Nvidia Taps Unitree for Humanoid Robot Platform
Nvidia is combining Unitree’s humanoid hardware with its own AI and simulation tools, in a new design aimed at researchers and developers.
Nvidia is combining Unitree’s humanoid hardware with its own AI and simulation tools, in a new design aimed at researchers and developers.
Therapy is predicated on trust. You can’t be honest and vulnerable, and share how you’re really feeling, if you don’t believe in the embodied-concerned-frown sitting in the armchair across from you.
So you can understand why one woman, 31-year-old Molly Quinn, was taken aback when her trusted therapist suddenly whipped out an AI model to start recording their private conversations, NPR reports.
“She wasn’t taking notes like she usually did,” Quinn recalled realizing halfway through one session. “The iPad was just propped up.”
Where were her words being processed and stored? Will they one day become training data? It’s not something you have to ask yourself when your therapist jots stuff down on a clipboard. But those questions were now racing through Quinn’s head, leaving her uneasy.
“The more I thought about it, the more I just started getting more and more sick to my stomach,” she told NPR. “This person who I’m supposed to be able to trust with some very private and very intense emotions had just completely disregarded something I said I was not comfortable with. I felt completely violated.”
Though her therapist offered to stop using the AI tool, Quinn cut her off and found another one.
“The trust was gone,” she told NPR.
Like doctors, therapists across the country are adopting AI tools for notetaking and generating transcripts. AI companies offering these services frame it as a way of cutting down on the drudgery of paperwork and other administrative tasks, freeing up more time to focus on patients — a permutation of a common AI industry refrain: let us do the tedious stuff for you.
The reliability of AI tools remains fairly dodgy, though, and even setting aside questions of hallucinations creeping into clinical notes — which is something we’re already seeing happen — it’s not clear whether patients are even comfortable with the tech yet. In a YouGov survey cited by NPR, only 11 percent of Americans said they would be open to using AI in mental health care. An even slimmer eight percent said they would trust AI being used this way, while 40 percent said they don’t trust the technology at all.
“Even the presence of AI changes the therapeutic experience,” Marisa Cohen, a couples and sex therapist in New York, told NPR. “Clients know or feel like something else is listening to them. That awareness can subtly alter their disclosure.”
“When you introduce something that’s being stored electronically, it raises additional questions about trust and safety,” Cohen added. “It’s essentially a third party.”
Tal Salman, the CEO a popular AI scribe tool for therapists called Berries, insists that conversation recordings are deleted immediately and that transcripts are stored on HIPAA compliant servers in the US. Even if this is true, if AI companies’ tools are to ever have a place in private mental health settings, they need the trust of patients — and that’s something the AI industry clearly hasn’t earned yet. Quinn fears that AI-recorded conversations could one day be exposed by hackers.
“We’re going to see breaches,” she told NPR. “Maybe not tomorrow, maybe not next week. But in a few years? I think we’re going to see them. And I don’t want my therapy session to be part of that.”
More on AI: The Pope Just Low Key Declared Holy War on Artificial Intelligence
The post Woman Alarmed When Her Trusted Therapist Starts Recording Her With AI appeared first on Futurism.
When it comes to excuses from the front office, Jets fans have heard it all. The beleaguered New York franchise continues to hold the longest playoff drought of all major-league men’s sports teams, a situation which has been blamed on everything from management and coaching to players and locker room culture. Fans have likewise heard all the promises of hare-brained schemes sold as the team’s salvation, from the short-lived Sam Darnold rebuild to the infamous Aaron Rodgers gamble.
Now, the organization has hatched a new plot to snap their historic dry spell: going all-in on AI.
New reporting by the Sports Business Journal revealed the Jets front office has been making a concerted push to embrace AI in their day-to-day work. According to Iwao Fusillo, the Jets’ recently appointed chief data and analytics officer, roughly 91 percent of front office staffers are now daily users of Microsoft Copilot.
“I call that level one, or horizon one, which is adoption,” Fusillo told Sports Business. “Do we have large business gains from that level one? Not really. But have we changed the culture of the entire front office? Yes. To think AI-first.”
During department-level AI workshops led by the digital consulting firm Next League, Sports Business reports staffers “generated” a whopping 60 ideas about where to deploy AI throughout the front office, and “probably double that” for the football side.
