Hedge fund Situational Awareness, founded in 2024 by former OpenAI researcher Leopold Aschenbrenner, is reportedly seeking new funding after taking substantial losses during a recent sell-off in artificial intelligence stocks. The Financial Times said the firm has approached investors and lenders for additional capital, and in some cases has offered investors the chance to buy assets from its portfolio.

The fund—tied to a strategy centered on the infrastructure underpinning AI—was reported by the Wall Street Journal to manage roughly $20 billion in assets under management as of June 8. However, the FT reported that the scale of losses and the amount of capital being sought were not disclosed in the discussions it reviewed, which included a July 24 investor letter.

Key takeaways

• Situational Awareness is reportedly raising fresh capital after losses tied to the July sell-off in AI-related equities.
• According to the Financial Times, borrowing amplified the impact of the downturn on the fund’s leveraged positions.
• The fund’s reported AI-infrastructure focus includes trades connected to data centers and power, with past disclosures referencing stakes in Bitcoin mining firms.
• In addition to seeking funding, the firm has reportedly offered some investors the option to purchase portfolio assets.

Why the AI sell-off became a funding story

The immediate catalyst for Situational Awareness’s capital push appears to be the market turbulence that hit AI stock momentum in July. The FT linked the losses to the broader “AI stock collapse” during that rout and emphasized that the fund’s risk profile was made more severe by increased borrowing.

While the FT did not provide a dollar figure for losses or the size of the capital requirement, it reported that Aschenbrenner’s fund had gained 439% after fees through June, as described in the July 24 investor letter. The same letter suggests that strong earlier performance did not prevent a rapid drawdown once AI equities sold off—particularly because leverage can magnify both gains and losses.

That leverage detail matters to investors because it helps explain how a thematic equity thesis—AI infrastructure—can still unravel quickly when valuation compression and liquidity pressures hit the complex simultaneously. The situation also reflects a recurring pattern in crowded “platform” trades: when the market reprices the expected earnings power of AI beneficiaries, funds exposed to those segments may require external capital to stabilize their balance sheets.

What Situational Awareness is betting on

Situational Awareness’s strategy has been described as focused on the physical backbone of AI: the power generation, data centers, and related infrastructure that enable compute-heavy systems. In earlier reporting, Cointelegraph noted that the fund made a notable bet around that infrastructure theme, including investments connected to Bitcoin miners pivoting into AI computing.

Cointelegraph previously pointed to a March filing with the U.S. Securities and Exchange Commission that showed approximately $1.11 billion in positions across seven Bitcoin miner stocks. The stocks cited in that disclosure included IREN, Core Scientific, Riot Platforms, and CleanSpark, among others.

That matters in the current context because it ties the fund’s AI infrastructure thesis to a sector that has its own cycle of operational risk, capital intensity, and market sensitivity. Even if the longer-term narrative is about compute supply, short-term market swings can still create liquidity and valuation pressures for holders of infrastructure-linked equities.

Investors were also offered a chance to buy assets

The Financial Times reported that the fund’s efforts have not been limited to classic fundraising. It said Situational Awareness has offered some investors the option to buy portfolio assets—an approach that can be used when a manager wants to reduce exposure or improve liquidity without immediately selling positions into a weak market.

According to the FT, the account relied on people briefed on the discussions. The report also cited the fund’s July 24 investor letter while noting that the specific amounts involved were not disclosed publicly.

For investors, asset-purchase offers can create a different decision set than a capital raise. Instead of simply assessing whether to contribute more cash, counterparties may need to evaluate the underlying securities at a point in time when market prices may reflect fear or forced selling. That dynamic can produce opportunities for investors willing to underwrite longer-term fundamentals, but it also introduces questions about what happens next if market conditions remain unsettled.

Aschenbrenner’s AGI expectations and the timing

Beyond the immediate funding pressure, the broader storyline includes how closely the fund’s emergence aligned with Aschenbrenner’s public discussion of artificial general intelligence. Cointelegraph previously reported that he authored a series of essays on artificial general intelligence in mid-2024, around the time he launched Situational Awareness, discussing how he believed AGI machines could outpace college graduates by the end of the decade.

