Nvidia CEO Jensen Huang called Marvell Technology the next trillion-dollar company at Computex on June 2. Marvell shares jumped about 33% in a single session, their biggest one-day gain on record. The move added roughly $56 billion in market value, pushing Marvell above $250 billion.
The endorsement landed as investor Michael Burry warned that Nvidia itself faces concentrated demand and hidden financing risk across the AI buildout.
Huang made a surprise appearance during Marvell CEO Matt Murphy’s keynote in Taipei, spending about 10 minutes on stage. He praised Marvell’s networking and connectivity chips as essential to data centers, where AI workloads run across thousands of linked processors that must share data quickly.
The remark followed Nvidia’s roughly $2 billion equity investment in Marvell, which tied the firm’s custom accelerators and optical networking to Nvidia’s AI factory architecture.
BREAKING: Marvell Technology, $MRVL, extends gains to over +45% in 2 days after Nvidia CEO Jensen Huang says it could become the “next trillion-dollar company.”
Bulls argue connectivity is the next bottleneck in AI systems after raw compute and memory. Marvell builds the switches, optics, and custom silicon that link those clusters, and data center products now drive most of its revenue.
Skeptics counter that Marvell trades at a steep valuation. It also faces strong competition from Broadcom in networking silicon.
“…the next trillion-dollar company,” CNBC reported, citing Jensen Huang.
A single endorsement rarely changes fundamentals, yet Huang’s words carry weight with traders. Analysts have also stayed broadly bullish on Nvidia, reflecting confidence in the wider AI trade.
Michael Burry’s Warning on Nvidia
Michael Burry, known for his role in The Big Short, has taken the other side of the AI story. His firm, Scion Asset Management, bought put options (short orders) on one million Nvidia shares.
Burry flagged Nvidia’s customer concentration as a core risk. He said the top three customers now account for 64% of Nvidia’s accounts receivable, up from 56% the prior quarter and about 33% in 2020.
🚨Michael Burry says Nvidia has 3 big customers and if they stop buying the whole thing is over.
Those 3 customers now account for 64% of Nvidia’s entire accounts receivable.
In 2020 that number was 33%. It jumped 8 percentage points in a single quarter.
He also described much of today’s spending as a temporary benchmarking phase he calls a tokenmaxxing bubble. In his view, that demand looks permanent now, but could fade.
“The conditions for an aggressive fall are as strong as they have been in the history of the stock,” Burry stated.
His thesis points to leveraging hidden across the system. A Moody’s report in February found that Microsoft, Amazon, Alphabet, Meta, and Oracle have $662 billion in future data center lease commitments that are not yet reflected on their balance sheets.
That figure equals roughly 113% of the five companies’ adjusted debt, according to Moody’s. The obligations become real cash costs once the leases begin.
Other signals have added to the caution. Reports of falling H200 rental prices have raised questions about near-term GPU demand.
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.”
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,” afan 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.”
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.
Claude Opus 4.8 Launches: Anthropic Upgrades AI Flagship
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.
Major Capability Gains
Opus 4.8 shows stronger performance across coding, agentic skills, reasoning, and practical knowledge work benchmarks.
Introducing Claude Opus 4.8: it builds on Opus 4.7 with sharper judgment, more honesty about its own progress, and the ability to work independently for longer than its predecessors.
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:
Effort Control: Users on claude.ai and Cowork can now select how much thinking effort Claude applies — from Low (faster, lower rate-limit usage) to Max. Opus 4.8 defaults to High effort for the best balance of quality and experience.
Dynamic Workflows in Claude Code: This research preview feature enables Claude to tackle massive tasks by planning, running hundreds of parallel subagents, and verifying outputs. It supports codebase-scale migrations across hundreds of thousands of lines of code.
Messages API Update: Developers can now insert system instructions mid-conversation without breaking prompt cache.
“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.
Pricing and Availability
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.
XYO and Theta Just Solved AI’s Accountability Problem
AI & Infrastructure
XYO and Theta Just Solved AI’s Accountability Problem
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.
Crypto Coin Show·News & Analysis·May 2026
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.
Why This Matters Now
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.
What AI Agents Can Now Do That They Couldn’t Before
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.
Agents can now prove execution
Every task, coordination event, and service call can generate an on-chain record — written by an independent observer, not the agent itself.
Infrastructure can be audited publicly
Uptime, speed, and reliability records for Theta EdgeCloud are now permanently stored in XYO Data Lakes, open to anyone.
Builders can ship in days, not months
The XYO AI SDK compresses what would traditionally take months of engineering into a days-long integration, deployed directly to XYO Layer One.
The standard is open
Theta is the first partner — but XYO and Theta Labs are building a shared standard any infrastructure provider can adopt.
A New Accountability Layer for Agentic AI
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.
Token Mechanics: Every Verification Is a Transaction
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.
$XL1 Token Flow
Agent Runs
AI workload executes on Theta EdgeCloud
→
XYO Verifies
Independent record written to XYO L1
→
$XL1 Paid
Every record is a transaction
→
Burn
Portion of every payment permanently removed
What Comes Next
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.
