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Bitcoin slips below $71k as Powell and Iran oil shock hit crypto

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Bitcoin sinks below $71k as Powell’s hawkish tone and Iran’s oil shock trigger a $542M liquidation wave across leveraged crypto markets.

Summary

  • Bitcoin drops to about $71,313, Ethereum to $2,201, as crypto and stocks sell off on Fed projections and oil shock fears.
  • Powell flags oil-driven inflation, keeps just one 2026 rate cut in the dot plot, crushing hopes for easier policy and triggering a risk-off move.
  • Over $542M in mostly long liquidations and Brent above $110 show how leveraged crypto positioning collides with Iran-driven energy turmoil.

Crypto markets extended their slide into Thursday as the combined aftershock of the Federal Reserve’s March policy meeting and an escalating oil shock from the Iran conflict continued to rattle risk assets. Bitcoin (BTC) fell to approximately $71,313 (-4.62%), Ethereum dropped to $2,201 (-5.92%), and a cascade of leveraged long positions was wiped out — with total network-wide liquidations reaching $542 million over 24 hours, of which $448 million were long positions. It was the largest liquidation event in weeks, and the most heavily one-sided since the early stages of the U.S.-Iran conflict in late February.

The proximate trigger was Wednesday’s Federal Open Market Committee decision and, more critically, the press conference that followed. The Fed held its benchmark rate at 3.5%–3.75% as universally expected, with the FOMC voting 11-1 to maintain that range. But the new Summary of Economic Projections — the first of 2026 — delivered the information markets least wanted to hear. The Fed raised its 2026 PCE inflation forecast to 2.7%, up from a prior estimate of 2.4%, citing the oil shock stemming from Iran’s blockade of the Strait of Hormuz as a direct driver. The dot plot’s median remained anchored at just one 25-basis-point cut for all of 2026, dashing residual hopes for a more accommodative path.

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Fed Chair Jerome Powell was unambiguous in his press conference. “The oil shock for sure shows up,” he said, referring to its impact on the central bank’s projections. In his opening statement, he noted that near-term inflation expectations “have risen in recent weeks, likely reflecting the substantial rise in oil prices caused by the supply” disruption — a reference to the Hormuz closure that has taken roughly 20% of global oil flows offline since late February. Core PCE rose 3.0% in the 12 months through February, well above the Fed’s 2% target. Powell rejected comparisons to 1970s stagflation, arguing unemployment remains near normal levels, but acknowledged the tension between the Fed’s dual mandate goals in the current environment.​

The market reaction was swift and familiar. Bitcoin dropped from approximately $74,000 to $70,900 within hours of the press conference — its eighth decline following an FOMC meeting out of the last nine. The Nasdaq closed down 1.5% on Wednesday, the Dow and S&P 500 reversed five consecutive sessions of gains to hit their lowest levels since November, and 10-year Treasury yields climbed more than 5 basis points. On Thursday, the selloff continued, with the Dow opening down 420 points (-0.91%), the S&P 500 -0.89%, and the Nasdaq -1.23%.

The liquidation breakdown tells its own story: Bitcoin longs alone accounted for $172 million in forced selling, ETH longs for $126 million, with a total of 143,776 traders liquidated globally. The largest single liquidation — an ETH position worth $17.98 million on Aster — underscores how aggressively leveraged some participants were ahead of the FOMC. Long-term Bitcoin holders were also reported to have sold over 1,650 BTC worth approximately $117 million in the wake of Powell’s remarks.

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With Brent crude now above $110 per barrel following renewed Iranian attacks on regional energy facilities, and a Fed that has explicitly incorporated oil-driven inflation into its baseline forecast, the conditions for a near-term rate cut have seldom looked more remote.

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Solana Price Drops 3% but Longs Keep Piling In: 17 Million SOL Explain Why

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Solana (SOL) price trades at $82.20 on April 9, down 3% in 24 hours and 34% year-to-date. Yet leveraged traders are betting heavily on a bounce.

The seven-day liquidation map on Bybit shows $309 million in cumulative long leverage against just $127 million in shorts, a 2.4x mismatch that defies the price weakness. A bullish reversal pattern on the 12-hour chart and an on-chain supply wall may explain why the crowd refuses to turn bearish on Solana price despite the sustained bleed.

Price Weakness Meets a 2.4x Long Bias as a Reversal Pattern Takes Shape

Solana price has dropped almost 5% over the past 30 days while the broader market digested ceasefire uncertainty and capital rotation into equities. The 34% year-to-date decline makes SOL one of the weaker performers among top tokens.

The leverage picture tells a completely different story. On Bybit’s SOL/USDT perpetual market, cumulative long liquidation leverage stands at $308.79 million. Short liquidation leverage sits at $127.02 million. Longs outweigh shorts by roughly 2.4 to 1.

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SOL Liquidation Map
SOL Liquidation Map: CoinGlass

The mismatch becomes less puzzling when the 12-hour chart is considered. SOL is forming an inverse head and shoulders, a bullish reversal pattern. The right shoulder is currently taking shape, and the price is sitting near its base. As long as the pattern remains valid (SOL stays above $76.63), the leveraged crowd appears to be betting that the current dip is the final leg of the right shoulder before a breakout.