Those views help frame why the fund may have been positioned for a sustained build-out of AI-related infrastructure rather than a short-term trade. Yet the funding request underscores an important asymmetry: even a conviction-driven infrastructure thesis can still be pressured by market mechanics—especially when leverage is used to scale returns.

As of publication, Cointelegraph said it contacted Situational Awareness for comment and had not received a response.

What to watch next

Investors watching this situation should focus on two things: whether Situational Awareness secures the capital it seeks without further destabilizing its leveraged positions, and how any asset-buyback offers to investors are priced relative to the market’s ongoing repricing of AI-exposed equities. The next reports—particularly any updates that clarify the scale of losses, borrowing, and proposed restructuring—will determine whether this becomes a one-off liquidity event or a longer process of portfolio adjustment.

Telegram, the messaging platform used by more than 1 billion people worldwide, is facing a major legal challenge in Australia over claims that it failed to stop the spread of terrorism-linked material.

Australia’s online safety regulator, the eSafety Commissioner, launched civil penalty proceedings against Telegram in the Federal Court on Thursday, according to an official statement.

The authority alleged Telegram breached its obligations under the country’s Online Safety Act to address “pro-terror” content by failing to act on multiple user complaints.

The case adds to growing global scrutiny of Telegram’s moderation practices, following legal pressure on CEO Pavel Durov in Russia and France as governments increasingly examine how major online platforms handle harmful content.

Australia alleges Telegram ignored repeated warnings

ESafety said its year-long investigation found that Telegram failed to remove certain unlawful material after becoming aware of it, with some reported content remaining visible for up to three weeks.

The regulator also alleged that Telegram did not take sufficient steps to prevent repeated violations, including removing accounts, channels and groups used to distribute pro-terror material.

According to eSafety, Telegram also failed to detect known extremist content, including footage from the 2019 Christchurch mosque shootings and the 2022 Buffalo mass shooting, before the material was later removed.

Related: Pavel Durov says Telegram to roll out native Gram crypto wallet

The regulator is seeking financial penalties, with violations of Australia’s online safety rules carrying potential fines of up to 54.6 million Australian dollars ($35.8 million).

Telegram has not issued an official statement on the Australian proceedings, but its official X account posted a video captioned “freedom of expression.”

Telegram did not immediately respond to Cointelegraph’s request to comment on this story.

Russia intensifies legal pressure on Durov

Australia’s legal action came a day after Russia’s Federal Security Service (FSB) charged Durov with facilitating terrorist activity and said it had begun procedures to place him on an international wanted list.

Russian authorities alleged that Telegram failed to remove channels, chats and bots that Ukrainian intelligence services, terrorist groups and extremist organizations used to coordinate attacks, recruit operatives and carry out cyber fraud.

Telegram has also not issued an official statement on the latest legal developments in Russia, but posted an image of Durov making a profane hand gesture.

Source: Telegram Messenger

Durov also remains under investigation in France following his August 2024 arrest at Le Bourget Airport. French prosecutors charged him with offenses including complicity in the distribution of illegal content, including material related to organized crime, through Telegram.

Durov has previously criticized what he described as growing threats to online privacy, warning that governments were rolling back protections for the free internet.

“What was once the promise of the free exchange of information is being turned into the ultimate tool of control,” he wrote in an October 2025 post on X.

Magazine: The real reason DeFi projects that survived 2022 crash are shutting down now

Australian authorities are taking Telegram to court over an alleged failure to remove terror-related content, including video of the March 2019 shooting at a Christchurch, New Zealand mosque in which 51 people were murdered, several news outlets reported Thursday.

Julie Inman-Grant, Australia’s Safety Commissioner, said the messaging app founded by Pavel Durov faced a fine of up to $38 million for failing to comply with its obligations under the Online Safety Act, the BBC said.

“This case concerns content linked to some of the most notorious ​acts of known extremist violence in recent history, including material associated ​with the Christchurch and Buffalo terror attacks,” Inman-⁠Grant said in a statement, according to Reuters.