Early Access — Now Open
Build with the XYO AI SDK
Start shipping verified AI apps and agents in days — not months.
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.
China breaks from Moore’s Law with new chip design
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.
American chipmakers bet big on new markets
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.
Bittensor price predictions anticipate a high of $473.94 by the end of 2026.
In 2028, TAO will range between $842.56 and $1,000.54, with an average price of $921.55.
In 2032, TAO will range between $1,895.75 and $2,053.73, with an average price of $1,974.74.
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.
Overview
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
TAO price prediction: Technical analysis
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%)
Bittensor price analysis
TL;DR Breakdown:
TAO price analysis confirms a bullish trend at $277.96.
The altcoin has gained 0.71% over the day.
TAO token has support at $265.
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.
TAO/USD 1-day chart analysis
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.
TAO/USD 4-hour chart analysis
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 $259, indicating the support level.
Multiple technical quantitative indicators are still bearish, but the RSI indicator is in the neutral region. However, the current score of 53 and decreasing numbers confirm selling pressure. The declining curve on the indicator’s graph shows rising selling activity and bearish progress as the market conditions turn unfavorable on an hourly basis.
Bittensor technical indicators: Levels and actions
Daily simple moving average (SMA)
Period
Value ($)
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
Daily exponential moving average (EMA)
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
What can we expect from Bittensor price analysis next?
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.
Is Bittensor TAO a good investment?
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.
Why is TAO up?
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.
How much is the Bittensor stock worth?
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.
What is the price prediction for TAO 2026?
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.
Will Bittensor reach $1000?
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.
What is the total supply of Bittensor?
The total supply of Bittensor (TAO) tokens is 21 million TAO.
Does Bittensor have a good long-term future?
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.
Recent news/ opinions on Bittensor
ORO just went live on Bittensor, a specialized marketplace focused on AI agents for real-world e-commerce. It is important to remember that ORO (subnet 15) outperformed OpenAI’s GPT-5.4 on some complex online shopping evaluations.
ORO is now live on Bittensor, an open arena for AI agents.
A decentralized evaluation platform where miners submit AI shopping agents and validators assess them independently, with top performers earning emissions.
— xTAO – a Bittensor company (@xtaohq) May 1, 2026
Bittensor price prediction May 2026
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
Bittensor price prediction 2026
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
Bittensor price predictions 2027-2032
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
Bittensor’s price forecast 2027
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.
Bittensor price prediction 2028
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.
Bittensor TAO price prediction 2029
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.
Bittensor price prediction 2030
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.
Bittensor crypto price prediction 2031
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.
Bittensor price prediction 2032
The Bittensor price prediction for 2032 places TAO between $1,895.75 and $2,053.73, with an average price of $1,974.74.
TAO market price prediction: Analysts’ TAO price forecast
Platform
2026
2027
Digitalcoinprice
$202.28
$224.87
Coincodex
$245.77
$245.77
Cryptopolitan’s Bittensor (TAO) price prediction
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.
TAO launched on March 6, 2023, at $93.4, but fell below its opening price within a week, sliding into the $76 range.
By early April, it had lost half its value, dropping to $47, and continued downward to its $30.83 low in May before slowly recovering to $63 by the end of the month.
The token climbed to $86.18 in July, just under its launch price, then pulled back again and traded near $54 through October.
Momentum returned in November, pushing TAO into the $95 range, showing continuous improvement, and then sharply to a peak of $379 on December 15, 2023.
TAO trended downward into early 2024 but surged to its all-time high of $757.60 in March. It quickly corrected to $522 in April and continued weakening through mid-year, reaching $216 in July.
A brief rebound to $357 faded again as the token slipped back toward the mid-$200s by late summer, as per the crypto market price history records.
Momentum returned in October, pushing TAO into the $660 range before cooling to $468, according to the historical price data. It climbed once more to $679 in November but ultimately closed 2024 at $440.69, as the broader crypto market turned bearish again.
TAO opened in 2025 at $439.73, peaked at $565 in January, and its price decreased to the $324 level in February, taking down the token’s market capitalization as the technical indicators turned bearish due to some fundamental factors.
In March, TAO dipped to the $259 mark and descended further to $228 in April; however, in May, it recovered to $467 as the Bittensor market revived.
In October, TAO observed its year’s lowest prices extending toward $200.44.
TAO opened trading in November at $506, lost 46% of its value, and closed the month at $269.11, while at the start of December, the coin was trading between $256.29 and $298.90.
At the start of January 2026, TAO was trading near the $223 range, as the market shifted towards the bearish side.
In March, TAO traded below the psychological level of $200, but it surged past $300 in the month of April. At the start of May, TAO is trending above the $260 range, as current market sentiment turned decidedly bullish once again.
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 books OpenAI cloud spending after funding the same 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.
Amazon burns real cash while AI paper gains lift reported profit
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.”