Of course, the real question is whether any of those ideas were good. Writ large, it remains a mystery how simply adopting AI is supposed change the depressing reality of life in the Jets organization.
The AI initiative and Fusillo’s appointment are the brainchild of Jets owner Woody Johnson, great-grandson of Robert Wood Johnson, founder of the eponymous Johnson & Johnson. Often described as easily influenced by agreeable toadies and public sentiment, the Jets mogul evidently isn’t aware that the infamously sycophantic tech will probably just tell him whatever he wants to hear. Johnson’s long-suffering fanbase, however, lacks that particular feature.
“Jets finally acknowledging they need to outsource for intelligence as there is none in the building itself,” one Redditor quipped. “We’re going 0-17,” a fan wrote on X-formerly-Twitter.
“Lol I asked ChatGPT [to] ‘make the Jets a Superbowl contender’ and the short of it was literally just get rid of any and everybody from the Jets,” one New York Giants fan shared in a Reddit post. “Some of its top recommendations were to change the coaching staff completely and somehow get a top 10 offense by year two.”
More on AI in sports: NBA Commissioner Announces Plans to Let AI Take Over for Lazy Referees
The post Fans Aghast as New York Jets Say They’re Switching to AI appeared first on Futurism.
The French startup has secured 10 megawatts of compute at Digital Realty’s Paris South campus.
Anthropic has activated Claude Opus 4.8 for users on May 28, 2026, just weeks after Opus 4.7’s April launch.
Fresh code leaks, desktop app sightings, and backend references confirm the rollout, delivering stronger agentic coding and reasoning amid intensifying competition from OpenAI.
Anthropic officially released Claude Opus 4.8 on May 28, 2026, delivering measurable improvements over Opus 4.7. The release confirms earlier speculation, after leaks on reddit suggested a planned roll-out.
Notwithstanding, the new model is now available at the same price with powerful new features for coding, agentic workflows, and user control.
Opus 4.8 shows stronger performance across coding, agentic skills, reasoning, and practical knowledge work benchmarks.
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Early testers reportedly highlight greater reliability, sharper judgment, and significantly improved honesty. The model is four times less likely than Opus 4.7 to miss flaws in code it produces and is less prone to unsupported claims.
Alignment assessments also reached new highs in prosocial traits while showing substantially lower rates of misaligned behavior compared to Opus 4.7.
New features rolling out today include:
“I think you’ll really like Opus 4.8 It’s as smart as its benchmarks show but expresses and utilizes that intelligence in a warm and collaborative way. Workflows are a great way to utilize it- I’m hooked. Article on that soon,” said Thariq, Anthropic team member focused on Claude Code.
Standard pricing remains unchanged: $5 per million input tokens and $25 per million output tokens.
Fast Mode for Opus 4.8, running at 2.5× speed, is priced at $10/$50 and is three times cheaper than previous fast modes.
The model is available immediately across claude.ai, Claude API (claude-opus-4-8), and major cloud platforms.
Anthropic plans lower-cost models with similar capabilities and is preparing Mythos-class models for wider release in the coming weeks after completing stronger cyber safeguards under Project Glasswing.
Enterprises and developers can begin testing Opus 4.8 today on complex agentic and coding workloads.
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The post Claude Opus 4.8 Rolls Out: Anthropic Strikes Back in AI Race appeared first on BeInCrypto.
For the first time, AI agents running on decentralized infrastructure can generate independent, on-chain proof of their own performance — thanks to a new integration between XYO Layer One and Theta EdgeCloud. No centralized cloud has ever offered this.
Autonomous AI agents are already operating at scale — initiating transactions, consuming cloud services, and coordinating with other agents, all without a human in the loop. But until now, there has been no reliable, independent way to verify whether those agents actually performed as intended. When no human is watching, the record of what happened — if it exists at all — lives inside the same system that ran the workload.
That changes today. XYO Layer One and Theta EdgeCloud have announced a new integration that gives AI agents something they have never had: verifiable, tamper-proof proof-of-performance written to a public blockchain by an independent observer.
AI agents are already running production workloads for the Houston Rockets, Olympique de Marseille, and partners across the MLS, NBA, NHL, and Ligue 1 on Theta EdgeCloud. As agentic AI scales across industries, the question of accountability — did it actually do what it said? — becomes critical infrastructure, not a nice-to-have.