“We reject these allegations and will contest them in court,” a spokesperson for Telegram said in response to Reuters a ​request for comment. Telegram’s anti-terrorism efforts are well-documented, with thousands of ​extremist communities blocked by the platform in 2026 alone, the spokesperson told the news agency.

Telegram, home of many crypto-related discussion groups, hosting project communities, trading groups, bots and blockchain-based mini apps, did not immediately respond to a CoinDesk request for further comment.

Samsung SDS, the IT services arm of Samsung Group, is exploring stablecoin infrastructure, digital asset systems and AI-based payment models with Dunamu, the operator of Upbit, one of the biggest local cryptocurrency exchanges.

Samsung SDS said it is discussing potential cooperation with Dunamu on stablecoin infrastructure, digital asset systems and AI-based payment business models, CEO Lee Jun-hee said during the company’s second-quarter earnings call on Thursday.

“We have already secured differentiated business capabilities in digital asset infrastructure through the Korea Securities Depository’s tokenized securities platform project and through end-to-end validation […] of the full stablecoin process from issuance to settlement,” Lee said. He said he expects the relationship with Dunamu will help Samsung SDS expand in the digital asset infrastructure market.

The news came days after Samsung Electronics unveiled plans to add stablecoin support to Samsung Wallet, broadening the company’s digital asset push.

Strategic investment targets digital finance

In May 2026, Samsung Securities, Samsung SDS and Samsung Card agreed to buy a combined 4% stake in Dunamu, deepening Samsung affiliates’ ties to South Korea’s digital asset sector.

In the latest Q2 call, Lee reportedly said the company’s investment in Dunamu is a strategic move rather than a financial investment, adding that both companies plan to refine potential business models for digital financial infrastructure.

Source: Samsung SDS

“By combining Samsung SDS’s IT services, cloud, and security capabilities with Dunamu’s blockchain expertise, we aim to lead this market,” the Q2 transcript said.

Related: South Korea report proposes stablecoin rules before crypto law

Samsung SDS did not immediately respond to Cointelegraph’s request for comment, while Dunamu declined to comment.

AI growth supports broader expansion

The digital asset initiative comes amid Samsung SDS’ ongoing expansion in AI and cloud services, which helped lift Q2 revenue 5.9% year on year to 3.72 trillion Korean won ($2.6 billion), according to the quarterly earnings presentation.

Cloud revenue increased 17% from a year earlier, with external cloud business revenue jumping 75%, driven by demand for Samsung’s cloud platform and graphics processing unit-as-a-service offerings.

The company also reportedly outlined ambitious plans to expand its AI infrastructure from 110 megawatts today to 230 MW by 2029 and more than 800 MW by 2031, underscoring its broader push to build AI infrastructure alongside digital finance services.

Magazine: Fears of AI-driven DeFi hack epidemic overstated for now — but not for long

Situational Awareness, the hedge fund founded in 2024 by ex-OpenAI researcher Leopold Aschenbrenner, has approached investors and lenders for fresh capital after suffering heavy losses in the recent artificial intelligence stock sell-off, the Financial Times reported Thursday.

The fund, which the Wall Street Journal said had around $20 billion in assets under management as of June 8, has also offered some investors the option to buy portfolio assets, according to the FT, citing people briefed on the discussions and a July 24 investor letter. 

The size of the losses and amount sought were not disclosed. Aschenbrenner’s fund had gained 439% after fees through June, according to the letter, but the FT said borrowing increased the size of the fund’s bets, driving up losses when AI stocks collapsed during July’s market rout. Aschenbrenner also reportedly argued in the letter that the sell-off had created attractive investment opportunities.

Cointelegraph previously reported that the fund had made a big bet in its portfolio around the power and data centers supporting AI, including Bitcoin (BTC) miners pivoting into AI computing. A filing with the US Securities and Exchange Commission in March showed about $1.11 billion in positions across seven Bitcoin miner stocks, including IREN, Core Scientific, Riot Platforms and CleanSpark.

