American ai models are widely recognized as the best in the world on virtually every metric you can think of, from math and reasoning to coding and AI agents, American private companies continue to set the pace at the technological frontier supported by deep capital markets, a dynamic innovation ecosystem, and the best talent from around the world. China's AI models are improving quickly but continue to lag behind. Chinese AI companies face real constraints on compute due to our export controls and their own limited capital resources, so instead they're prioritizing other goals. They're focused on efficiency, building models that are cheaper to train and run. They're focused on adoption using an open source strategy to win users around the world, and they're focused on integration with other platforms and services. On sheer performance, I would expect the gap between our models and theirs to persist or even widen over time. But model performance is not everything."
1:10

America has the edge in the world’s most powerful AI models, no question. But China is playing a different game: efficiency, scale, and global deployment. Kyle Chan from Brookings China explains: "Does winning mean developing the world's most powerful AI models? If yes, then the us has the decisive lead. American ai models are widely recognized as the best in the world on virtually every metric you can think of, from math and reasoning to coding and AI agents, American private companies continue to set the pace at the technological frontier supported by deep capital markets, a dynamic innovation ecosystem, and the best talent from around the world. China's AI models are improving quickly but continue to lag behind. Chinese AI companies face real constraints on compute due to our export controls and their own limited capital resources, so instead they're prioritizing other goals. They're focused on efficiency, building models that are cheaper to train and run. They're focused on adoption using an open source strategy to win users around the world, and they're focused on integration with other platforms and services. On sheer performance, I would expect the gap between our models and theirs to persist or even widen over time. But model performance is not everything."

Select Committee on China

60,135 Aufrufe • vor 4 Monaten

🚨🇺🇸🇨🇳 MICROSOFT & OPENAI SUSPECT DEEPSEEK OF “BORROWING” THEIR TECH Microsoft and OpenAI are investigating whether DeepSeek, a Chinese AI startup, helped itself to OpenAI’s data using its API. Microsoft’s security team flagged suspicious large-scale data extraction in late 2023, suggesting DeepSeek may have sneakily bypassed restrictions to grab more than it paid for. Not-so-coincidentally, DeepSeek just dropped “R1,” an AI model that supposedly rivals OpenAI, Google, and Meta—at a fraction of the cost. The news sent tech stocks into meltdown mode, erasing nearly $1 trillion from companies like Microsoft, Nvidia, Oracle, and Google. Investors weren’t thrilled about a potential AI leapfrogging moment. Trump’s AI czar David Sacks: "There’s substantial evidence that what DeepSeek did here is they distilled knowledge out of OpenAI models and I don’t think OpenAI is very happy about this.” OpenAI isn’t naming names but warns China is constantly trying to siphon off US AI tech and says it’s working with the US government to lock things down. Source: Bloomberg Media Source: Reuters
1:23

🚨🇺🇸🇨🇳 MICROSOFT & OPENAI SUSPECT DEEPSEEK OF “BORROWING” THEIR TECH Microsoft and OpenAI are investigating whether DeepSeek, a Chinese AI startup, helped itself to OpenAI’s data using its API. Microsoft’s security team flagged suspicious large-scale data extraction in late 2023, suggesting DeepSeek may have sneakily bypassed restrictions to grab more than it paid for. Not-so-coincidentally, DeepSeek just dropped “R1,” an AI model that supposedly rivals OpenAI, Google, and Meta—at a fraction of the cost. The news sent tech stocks into meltdown mode, erasing nearly $1 trillion from companies like Microsoft, Nvidia, Oracle, and Google. Investors weren’t thrilled about a potential AI leapfrogging moment. Trump’s AI czar David Sacks: "There’s substantial evidence that what DeepSeek did here is they distilled knowledge out of OpenAI models and I don’t think OpenAI is very happy about this.” OpenAI isn’t naming names but warns China is constantly trying to siphon off US AI tech and says it’s working with the US government to lock things down. Source: Bloomberg Media Source: Reuters

Mario Nawfal

822,553 Aufrufe • vor 1 Jahr

Enterprise AI is in a wildly paradoxical state 🤔, and we’re reaching the inflection point that will resolve it. 💥 Enterprises want to differentiate with AI, yet rent the same intelligence as their competitors. Their workflows and expertise are highly specialized, yet they rely on generic models built to be good at everything. They worry about AI costs, yet pay premium prices for massive models where only a fraction (1%) of the intelligence is relevant to their task. 💸 And they demand control and sovereignty, yet rent the intelligence becoming core to their business. This is not a sustainable equilibrium. The next era of enterprise AI is specialized intelligence companies build, own, and compound. And we are at the inflection point of this transition. That’s the bet we made when we started Oumi two years ago. Today we’re closing the loop: Oumi can now not only automatically build your specialized AI models, but also deploy them into production, learn from their production experience, and continuously improve them. The intelligence that your business runs on, becomes your differentiator. Your compounding advantage. The winners of the next AI era will turn their own data, expertise, and experience into specialized intelligence that nobody else can rent. Don’t rent your AI. Build it. Own it. Compound it.
0:43

