Site language
Ru En
Социальные сети

bitcoinist.com Zcash Bug Could Have Minted Unlimited ZEC Undetected

A critical vulnerability in Zcash’s Orchard shielded pool could have allowed an attacker to create an unlimited amount of counterfeit ZEC without detection, according to a new disclosure from Zooko Wilcox, Jason McGee and security researcher Taylor Hornby. The flaw was discovered on May 29, remediated through an emergency ecosystem response completed by June 2, […]

forklog.media OQC, JPMorgan, and AMD to Launch Quantum AI Research Data Center

OQC, JPMorganChase, and AMD announced the launch of a research partnership program in London based at a dedicated Quantum-AI data center. The facility will be used to explore quantum and hybrid computing within financial sector tasks. The platform will integrate the OQC GENESIS quantum system with AMD's infrastructure for AI and classical computing. The ecosystem will serve as a tool for simulation, optimization, language model development, and benchmarking. The partners aim to test quantum approaches for optimizing financial portfolios. A separate focus will be the development of specialized AI models designed to enhance the performance of quantum circuits. The parties also plan to investigate whether quantum-enhanced LLM can accelerate the discovery of new algorithms for financial tasks, and what role classical computing will play in creating scalable, fault-tolerant quantum algorithms. OQC CEO Gerald Mullally emphasized the need to move from "isolated experiments" to secure computing environments for corporate clients. AMD CTO Mark Papermaster highlighted that progress at the intersection of quantum computing and AI requires tightly integrated platforms with quantum systems, AI infrastructure, and HPC. In June, Japanese holding Hamamatsu Photonics, its subsidiary NKT Photonics, and startup Yaqumo signed a memorandum of understanding for the joint development and commercialization of photonic systems intended for cold atom quantum computers.