Aschenbrenner wrote a series of essays on artificial general intelligence in mid-2024 around the same time he launched his Situational Awareness fund. In it, he predicted that AGI machines will outpace college graduates by the end of the decade.

Cointelegraph contacted Situational Awareness for comment but had not received a response by publication.

Related: Bitcoin mining’s 2026 reckoning: AI pivots, margin pressure and a fight to survive

This article is produced in accordance with Cointelegraph’s Editorial Policy and is intended for informational purposes only. It does not constitute investment advice or recommendations. All investments and trades carry risk; readers are encouraged to conduct independent research.

Impermanent loss has long been one of the biggest challenges facing liquidity providers (LPs) in decentralized finance (DeFi). While automated market makers (AMMs) have revolutionized decentralized trading, they expose LPs to the risk of earning less than simply holding their assets whenever prices diverge significantly.

As artificial intelligence becomes increasingly integrated into DeFi protocols, many investors are asking an intriguing question:

Can AI finally eliminate impermanent loss?

The short answer is not entirely—but AI can dramatically reduce its impact. Let’s explore how.

---

Understanding Impermanent Loss

Impermanent loss occurs when the price ratio between two assets in a liquidity pool changes after you deposit them.

For example:

• You provide ETH and USDC to a liquidity pool.
• ETH doubles in price.
• Arbitrage traders rebalance the pool.
• You end up holding less ETH and more USDC than if you had simply held both assets.

Although trading fees can offset these losses, they aren’t always sufficient during periods of high volatility.

This is why many LPs hesitate to provide liquidity despite attractive yields.

---

Why Impermanent Loss Exists

Impermanent loss isn’t a bug—it’s a consequence of how AMMs maintain liquidity.

Traditional AMMs like constant-product pools automatically adjust token balances according to mathematical formulas.

These formulas:

• Keep markets liquid
• Allow permissionless trading
• Remove the need for order books

But they cannot predict future prices.

As a result, liquidity providers essentially sell appreciating assets and accumulate depreciating ones automatically.

---

Enter Artificial Intelligence

AI introduces something AMMs have never possessed:

Prediction.

Instead of relying solely on fixed mathematical curves, AI can analyze:

• Historical price behavior
• Market volatility
• On-chain liquidity movements
• Whale wallet activity
• Trading volume
• Cross-chain capital flows
• Social sentiment
• Macroeconomic events

This allows protocols to make smarter liquidity decisions.

---

AI Can Optimize Liquidity Placement

Concentrated liquidity protocols require LPs to choose price ranges.

Selecting the wrong range often leads to:

• Reduced fee generation
• Inactive liquidity
• Greater impermanent loss

AI can continuously monitor markets and recommend—or automatically adjust—the optimal liquidity ranges based on:

• Expected volatility
• Trend strength
• Volume concentration
• Support and resistance zones

Instead of manually repositioning liquidity, AI agents could perform these adjustments in real time.

---

Predictive Risk Management

Machine learning models excel at identifying patterns humans often miss.

Imagine an AI system detecting:

• A surge in exchange inflows
• Whale selling activity
• Rising options volatility
• Negative sentiment across crypto social platforms

The AI could recommend temporarily withdrawing liquidity before significant price swings occur.

After volatility subsides, liquidity could be redeployed.

This proactive strategy reduces exposure to major impermanent loss events.

---

Dynamic Portfolio Allocation

Rather than placing all assets into a single pool, AI can intelligently diversify liquidity across multiple pools.

For example:

• Stablecoin pools during uncertain markets
• ETH/BTC pools during lower volatility
• Emerging token pools when momentum increases
• Yield-generating vaults when volatility spikes

Capital continuously shifts where risk-adjusted returns are highest.

This resembles how institutional portfolio managers rebalance investments—only AI can do it every minute.

---

Adaptive Fee Strategies

Some modern AMMs feature dynamic trading fees.

Instead of fixed fees, AI can estimate:

• Expected volatility
• Arbitrage intensity
• Liquidity demand

The protocol can then automatically increase fees during turbulent periods.

Higher fees help compensate LPs for taking on greater risk.

This doesn’t eliminate impermanent loss, but it can significantly offset it.