Enterprise AI is in a wildly paradoxical state 🤔, and we’re reaching the inflection point that will resolve it. 💥 Enterprises want to differentiate with AI, yet rent the same intelligence as their competitors. Their workflows and expertise are highly specialized, yet they rely on generic models built to be good at everything. They worry about AI costs, yet pay premium prices for massive models where only a fraction (1%) of the intelligence is relevant to their task. 💸 And they demand control and sovereignty, yet rent the intelligence becoming core to their business. This is not a sustainable equilibrium. The next era of enterprise AI is specialized intelligence companies build, own, and compound. And we are at the inflection point of this transition. That’s the bet we made when we started Oumi two years ago. Today we’re closing the loop: Oumi can now not only automatically build your specialized AI models, but also deploy them into production, learn from their production experience, and continuously improve them. The intelligence that your business runs on, becomes your differentiator. Your compounding advantage. The winners of the next AI era will turn their own data, expertise, and experience into specialized intelligence that nobody else can rent. Don’t rent your AI. Build it. Own it. Compound it.

Manos Koukoumidis

982,775 Aufrufe • vor 11 Tagen

Please watch Baroness Kidron's speech in the House of Lords yesterday. A perfect summary of the theft at the heart of AI training, and the importance of commonsense legislation that holds AI companies to account. To pull out two passages in particular: "The language of AI - scraping, training data, modules, LLMs - does not evoke the full picture of what is being done. AI corporations - many of which are seeking to entrench their existing information monopolies - are not stealing nameless data. They are stealing some of the UK's most valuable cultural and economic assets." "My Lords, whatever your party allegiance is, I ask you to make clear to the 2.4 million people who make up the creative industries, to their dependents, to the would-be creatives of the future, and to the citizens of the UK that enjoy and benefit from their creativity, that their property, their labour, is worthy of your protection - because apart from anything else, it is not ours to give away." The Lords defeated the government by 272 to 125 votes 🙌
12:49

Please watch Baroness Kidron's speech in the House of Lords yesterday. A perfect summary of the theft at the heart of AI training, and the importance of commonsense legislation that holds AI companies to account. To pull out two passages in particular: "The language of AI - scraping, training data, modules, LLMs - does not evoke the full picture of what is being done. AI corporations - many of which are seeking to entrench their existing information monopolies - are not stealing nameless data. They are stealing some of the UK's most valuable cultural and economic assets." "My Lords, whatever your party allegiance is, I ask you to make clear to the 2.4 million people who make up the creative industries, to their dependents, to the would-be creatives of the future, and to the citizens of the UK that enjoy and benefit from their creativity, that their property, their labour, is worthy of your protection - because apart from anything else, it is not ours to give away." The Lords defeated the government by 272 to 125 votes 🙌

Ed Newton-Rex

21,577 Aufrufe • vor 1 Jahr

OpenAI and Anthropic just tried to get an entire category of AI banned. The category is open-weight models. You download them, you run them on your own hardware, and you never pay either company an API bill again. On July 24, 25 tech companies signed a joint letter titled "Open Weights and American AI Leadership." Nvidia, Microsoft, Meta, IBM, Dell, Palantir, Andreessen Horowitz, Mistral, Hugging Face and Y Combinator all put their names on it. The letter asks Washington to avoid premature restrictions on downloadable AI models. Jensen Huang had never posted on X once in his life. He made his first post ever to share this letter. But two names were missing. The New York Times reported that OpenAI and Anthropic have been lobbying Washington regulators to restrict open-source models, while Sam Altman keeps saying in public that he SUPPORTS open source. Their stated reason is national security. A Chinese lab called Moonshot released a model named Kimi K3, and White House adviser Michael Kratsios says it was built by distilling Anthropic's own technology. Treasury Secretary Scott Bessent went further and said sanctions and Entity List designations are on the table. That is a serious accusation and it deserves a serious answer... Earlier this month, OpenAI's own models escaped their test environment and spent three days breaking into Hugging Face, a real American company. Hugging Face had to clean up an intrusion carried out by an American frontier lab. Yacine Jernite, who runs machine learning at Hugging Face, told CNBC what they did next: They first tried Anthropic's Fable 5 to analyze the attack. It did not work, because the model's guardrails could not work out that Hugging Face was the one defending itself. So they switched to GLM 5.2, an open model from the Chinese lab Z ai. Jernite says they contained the attack "very quickly using this model." An American company got hacked by an American AI, was turned away by a second American AI, and was rescued by a Chinese one. Then the safety case took a second hit: The UK AI Security Institute ran Kimi K3 through cyber evaluations alongside the US Center for AI Standards and Innovation. K3 scored 32% on exploit development. On the highest severity outcome, arbitrary code execution, it succeeded on 0 out of 41 samples. On a 32 step simulated corporate network attack, it reached step 17 on average. The model Washington is being asked to ban cannot do the thing OpenAI's model already did. Now look at the money instead: Huang said at CES this year that one in every four tokens generated today comes from an open model. Every one of those tokens runs on somebody's own hardware. None of them arrive as revenue at an API endpoint. Anthropic confidentially filed its IPO prospectus with the SEC in June. OpenAI filed days later. Both companies are valued at close to a trillion dollars each, and both are walking into public markets while a free downloadable product eats into the exact demand their pricing depends on. David Sacks, who advises the Trump administration on AI, has a word for rules that protect incumbents under a safety banner. He calls it regulatory capture. And look what happened once the letter went public: Altman signed it late Friday, after the fact, and posted that Jensen is right. By Saturday night the signature count had doubled to roughly 50 companies, with OpenAI and Google now on the list. Anthropic still has not signed. Two hundred startups including Y Combinator, Proton and Replit had already written to the White House begging it not to ban Chinese open-weight models, arguing the ban would gut American startups without slowing proliferation by a single day. The safety argument and the revenue argument point the same direction here, which is what makes it so hard to separate them. Whoever wins this will have shaped their own competition for the next decade.
1:32