XYO watches EdgeCloud from the outside — independently measuring real uptime, speed, and reliability — and writes permanent records to XYO Layer One. Those records are stored in XYO Data Lakes and can be queried by anyone, at any time. The data never touches the system it is measuring, which is precisely the point.
Centralized clouds can’t offer this — their performance data never leaves their own systems.
This integration unlocks a new capability for the broader AI industry: agents can now generate cryptographic receipts of their own execution. Every task completed, every service consumed, every coordination event — recorded independently and permanently on-chain, paid for in $XL1 with a portion of each payment burned.
For developers and enterprises deploying AI agents, this means auditability without trusting the platform running the agents. For end users interacting with AI systems, it means a publicly accessible performance history. For the broader Web3 ecosystem, it means the accountability layer that autonomous AI has been missing is now real.
The broader significance of this integration goes beyond XYO and Theta. As AI agents take on more consequential tasks — managing funds, executing trades, coordinating supply chains — the question of whether they performed correctly becomes a legal and commercial necessity, not just a technical curiosity.
Today’s announcement establishes a blueprint: an independent, blockchain-based verification layer that operates outside the systems it monitors. Theta EdgeCloud is the first infrastructure partner to ship a verification standard built this way. The XYO team says it will not be the last.
For $XL1 and $XYO holders, the integration ties real-world AI activity directly to on-chain economics. Every record written to XYO Layer One is a transaction. Every transaction burns a portion of $XL1. As AI agent workloads scale across EdgeCloud and beyond, that activity flows through XYO Layer One — creating deflationary pressure anchored to actual infrastructure usage, not speculation.
The XYO AI SDK is now open for early access testing. Developers can begin building verified AI applications and agents — with deployment directly to XYO Layer One — starting today. Theta EdgeCloud is live as the first verified partner, with more integrations expected to follow as the standard gains traction.
Two of crypto’s earliest protocols. One accountability standard built for the age of autonomous AI.
Huawei has achieved a breakthrough in building advanced chips in half a decade. The company announced a new technology called LogicFolding, which will allow them to stack computer circuits on top of each other.
This technology will save them from the need to buy machines to make the chips smaller. He Tingbo, who leads Huawei’s chip division, said at a tech conference in Shanghai on Monday that the new 3D design will make their chip reach the performance levels of the best chips in the world.
Washington and Beijing are fighting for control over artificial intelligence. American sanctions have stopped Huawei from getting the tiny chips that power phones, cars, and computers.
The U.S. has also blocked China from buying the software and equipment needed to make these chips. Beijing has spent billions building its own supply chain.
Huawei says its chips will match 1.4-nanometer technology by 2031. Right now, China can only make 7-nanometer chips. TSMC in Taiwan makes chips for Nvidia. It already uses 2-nanometer technology and expects to start making 1.4-nanometer chips in 2028.
The company is also replacing Moore’s Law with Tau Scaling Law. Moore’s law has been employed in the industry by making the transistors smaller. The Tau Scaling Law focuses on the speed of data transfer of the stacked chips.
“The industry will face these problems sooner or later,” He told reporters after her speech. “We have confidence in this path because we have practice as proof.”
People in the Chinese tech industry call her the “chip queen.”
However, the company still has some hurdles. The big challenge is to keep stacked chips from overheating, which current tools can’t protect against.
Costs, power use, heat, and putting everything together are already major hurdles for Chinese technology, according to Brady Wang from Counterpoint Research.
Still on Weibo, Huawei’s breakthrough is being hyped as what DeepSeek offered. Lower costs for the American standard technology. Some are even saying that U.S sanctions have pushed China into “survival mode,” which needed faster innovation.
Huawei also bounced back in 2023 with new phones that had surprisingly good Chinese-made 5G chips. American restrictions are an actual hurdle.
Nvidia CEO Jensen Huang went to China this month with President Donald Trump for talks with Chinese leader Xi Jinping. He told CNBC his company has “largely conceded” the Chinese chip market to Huawei. But he also said China is part of a $200 billion market for Nvidia’s new processors, as reported by Cryptopolitan previously.
AMD is putting $10 billion into building infrastructure. Nvidia is changing its business strategy to focus on enterprise customers instead of just big cloud companies. Both moves show American chipmakers are shifting away from China.
A new analysis from Anthropic warns that the next two years will decide whether democratic countries or authoritarian governments control the future of artificial intelligence.