---

AI-Powered Hedging

One of AI’s greatest strengths may lie outside the liquidity pool itself.

An intelligent system could automatically hedge LP positions using:

• Perpetual futures
• Options
• Synthetic assets
• Volatility products

For instance:

If AI predicts ETH is likely to experience extreme price movement, it could open a corresponding hedge that offsets potential impermanent loss.

Today, these strategies require sophisticated traders.

Tomorrow, AI agents could execute them autonomously.

---

Reinforcement Learning for AMMs

Researchers are exploring reinforcement learning, where AI continuously learns from market outcomes.

Instead of relying on static formulas, AI-powered AMMs could adapt their behavior based on:

• Trader activity
• Liquidity utilization
• Historical performance
• Market efficiency

Each market cycle provides new data, enabling the system to improve over time.

Eventually, liquidity allocation could become increasingly optimized with every transaction.

---

AI and Intent-Based DeFi

The next generation of DeFi may be driven by intent-based systems.

Instead of manually selecting pools, users simply specify their goals:

• Maximize yield
• Minimize impermanent loss
• Preserve capital
• Earn stable income

AI agents then determine:

• Which protocols to use
• When to move liquidity
• How to hedge positions
• When to rebalance

Liquidity management becomes autonomous rather than manual.

---

The Challenges

Despite its promise, AI cannot eliminate impermanent loss entirely.

Several obstacles remain:

Market Uncertainty

Even advanced AI cannot predict black swan events with certainty.

Unexpected news, protocol exploits, or geopolitical developments can quickly invalidate predictions.

Data Quality

AI is only as effective as the data it receives.

Incomplete or manipulated on-chain data can lead to poor decisions.

Execution Costs

Frequent rebalancing introduces:

• Gas fees
• Slippage
• MEV exposure
• Operational complexity

Sometimes the cost of optimization outweighs the benefits.

Smart Contract Risk

AI strategies still depend on secure smart contracts.

If the underlying protocol is compromised, optimization becomes irrelevant.

---

The Future: AI as a Liquidity Manager

Rather than replacing AMMs, AI is likely to become their intelligent layer.

Future liquidity providers may no longer choose pools manually.

Instead, autonomous AI agents will:

• Monitor markets 24/7
• Rebalance liquidity automatically
• Hedge risky positions
• Optimize fee generation
• Reduce capital inefficiencies
• Continuously learn from market behavior

Providing liquidity could eventually resemble hiring an AI portfolio manager.

---

Conclusion

AI is unlikely to eliminate impermanent loss because the phenomenon is rooted in the mechanics of automated market makers and the unpredictability of financial markets. However, it has the potential to substantially reduce its impact through predictive analytics, dynamic liquidity allocation, automated hedging, adaptive fee optimization, and continuous portfolio rebalancing.

As AI agents become more sophisticated and intent-based DeFi matures, liquidity provision could shift from a passive activity to an actively managed, intelligent strategy. The future may not be one where impermanent loss disappears—but one where it becomes far more manageable, allowing liquidity providers to earn more efficiently while taking on less unnecessary risk.

REQUEST AN ARTICLE

This month, analysts have repeatedly pointed to multiday inflows into the U.S.-listed crypto exchange-traded funds as evidence of the return of institutional demand. Zoom out, though, and the institutional story still looks bleak.

Bitcoin spot ETFs have pulled in just $205 million in net inflows in July, the lowest monthly total on record, according to SoSoValue data. While there are still two trading days left, the figure marks anemic recovery from the heavy red ink of prior months, which saw $2.43 billion exit in May and $4.52 billion in June.

Ether has fared somewhat better. ETH ETFs have attracted $342.85 million in July, almost as much as in April and outperforming bitcoin and other crypto funds. XRP is on track for a fourth consecutive month of inflows, though the sum remains a paltry $13.61 million. Solana ETFs sit at $13.82 million.

Together, the numbers paint a picture of limited institutional appetite at best. Ether’s stronger haul is consistent with its price performance against bitcoin. The Binance-listed ether-bitcoin pair has surged by 11% this month.