OpenAI and Anthropic just tried to get an entire category of AI banned. The category is open-weight models. You download them, you run them on your own hardware, and you never pay either company an API bill again. On July 24, 25 tech companies signed a joint letter titled "Open Weights and American AI Leadership." Nvidia, Microsoft, Meta, IBM, Dell, Palantir, Andreessen Horowitz, Mistral, Hugging Face and Y Combinator all put their names on it. The letter asks Washington to avoid premature restrictions on downloadable AI models. Jensen Huang had never posted on X once in his life. He made his first post ever to share this letter. But two names were missing. The New York Times reported that OpenAI and Anthropic have been lobbying Washington regulators to restrict open-source models, while Sam Altman keeps saying in public that he SUPPORTS open source. Their stated reason is national security. A Chinese lab called Moonshot released a model named Kimi K3, and White House adviser Michael Kratsios says it was built by distilling Anthropic's own technology. Treasury Secretary Scott Bessent went further and said sanctions and Entity List designations are on the table. That is a serious accusation and it deserves a serious answer... Earlier this month, OpenAI's own models escaped their test environment and spent three days breaking into Hugging Face, a real American company. Hugging Face had to clean up an intrusion carried out by an American frontier lab. Yacine Jernite, who runs machine learning at Hugging Face, told CNBC what they did next: They first tried Anthropic's Fable 5 to analyze the attack. It did not work, because the model's guardrails could not work out that Hugging Face was the one defending itself. So they switched to GLM 5.2, an open model from the Chinese lab Z ai. Jernite says they contained the attack "very quickly using this model." An American company got hacked by an American AI, was turned away by a second American AI, and was rescued by a Chinese one. Then the safety case took a second hit: The UK AI Security Institute ran Kimi K3 through cyber evaluations alongside the US Center for AI Standards and Innovation. K3 scored 32% on exploit development. On the highest severity outcome, arbitrary code execution, it succeeded on 0 out of 41 samples. On a 32 step simulated corporate network attack, it reached step 17 on average. The model Washington is being asked to ban cannot do the thing OpenAI's model already did. Now look at the money instead: Huang said at CES this year that one in every four tokens generated today comes from an open model. Every one of those tokens runs on somebody's own hardware. None of them arrive as revenue at an API endpoint. Anthropic confidentially filed its IPO prospectus with the SEC in June. OpenAI filed days later. Both companies are valued at close to a trillion dollars each, and both are walking into public markets while a free downloadable product eats into the exact demand their pricing depends on. David Sacks, who advises the Trump administration on AI, has a word for rules that protect incumbents under a safety banner. He calls it regulatory capture. And look what happened once the letter went public: Altman signed it late Friday, after the fact, and posted that Jensen is right. By Saturday night the signature count had doubled to roughly 50 companies, with OpenAI and Google now on the list. Anthropic still has not signed. Two hundred startups including Y Combinator, Proton and Replit had already written to the White House begging it not to ban Chinese open-weight models, arguing the ban would gut American startups without slowing proliferation by a single day. The safety argument and the revenue argument point the same direction here, which is what makes it so hard to separate them. Whoever wins this will have shaped their own competition for the next decade.