Bullish Pattern
Bullish Pattern: TradingView

However, a pattern alone does not justify $309 million in directional bets. The on-chain picture reveals where that conviction is coming from.

17.5 Million SOL Accumulated at the Exact Level Where the Right Shoulder Sits

The cost basis distribution heatmap from Glassnode shows the densest supply cluster sitting between $81.16 and $81.98. Approximately 17.47 million SOL has been accumulated at this range, making it the strongest holder concentration zone on the chart.

The right shoulder’s lowest wick sits at $81.67, directly inside this cluster. The alignment is not a coincidence. Traders and holders who bought between $81.16 and $81.98 are defending their cost basis. Every dip into this zone gets absorbed because selling here would mean realizing losses for a large portion of the supply.

SOL Cost Basis Heatmap
SOL Cost Basis Heatmap: Glassnode

This on-chain wall gives the inverse head and shoulders its structural credibility. The pattern is holding because a real supply base supports it, not just speculative leverage. The longs on Bybit appear to be reading the same signal and positioning accordingly.

However, a $175 million long liquidation cluster sits around $78. If the cost basis wall fails and Solana price drops through $78, the resulting cascade could wipe out the bullish thesis rather quickly.

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Biggest Liquidation Cluster
Biggest Liquidation Cluster: Coinglass

The SOL price levels now determine which outcome plays out.

Solana Price Levels That Decide if the Longs Are Right

SOL trades at $82.20. The first hurdle sits at $84.12 at the 0.236 Fibonacci level. A 12-hour close above $84.12 would suggest the right shoulder was completed earlier and buyers are now pushing toward the neckline.

The neckline zone sits between $86.86 at the 0.5 level and $88.09 at the 0.618 level. A daily close above $88.09 would confirm the breakout and activate the 13.2% measured move projection from the neckline. That targets $98.47-$98.80, per target projection.

On the downside, $81.67 is the right shoulder floor and almost the base of the 17.5 million SOL supply wall. A 12-hour close below $81.67 would deepen the right shoulder and raise questions about the pattern’s validity.

Solana Price Analysis
Solana Price Analysis: TradingView

Below that, $78.38 offers the next technical support. However, the $78 zone is where roughly $175 million in long liquidations are clustered. If SOL reaches that level, forced selling from liquidated positions would likely accelerate the decline and damage the pattern significantly. A break below $76.63 at the head invalidates the inverse head and shoulders entirely.

For now, $88.09 separates a confirmed breakout toward $98.80 from a failed right shoulder that risks triggering $175 million in long liquidations below $78.

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Alibaba leads $290m investment for Shengshu Vidu AI world model

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Markets will soon go back to being driven by AI investment, says Aperture’s Peter Kraus

A mechanical hand is on display at the Robot Mall, world’s first embodied intelligent robot 4S store, on August 13, 2025 in Beijing, China.

Vcg | Visual China Group | Getty Images

BEIJING — Alibaba Cloud is investing in a new type of artificial intelligence designed to better replicate the real world using a different approach from chatbots such as OpenAI’s ChatGPT.

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The shift recognizes the limits of “large language models” trained primarily on text. Instead, developers are starting to focus more on “world models” built on videos and real-life physical scenarios.

To jump on the trend, Alibaba led a 2 billion yuan ($290 million) investment in ShengShu, the startup behind the AI video generation tool Vidu, the company announced Friday. TAL Education and Baidu Ventures also participated in the series B funding round.

The investment comes about two months after ShengShu raised 600 million yuan from Qiming Venture Partners and other backers. The startup declined to disclose its valuation.

ShengShu said the latest funding will support the development of a “general world model” that uses AI to bridge two currently separate domains: the digital world of games and AI-generated video, and the physical world of autonomous driving and robots.

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“ShengShu believes that a general world model, built on multimodal data such as vision, audio, and touch, more naturally captures how the physical world works than large language models,” the three-year-old startup said in a statement.

Markets will soon go back to being driven by AI investment, says Aperture’s Peter Kraus

“We aim to connect perception and action,” Zhu Jun, founder of ShengShu, added in a statement, allowing AI systems to better model and predict real-world behavior consistently.

ShengShu’s latest Vidu Q3 Pro model, released in January, ranks among the top 10 AI models for generating videos from text and images, according to Artificial Analysis.

The company launched Vidu globally months before OpenAI made its now-shuttered Sora tool for AI video generation widely available. Chinese short-video companies Kuaishou and ByteDance have also released similar competing AI tools for generating videos.

World model competition

Alibaba has expanded its investments in related startups.

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The Chinese tech giant and Baidu Ventures last month led a $50 million investment in Tripo AI, a platform that uses AI to quickly generate digital 3D models from photographs. Tripo said it is also moving away from techniques used by language models toward AI tools grounded in physical space and is developing its own world model.

In September, Alibaba also led a $60 million investment in PixVerse, which released an AI world model earlier this year that allows users to direct how a video unfolds while it is being generated.