Anthropic is an AI company. The report says democracies now lead in “compute,” which means the advanced chips needed to build the best AI systems. This lead exists because of American innovation and export controls.
But Chinese labs are staying close by, exploiting gaps in U.S. rules. They smuggle chips into China. They use American chips in data centers outside China. They run what Anthropic calls “distillation attacks.” These attacks involve creating fake accounts to copy American AI models. This steals decades of research and billions in investment.
Anthropic describes two possible futures for 2028. In the first, democracies close these loopholes and build a lead of 12 to 24 months in AI capabilities. In the second, China keeps finding ways around the rules and catches up. It then uses AI to expand surveillance and control.
The report says Firefox fixed more security problems last month using Anthropic’s new AI model than it did in all of 2025. A Chinese cybersecurity expert wrote that while China is “still sharpening our swords,” America has “suddenly mounted a fully automatic Gatling gun.”
Chinese state media said after Huawei’s announcement that competition should be “moderate and healthy.” It should help both sides advance. A Foreign Ministry spokesman said Trump and Xi agreed to start government talks on AI during their recent meeting in Beijing.
Anthropic says the decisions policymakers make this year will determine who controls transformative AI technology. It will also determine whether it serves democratic values or enables authoritarianism worldwide.
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Key takeaways:
Bittensor is one of the most renowned AI-facilitated decentralized networks that promotes blockchain and artificial intelligence infusion. By leveraging Proof of Learning (POL) technology, Bittensor supports user privacy while minimizing errors. The AI models within the network are reliable, flexible, and up-to-date with modern technological advancements. The AI-based Bittensor network prioritizes cross-chain integration and native token expansions to promote collaboration among various decentralized AI networks.
TAO uses reliable authentication methods to ensure a successful transfer of nodes through its AI knowledge to correct models. The process is made possible through the PoL consensus method, which secures this process. Moreover, this technology helps to develop different stages of more advanced AI technology within the blockchain. Bittensor also uses its TAO token to incentivize node operators and AI developers.
What’s next for Bittensor and TAO in 2026 and beyond? Let’s get into the TAO price prediction and technical analysis.
| Cryptocurrency | Bittensor |
| Ticker | TAO |
| Current price | $277.96 (+0.71%) |
| Market cap | $3.04B |
| Trading volume (24-hour) | $171.08M |
| Circulating supply | 10.93M TAO |
| All-time low | $30.40 on May 14, 2023 |
| All-time high | $767.68 on Apr 11, 2024 |
| 24-hour low | $280.10 |
| 24-hour high | $269.05 |
| Metric | Value |
| Price Volatility (30-day variation) | 8.04% (Very High) |
| 14-day RSI | 48.47 |
| 50-day SMA | $275.59 |
| 200-day SMA | $258.86 |
| Market Sentiment | Neutral |
| Fear and greed index | 30 (Fear) |
| Green days | 13/30 (43%) |
TL;DR Breakdown:
On May 25, 2026, TAO price analysis indicates a mild bullish daily trend, with Bittensor currently trading at $277.96. The altcoin has shown a 0.71% increase in value over the last 24 hours, primarily due to the swift recovery observed over the day, as the token is slipping from sellers’ grip. Buyers remain in control as the TAO price has the nearest support at the $274 level, and it may continue to maintain above the aforementioned level for the coming days.
The one-day price chart of Bittensor confirmed a bullish trend for the altcoin. The TAO/USD pair value has slightly recovered to $277.96 following a bearish spell. The comparatively high volatility suggests a higher chance of a reversal in the trend or further price appreciation.

The distance between the Bollinger Bands determines the market volatility. Currently, this distance is wide, leading to high volatility levels. Moreover, the upper limit of the Bollinger Bands indicator, indicating resistance, has shifted to $329. Whereby its lower limit, indicating support, has moved to a low of $247.
The Relative Strength Index (RSI) indicator is in the neutral region, in contrast to the other technical factors, which also seem to be bearish. Its curve also increased to 54 during the day. This slowly increasing price movement today reflects a relatively balanced trading setup in the market under the larger bearish trend. However, if the bullish momentum accelerates, the RSI value will move further up into the neutral region.
The four-hour price chart for the Bittensor coin signifies a weak bearish trend, as the token’s price movements are again in a downward direction, with sellers trying to control the market. In the past few hours, the cryptocurrency’s value has slightly decreased to $277.81. Red candlesticks on the price chart signal a returning selling pressure.