The basic multiple-to-Net Asset Value (mNAV) that investors are willing to pay for Michael Saylor’s Strategy has declined by two-thirds over the past two years from 2x to 0.68x.

Exactly 24 months ago, Strategy common stock was worth exactly twice the value of its BTC. For every $1 of BTC the company owned, MSTR traded at $2.

In 2024, there was optimism about Strategy’s ability to positively accrete BTC for shareholders through successful business operations.

As of today, that measure of optimism has declined by exactly two-thirds.

Saylor’s company now holds 843,775 BTC at an average cost of $75,476, uncomfortably higher than the current market below $65,000.

For most of the past two years, its shares commanded a premium to that pile. As that original premium flipped to a discount, the company redefined the term mNAV twice in an attempt to keep it above 1x.

Its latest iteration is holding on by a thread. It read 1.03x yesterday.

New and updated market metrics are live at https://t.co/yIv7IimRdf. As Digital Credit becomes a larger portion of our balance sheet, we’ve sharpened our precision based on investor feedback. This video walks through what’s new and why.
00:00 – Intro to Strategy’s new and updated… pic.twitter.com/ndCoDc9PDW

— Strategy (@Strategy) July 23, 2026

Three definitions for mNAV

Basic mNAV is arithmetic a teenager can do. Divide the company’s market capitalization by the dollar value of its BTC. Above 1x means that investors are paying more for the stock than for the BTC. Below it, less.

BitcoinTreasuries.net, which still runs that original calculation, calculates Strategy’s basic mNAV at 0.64x.

Best to dust that number under the rug.

Strategy’s first attempt to redefine mNAV became enterprise value mNAV. This folded in the value of debt and preferred stock into the numerator alongside the market cap of MSTR, the common stock.

Conveniently, loading liabilities onto the top of a fraction made the result larger. The enterprise value-adjusted mNAV therefore sat above 1x long after the basic one had sunk below 1x, and only crossed below 1x in late June 2026.

Predictably, a new-and-improved version of mNAV arrived in July.

Strategy’s dashboard now begins its calculation from a reserve of roughly $57.7 billion in BTC plus dollars, subtracts $6.8 billion of debt and $15.4 billion of preferred stock, and calls the remaining $35.5 billion a net reserve.

It then divides that so-called net reserve by the share count, compares it against a share price of $95.32, and the multiple lands at 1.04x. Voilà.

Read more: How Michael Saylor replaced ‘bitcoin’ with ‘credit’

Advertisement

Redefinitions didn’t stop MSTR from crashing

Saylor pitched the overhaul on the grounds that “Bitcoin capital markets require a new financial language.”

Strategy CEO Phong Le credited investor feedback for an “upgraded” metric that “establishes a 1x threshold for accretive MSTR issuance.”

The redefinition also orphans the company’s entire back catalogue. Strategy’s glossary advises, “Prior to July 23, 2026, the company’s use of the term mNAV referred to a different metric so references to the company’s mNAV calculated prior to that date are not comparable to the company’s mNAV calculated after that date.”

Every mNAV Saylor has ever tweeted prior to this month is, by the company’s own account, incomparable to the one on the company’s own website today.

Advertisement

The same page concedes that despite the label, “it is not equivalent to ‘net asset value’ or ‘NAV’ or any similar metric in the traditional financial context,” and should be used “only by sophisticated investors who understand its limited purpose and many limitations.”

Saylor himself needed seven minutes to define the old mNAV on stage at BTC Prague in June.

Strategy briefly promised shareholders in July 2025 that it wouldn’t dilute MSTR shareholders below 2.5x mNAV, then sold $14.3 billion of stock beneath that line anyway.

On Wednesday, it was 0.68x, and the metric that produced both figures no longer officially exists.

Advertisement

The price of MSTR — the thing that actually matters to shareholders and cannot be redefined — has declined 38% year to date and 76% over the past 12 months.

Got a tip? Send us an email securely via Protos Leaks. For more informed news and investigations, follow us on X, Bluesky, and Google News, or subscribe to our YouTube channel.