Alibaba, which got its start in e-commerce, has also released free, open-source AI models for video generation and, in February, launched one for powering robots.

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Shengshu said Friday it has strategic partnerships with companies developing embodied AI — systems such as humanoid robots that interact with the physical world — for use across industrial, commercial and home settings.

World models are critical for robotics because the technology needs more than LLMs to work, Kevin Kelly, co-founder of the U.S. tech magazine Wired, wrote last month on his Substack.

Ultimately, to replicate human intelligence, AI will need three things: reasoning, an understanding of the physical world and continuous learning, Kelly said. While AI for the learning category hasn’t been developed yet, LLM-powered chatbots have created the knowledge element, he said, making world models a key area requiring a breakthrough.

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Mythos AI threat prompts Bessent, Powell to convene bank CEOs for urgent talks

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Mythos AI threat prompts Bessent, Powell to convene bank CEOs for urgent talks

Mythos’ AI scare is real — enough for U.S. regulators to call an urgent meeting and assess what Anthropic’s advanced artificial intelligence model it could mean for banks.

The meeting happened Tuesday, with Treasury Secretary Scott Bessent and Fed Chair Jerome Powell sitting down with Wall Street bank CEOs to discuss possible cybersecurity risks linked to Mythos, people familiar with the matter told Bloomberg.

Participants included chief executives from Citigroup Inc, Morgan Stanley, Bank of America Corp.’, Wells Fargo & Co.’s, and Goldman Sachs Group Inc.’s. All these are designated as systemically important, meaning disruptions to their operations could have global repercussions.

Mythos, an advanced artificial intelligence model developed by Anthropic, is designed to identify and exploit vulnerabilities in software systems when prompted. Unlike typical consumer-facing AI tools, Mythos is geared toward cybersecurity software engineering and cybersecurity tasks. Its specialty is identifying critical software vulnerabilities and bugs, but it can also assemble sophisticated exploits.

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The episode highlights a fundamental change in how regulators are framing AI risk, not merely as a technological challenge, but as a potential catalyst for systemic events.

This has already raised red flags in crypto, where experts are worried that Mythos’ capability of discovering and exploiting zero-day vulnerabilities in real-time at a low cost poses risk to the DeFi infrastructure.

Anthropic, therefore, has taken a cautious approach, releasing the product only for small group of large technology and financial firms under “Project Glasswing.”

Anthropic has previously disclosed that it consulted with U.S. officials ahead of Mythos’ release regarding both its defensive and offensive cyber capabilities. The company is also separately engaged in a legal dispute with the Pentagon, which has designated it a supply-chain risk — a classification Anthropic is contesting in court.

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CIA to Bring in AI Co-workers to Help Catch Spies

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CIA to Bring in AI Co-workers to Help Catch Spies

The US Central Intelligence Agency said it will embed “AI co-workers” directly into its analytics platforms to assist analysts with detecting spies and anticipating hostile moves by foreign adversaries.

“Within the next couple of years, we will have AI co-workers built into all of the agency’s analytic platforms — a kind of classified version of generative AI that will help our analysts with basic tasks,” CIA deputy director Michael Ellis reportedly said on Thursday during an event hosted by the Special Competitive Studies Project in Washington, DC.

According to Politico, Ellis said the AI co-workers would assist intelligence officers with drafting key judgments, testing analytical conclusions and identifying trends in intelligence that the agency gathers from abroad.

However, he said humans would continue to be the ones making the “key decisions.”

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Michael Ellis (right) speaking with Anthony Pompliano (left) about Bitcoin and AI’s role in US national security in May: Source: Anthony Pompliano

The CIA’s AI plans come amid a feud between the US Department of Defense and AI firm Anthropic. Despite having a $200 million contract with the Department of Defense, Anthropic prevented the use of its flagship AI product, Claude, for mass domestic surveillance and fully autonomous weapons.

US President Donald Trump ordered all federal agencies to immediately cease using Anthropic’s technology in March, while the Department of Defense declared Anthropic a supply chain risk.

The parties remain locked in a legal dispute over the designation, with a US appeals court on Wednesday denying Anthropic’s emergency request to temporarily pause the label.

While Ellis didn’t point out Anthropic, he said the CIA “cannot allow the whims of a single company” to constrain its capabilities.

The CIA has already adopted AI for other intelligence tasks, having tested about 300 AI projects last year to “bring new capabilities to our mission,” such as processing large data sets and language translation, Ellis said.

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Ellis also noted that the CIA recently created its first intelligence report with AI while predicting that AI’s role in the agency’s work would continue to grow.

Related: North Korean cyber spies are no longer just remote threats 

A major motivation for the CIA is to stay ahead of China, Ellis said, noting that the once-large gap between the US and China has narrowed significantly.

“Five to ten years ago, China was nowhere near America, in terms of technological innovation,” Ellis said. “That’s just not true today.”

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Ellis likes the transparency of Bitcoin, crypto

In May, Ellis said Bitcoin and crypto were matters of national security, adding that the agency looks at blockchain data to assist with its counterintelligence operations.

“It’s another area of technological competition where we need to make sure the United States is well positioned against China and other adversaries.”

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