The Bollinger Bands are expanding, as the volatility level is high on the 4-hour chart. The high volatility suggests higher market unpredictability. The upper Bollinger Band has shifted to a $289 high, indicating the resistance level. Conversely, the lower Bollinger Band is at $259, indicating the support level.
Multiple technical quantitative indicators are still bearish, but the RSI indicator is in the neutral region. However, the current score of 53 and decreasing numbers confirm selling pressure. The declining curve on the indicator’s graph shows rising selling activity and bearish progress as the market conditions turn unfavorable on an hourly basis.
| Period | Value ($) | Action |
|---|---|---|
| SMA 3 | 273.13 | BUY |
| SMA 5 | 274.28 | BUY |
| SMA 10 | 271.05 | BUY |
| SMA 21 | 289.05 | SELL |
| SMA 50 | 275.59 | BUY |
| SMA 100 | 255.45 | BUY |
| SMA 200 | 258.86 | BUY |
| Period | Value ($) | Action |
|---|---|---|
| EMA 3 | 274.73 | BUY |
| EMA 5 | 273.97 | BUY |
| EMA 10 | 276.07 | BUY |
| EMA 21 | 279.09 | SELL |
| EMA 50 | 275.26 | BUY |
| EMA 100 | 267.74 | BUY |
| EMA 200 | 274.04 | BUY |
Bittensor (TAO) fundamental analysis indicates a bullish outlook for current market trends. The TAO/USD price has slightly recovered to $277.96, but the bearish momentum has not faded yet. Most technical indicators signal bearishness, but the price charts lean in favor of the buyers, suggesting a potential move toward the $294 level, due to today’s recovery.
TAO coin continues to trade higher, indicating growing adoption among crypto investors as AI development and machine learning progress. Despite this, the coin faces uncertainties and volatility like all other cryptocurrencies. Our Cryptopolitan price prediction explores its potential profit and expected movements from 2026 to 2032 while considering the past performance. However, this is not investment advice, and one must conduct their own research before taking any investment decision according to their risk tolerance.
TAO is up primarily due to buying pressure from traders after some degree of bullish price action, mainly due to strong market sentiment surrounding speculative AI tokens and the AI industry at large. Recent stability near key support levels also played a role in the resurrection of the bullish trend as traders started buying following a bull rally, and the token’s price has also increased during the past 24 hours.
Bittensor (TAO) powers the Bittensor Network and is not a stock. Stocks are usually traded on stock exchanges, and stock ownership represents a stake in a company. Buying TAO tokens gives the buyer certain rights within the Bittensor Network, for example, governance participation but not ownership in a company. However, Bittensor (TAO) tokens can be purchased and traded on different exchanges, including Binance, Bitget, Coinbase, KuCoin, and Kraken. See our price analysis part for day-to-day price changes of the TAO token.
The highest Bittensor (TAO) price prediction for 2026 is around $570.20, but it is not easy to predict Bittensor price movements due to its volatile nature.
Yes, Bittensor should surpass $1000 by 2028. Its price will range between $842.56 and $1,000.54 during that period, which makes it a viable option to buy Bittensor tokens, considering the future performance and long-term trends, as decentralized AI development is expected to scale exponentially.
The total supply of Bittensor (TAO) tokens is 21 million TAO.
According to most market observers, Bittensor TAO will trade higher in the coming years. However, factors like market crashes or difficult regulations could invalidate this bullish theory.
A break of resistance will result in a mini bull run, with the next target at $352 during the month. The average price is expected to be $263, according to the current forecast. In a bearish scenario, TAO could drop to $197 at its lowest.
| Month | Potential low | Potential average | Potential high |
| May 2026 | $197 | $263 | $352 |
The technical indicators are bullish on TAO for the end of 2026. It is anticipated to trade between $134 and $473.94, with an average price of $394.95, according to the Bittensor price prediction.
| Year | Potential low | Potential average | Potential high |
| 2026 | $134 | $394.95 | $473.94 |
| Year | Minimum Price | Average Price | Maximum Price |
| 2027 | $579.26 | $658.25 | $737.24 |
| 2028 | $842.56 | $921.55 | $1,000.54 |
| 2029 | $1,105.86 | $1,184.84 | $1,263.83 |
| 2030 | $1,369.15 | $1,448.14 | $1,527.13 |
| 2031 | $1,632.45 | $1,711.44 | $1,790.43 |
| 2032 | $1,895.75 | $1,974.74 | $2,053.73 |
TAO is expected to gain bullish momentum in 2027. According to the updated Bittensor forecast, the token will range between $579.26 and $737.24, with an average price of $658.25.