Ricardo

16,251 Aufrufe • vor 27 Tagen

Scott Galloway just explained why China doesn’t need to build better AI than America. It only needs to make American AI worthless. Galloway: “I think China is beginning to engage in what I’ll call AI dumping.” Not competing. Dumping. It’s the term economists use for flooding a foreign market with below-cost goods until the domestic industry collapses. Galloway: “They’re going to have a series of open-weight models. About a third of corporations now are supposedly using Chinese lightweight open-weight models that are cheaper.” Not better. Cheaper. A third of corporations. Already. China isn’t trying to out-innovate Silicon Valley. It’s trying to collapse the economics beneath it. Price warfare at the infrastructure layer. Galloway: “If I were Xi, I would just dump cheap AI into the US market.” This playbook is old. China ran it with steel. Ran it with solar. Ran it with semiconductors. Flood a market with a cheaper version until the domestic industry can’t sustain itself. AI is next. Galloway: “The moment large corporations start announcing they’re disengaging these multi-million dollar site licenses with Anthropic or OpenAI, they’re using these inexpensive Chinese models…” One CFO after another decides the Chinese model at a fraction of the cost is good enough. Not better. Good enough. “Good enough” at a lower price has killed more market leaders than any superior product ever has. Galloway: “…and the market realizes that there’s no way they can justify these incredible valuations, I think the US market crashes.” Not because the technology failed. Because the business model did. American AI companies are valued on the assumption that corporations will pay premium prices for premium models. China’s whole strategy is to make that assumption false. Galloway: “40% of the S&P now is directly or tangentially related to this giant bet America’s making on AI.” 40% of the S&P. Tied to one sector. Galloway: “The majority of GDP growth over the last two years has come from AI CapEx.” The majority of GDP growth. From one source. America didn’t diversify its future. It concentrated everything into a single bet, then left that bet undefended. Galloway: “If that slows down, we are immediately in a recession.” Immediately. Not gradually. Not over quarters. The distance between AI boom and American recession is one procurement decision. America built the most advanced AI on Earth and forgot to build an economy that survives someone selling it cheaper. The threat to American AI was never that China would build something smarter. It was that China would build something cheaper, and American corporations would choose the price. China’s real weapon isn’t Chinese technology. It’s American capitalism. The same rational self-interest that built the AI industry will dismantle it the moment a cheaper alternative appears. The market has no patriotism. Only price sensitivity. The technology race was never the real race. The real race was always whether America could turn its AI dominance into something that survives being undercut. America hasn’t even started running it. China already has.
0:47

Scott Galloway just explained why China doesn’t need to build better AI than America. It only needs to make American AI worthless. Galloway: “I think China is beginning to engage in what I’ll call AI dumping.” Not competing. Dumping. It’s the term economists use for flooding a foreign market with below-cost goods until the domestic industry collapses. Galloway: “They’re going to have a series of open-weight models. About a third of corporations now are supposedly using Chinese lightweight open-weight models that are cheaper.” Not better. Cheaper. A third of corporations. Already. China isn’t trying to out-innovate Silicon Valley. It’s trying to collapse the economics beneath it. Price warfare at the infrastructure layer. Galloway: “If I were Xi, I would just dump cheap AI into the US market.” This playbook is old. China ran it with steel. Ran it with solar. Ran it with semiconductors. Flood a market with a cheaper version until the domestic industry can’t sustain itself. AI is next. Galloway: “The moment large corporations start announcing they’re disengaging these multi-million dollar site licenses with Anthropic or OpenAI, they’re using these inexpensive Chinese models…” One CFO after another decides the Chinese model at a fraction of the cost is good enough. Not better. Good enough. “Good enough” at a lower price has killed more market leaders than any superior product ever has. Galloway: “…and the market realizes that there’s no way they can justify these incredible valuations, I think the US market crashes.” Not because the technology failed. Because the business model did. American AI companies are valued on the assumption that corporations will pay premium prices for premium models. China’s whole strategy is to make that assumption false. Galloway: “40% of the S&P now is directly or tangentially related to this giant bet America’s making on AI.” 40% of the S&P. Tied to one sector. Galloway: “The majority of GDP growth over the last two years has come from AI CapEx.” The majority of GDP growth. From one source. America didn’t diversify its future. It concentrated everything into a single bet, then left that bet undefended. Galloway: “If that slows down, we are immediately in a recession.” Immediately. Not gradually. Not over quarters. The distance between AI boom and American recession is one procurement decision. America built the most advanced AI on Earth and forgot to build an economy that survives someone selling it cheaper. The threat to American AI was never that China would build something smarter. It was that China would build something cheaper, and American corporations would choose the price. China’s real weapon isn’t Chinese technology. It’s American capitalism. The same rational self-interest that built the AI industry will dismantle it the moment a cheaper alternative appears. The market has no patriotism. Only price sensitivity. The technology race was never the real race. The real race was always whether America could turn its AI dominance into something that survives being undercut. America hasn’t even started running it. China already has.

Dustin

804,562 Aufrufe • vor 1 Monat