The Bittensor outlook strengthens further in 2028. Analysts expect TAO to trade between $842.56 and $1,000.54, with an average yearly price of $921.55.
The 2029 Bittensor price prediction suggests TAO will move between a minimum of $1,105.86 and a maximum of $1,263.83, settling at an average price of $1,184.84 for the year.
For 2030, Bittensor price predictions indicate a trading range from $1,369.15 to $1,527.13, with an average expected price of $1,448.14.
In 2031, Bittensor price prediction, TAO is projected to range between $1,632.45 and $1,790.43, with an average price of $1,711.44, which is quite higher than its current value.
The Bittensor price prediction for 2032 places TAO between $1,895.75 and $2,053.73, with an average price of $1,974.74.

| Platform | 2026 | 2027 |
| Digitalcoinprice | $202.28 | $224.87 |
| Coincodex | $245.77 | $245.77 |
According to our predictions, TAO could recover to $473.94 by the end of December 2026. We expect TAO to maintain a trading range of $579.26-$737.24, with an average of $658.25 in 2027. Note that the predictions are not investment advice. Seek independent professional consultation or do your research.

The AI boom now has one very ugly question hanging over it. Is the money real, or are Big Tech companies just feeding cash to AI startups and booking the same cash as cloud sales later?
That question now sits right on top of OpenAI and Anthropic, because fresh filings show both companies are tied to more than half of the almost $2 trillion in future cloud revenue sitting on the books of Microsoft (MSFT), Oracle (ORCL), Alphabet (GOOGL), and Amazon (AMZN).
It sounds too good to be true, and yes, it is wild. A tech giant invests billions in an AI firm through some financing agreement, and in that agreement, the AI firm is advised to deploy its funds on purchasing cloud infrastructure owned by the same tech giant.
And so, the AI firm receives funding, the cloud firm makes income, and Wall Street enjoys looking at some impressive figures. The money does not get very far, however. It goes out through one door and returns through another door in the guise of a new customer.
Microsoft’s OpenAI collaboration serves as an illustrative example. Microsoft spent close to $13 billion on funding OpenAI; however, this investment was not limited to cash contributions only. The majority of that investment consisted of Azure credits, which OpenAI used to develop and execute its AI models using Microsoft infrastructure.
The usage of the Microsoft servers by OpenAI generated revenues for Microsoft. As a result, Microsoft contributed financially to OpenAI’s activities, OpenAI used Microsoft resources to execute them, and Microsoft recognized that contribution as demand from its customers.
OpenAI’s cloud bill has now climbed above $60 billion a year. Its revenue is around $25 billion. That means its server costs are more than double what it brings in. For a normal company, that would look like a giant red flag. In AI land, it gets treated like growth.
Anthropic is running a similar play with Amazon. The company spent about $2.66 billion on Amazon Web Services in nine months. That was roughly the same size as its revenue at the time. So the money coming in was almost matched by the money going straight back out to AWS.
That is where the second part of the scam plays out. With more money flowing into Anthropic or OpenAI at a higher valuation, the technology giants that have invested in them can inflate the value of their stakes to make money without having sold any goods or collected any cash. A gain has been made.
Google’s parent company, Alphabet, earned $62.6 billion in the first quarter of 2026. $28.7 billion was attributed to Google’s gains in relation to its stake in Anthropic. Amazon posted $30.3 billion in earnings in the first quarter of 2026. Its Anthropic gains accounted for $16.8 billion of it.
However, Amazon’s cash metrics appeared to be in a more difficult position. Free cash flow fell by 95% to $1.2 billion, and the company also invested $44.2 billion into physical data centers. This clearly demonstrates the difference between accounting profits and real cash. One sits in spreadsheets, while the latter builds real-life data centers using land, semiconductors, electricity, cooling, connections, buildings, and personnel.
This could lead to concentration risks for both companies. In particular, Microsoft has 49% of its $627 billion future backlog dependent on OpenAI. On its part, Oracle has 54% of its $553 billion future pipeline dependent on OpenAI alone.
This all looks eerily familiar to something straight out of the dot-com era. Back in 2001, when Global Crossing and Qwest Communications traded equal fiber network capacity and recorded such swaps as sales. As a result, Qwest lost $1.4 billion in fraudulent revenue. Meanwhile, Global Crossing filed for bankruptcy. The only thing that separates both cases today is the fact that such swaps by telecommunications companies were not considered legal at that time, while today’s AI cloud loop easily fits in today’s accounting rules.
According to the Kobeissi Letter, the ten largest American stocks constitute 41% of the S&P 500. Among these stocks, we find Magnificent Seven, including Apple and Tesla. This percentage is 14 points above the previous dot-com peak in 2000.
“This means about 41 cents of every dollar invested in the S&P 500 flows directly into shares of just 10 firms,” The Kobeissi Letter wrote. “Roughly 35 cents of every dollar flows specifically into the Magnificent 7 group. All while nearly 50 cents of every dollar is now going into AI-linked stocks. Mega-cap tech is all that matters right now.”
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The artificial intelligence sectors in both the United States and China are being flooded with unprecedented capital. However, the AI funding is now becoming a competition between the two largest economies.
Global AI startups raised $255.5 billion in Q1 2026 alone. Meanwhile, Chinese AI ventures separately pulled in over 110 billion yuan ($16.2 billion).
Pan Xiaodong, the secretary general of the Ministry of Science and Technology, made some huge announcements at a Beijing press conference back in February. He mentioned that the Chinese government had launched a national venture capital guidance fund. It focuses on early-stage, small, long-term, and hard-tech enterprises. This includes AI, semiconductors, and advanced manufacturing. The estimated total scale of the fund is around 1 trillion yuan ($144.45 billion).
Investors linked to the Chinese government reportedly participated in more than 140 AI deals in 2025. It is a huge jump compared to the 10 deals per year seen before 2018. The authority has also joined hands with financial institutions and local governments. This is done to establish various funds totaling over 350 billion yuan. This includes tech-industry integration funds and secondary market funds.
DeepSeek will reportedly have its first outside investment round led by China’s Integrated Circuit Industry Investment Fund (the “Big Fund”). The AI company came into the light for its cost-efficient models. The startup’s valuation surged from $10 billion to $20 billion in April. It later reached an estimated $45-$50 billion by early May.
Other investment rounds backed by the government include Moore Threads, a Beijing-based GPU designer, which raised $720 million at a $4.1 billion valuation in February 2025. Moonshot AI secured $700 million at a $10 billion valuation in January 2026, while StepFun reportedly raised $717 million.
Linkerbot, a robotic-hand startup, is targeting a $6 billion valuation backed by Ant Group and Bank of China Asset Management, while Unitree Robotics has filed for a Shanghai listing seeking up to $7 billion.
Washington banned American investors from backing Chinese AI and chip companies back in January 2025. In late April, China applied its own version of the same restriction. The National Development and Reform Commission instructed Moonshot AI, StepFun, and ByteDance not to accept US capital without explicit government clearance after Meta acquired Manus for $2 billion.
Cryptopolitan previously reported that the Trump administration accused Chinese labs of “industrial-scale” distillation of American AI models. Distillation is a method where a developer uses data from a larger AI model to train a smaller one.
The White House memo outlined four measures to stop this, including sharing intelligence on distillation tactics and coordinating defenses with US AI companies.
Anthropic also previously accused DeepSeek, Moonshot AI, and MiniMax of exploiting its models.
Despite the tensions, the total deal activity for the Chinese private equity market reached 2,568 transactions worth 234.4 billion yuan in Q1 2026, and foreign-currency deals in China more than doubled year-on-year to 210 in the same period. The disclosed investment value jumped by 495% to 67.3 billion yuan ($9.9 billion).
In the US, investments from the first quarter of 2026 surpassed the $254.4 billion deployed across all of 2025. OpenAI, Anthropic, and xAI accounted for more than two-thirds of the total.
Despite the differences in the US and Chinese governments’ approaches, they are both producing results. Chinese large-model companies have shortened iteration cycles to under three months by 2026, and a Stanford University report suggested that the performance gap between top US and Chinese AI models has “effectively closed.”
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