forklog.media The Bitcoin Hayek Didn’t Ask For

In 1999, economist Milton Friedman — a Nobel laureate and the leading voice of monetarism — described something that didn’t yet exist. In an interview he suggested the internet lacked only reliable electronic cash that would let one person send money to another without revealing their identities. Ten years later, an anonymous developer using the pseudonym Satoshi Nakamoto launched Bitcoin — a peer-to-peer system that did exactly that. The monetarist was right. The irony is that Friedman was about the last person the industry expected to seed such an idea. He’s remembered as a defender of a central bank, albeit one bound by a strict monetary rule. The community instead cast another economist — his intellectual opponent, the Austrian Friedrich Hayek — as Bitcoin’s ideological father. That’s the first crack in crypto’s usual genealogy. Digital money had several prophets — and they disagreed with one another. A Common Denominator What made Hayek a convenient figurehead? In 1976 he published Denationalisation of Money (in Russian, “Private Money”). The thesis was radical: the state’s monopoly on issuance is harmful; the right to issue money should be given to the market. Let private issuers compete, and let people choose the currency they trust. Friedrich August von Hayek. Source: Wikimedia.  Digital gold seems to answer that thesis: no central bank, issuance set by code rather than a bureaucrat’s will, a ledger that’s open and auditable. In a blog post by Colin Wu, Bitcoin is described as a technological “trustless order” — a system where mathematics and protocol replace the intermediary. At this level, Hayek and Satoshi are saying the same thing: money doesn’t need the state; rules that can’t be broken are enough. It’s tempting to stop there — the first cryptocurrency as the Austrian’s dream come true. But open the book, and the construction starts to fall apart. A 1970s Foundation, With Caveats The industry likes to trace Bitcoin’s intellectual roots to the mid-1970s — as if the key breakthroughs all happened then. Part of that picture is true; part is a convenient fit. Cryptography did have a 1976 breakthrough. Whitfield Diffie and Martin Hellman published “New Directions in Cryptography” and introduced public-key cryptography: the public key is shared freely, only the private key remains secret.  Later it emerged that the same solution had been presented in the early 1970s at Britain’s GCHQ by James Ellis, Clifford Cocks and Malcolm Williamson — but their work remained classified. In other words, the foundations of future “anti-state money” were first laid by government cryptographers. The theory of distributed systems doesn’t fit the mid-’70s: the Byzantine Generals problem was formulated by Leslie Lamport and coauthors only in 1982. Their work is essential for digital gold — but not for this chronology. It’s also telling whom Satoshi actually cited. The Bitcoin white paper bibliography lists neither Hayek, nor Diffie, nor Lamport. But Stuart Haber and Scott Stornetta appear as coauthors on three of eight sources — their hash-chain timestamping system is a direct prototype of a blockchain.  The industry tells one lineage; Satoshi’s footnotes point to another. Infographic: ForkLog. Stability vs. Scarcity Open “Private Money” and the first contradiction appears immediately. The Austrian didn’t call for fixing the money stock — he wanted the opposite: the issuer should actively manage supply to keep purchasing power stable. For Hayek, competition is won not by the rarest currency but by the most stable — depreciation hurts creditors, appreciation hurts debtors, and people choose the instrument with predictable purchasing power. Bitcoin is built the other way around. Its issuance is set once and for all: 21 million coins, the block subsidy halves every four years, and issuance eventually stops (around 2140). Halving calendar. Source: Bitbo. Satoshi in the white paper explicitly compared this to gold mining, and called the end state “free of inflation.” There’s no manager to align supply with demand. There’s a rigid schedule — and a price that absorbs all demand swings. The result is volatility — which the Austrian saw as a sign of bad money. In Bitcoin’s early days it was extreme — the rate could soar and plunge by tens of percent within weeks. In recent years the amplitude has eased notably: by 2025, volatility fell roughly in half versus 2021 and was lower than in some “Magnificent Seven” stocks such as Tesla and Nvidia.  Historical Bitcoin volatility vs. Tesla and Nvidia, % annualized. Source: Charles Schwab.  But even reduced swings are incompatible with the ideal of money so steady you don’t have to think about it. For the Austrian school, money’s key function is everyday exchange. From that perspective, Bitcoin should have lost the competition rather than led the market. What the industry hails as “digital gold” is, in this frame, more a diagnosis. And that concept isn’t Hayek’s. Its foundation is scarcity, not stability.  In 2005 Nick Szabo described Bit Gold — an asset whose value rests on “unforgeable costliness”: creating a coin requires real computation, and that work can’t be faked.  Szabo took the cost mechanism from Adam Back: his 1997 Hashcash forced an email sender to burn CPU time so spam would be uneconomic. Satoshi combined those parts and produced money secured not by an issuer’s promise but by expended energy. The scheme works — but it’s the architecture of “gold,” not the managed currencies the Austrian described. He saw a flaw in precious metals: their supply can’t be flexibly tuned to the economy’s demand for money. The paradox runs deeper. The hard rule is closer not to the Austrian school but to its foil. Milton Friedman proposed “chaining” the central bank to a fixed rule — grow the money stock at a steady 3–5% a year, regardless of the business cycle. Portrait of Milton Friedman. Source: Wikimedia.  Bitcoin took that idea to the extreme: there is a rule — no improvisation, and no manager either. On monetary policy, it’s closer to Friedman. The difference is that the monetarist wanted to keep a central bank, while code abolished it altogether. Bitcoin advocates will counter: a fixed cap is “sound money,” protection against inflationary arbitrariness — the Austrian dream. Economist Saifedean Ammous developed that argument: in his “hard money” framework, Bitcoin even surpasses gold because its supply can’t rise with demand.  There’s some truth here — Hayek and Satoshi agree in rejecting the state monopoly. But they diverge on means: the Austrian fought inflation through stability; Bitcoin through scarcity. And scarcity delivers not constancy, but volatility.  Hayek sought money you don’t notice because its value doesn’t change. Digital gold became an asset whose price is all anyone talks about. Pluralism vs. Monopoly The second contradiction is obvious: the Austrian wanted many competing currencies; the industry ended up with one dominant. By May 2026, Bitcoin accounts for about 57% of the entire digital-asset market — down from the June 2025 peak of 65%, but still the system’s anchor. It looks like a new monopoly, private rather than state. But the charge is weaker than it seems. Hayek didn’t insist on endless variety. In the 1978 updated edition of “Private Money,” he allowed that competition would narrow the field to one or two stable standards — the leader is chosen by the market, not decree. A small set of issuers didn’t frighten him. The issue isn’t that the market chose one leader, but which one. Hayek expected the most stable currency to prevail. The winner is an asset valued for the opposite — for appreciation and scarcity, not stability. It settled into the role of “digital gold” and a speculative bet, ceding everyday money. In practice, Hayek’s scenario did materialize — but outside Bitcoin’s ecosystem. The market did pick stable private money for payments: these are stablecoins like USDT and USDC.  By 2026 their combined market capitalization exceeded $316 billion, and by value transferred, “stable coins” have long surpassed the first cryptocurrency. Private issuer, competition for stability — almost verbatim Hayek. 30-day value transferred in stablecoins reached $3.7 trillion. Source: Artemis. Monthly Bitcoin value transferred. Source: The Block.  Almost — because a stablecoin’s steadiness rests on its peg to the dollar. That is, to the money of the very state whose monopoly the Austrian sought to abolish. The market replicated his mechanism and inverted the meaning: the industry’s most “Hayekian” money is secured not by rejecting the central bank, but by its liabilities. And neither outcome delivered a clean Austrian victory. Bitcoin conquered the market at the price of the very instability Hayek saw as a vice. Stablecoins brought stability, but borrowed it from the dollar. Money free of the state and chosen for its steadiness remains a thought experiment. Anonymity Isn’t Hayek Bitcoin’s genealogy holds two different ideas of freedom, and Hayek accounts for only one. The Austrian was concerned with money’s independence from the state, not the payer’s anonymity. The right to be unseen came from another source — the cypherpunks. The path to anonymous payments was opened by David Chaum. As early as 1982, he proposed the “blind signature” — mathematics that allows a bank to validate a coin without seeing its denomination or owner. From it Chaum built DigiCash — the first attempt to make untraceable electronic cash. The aim was precisely confidentiality: money that leaves no traces. The company went bankrupt in 1998. Anonymous money was ahead of its time and demand, but it failed commercially. The idea remained. Timothy May made it into an ideology. His 1988 “Crypto Anarchist Manifesto” carried an explicit an ironic reference to the Communist Manifesto — and the thesis wasn’t the Hayekian “let the market issue money,” but “let cryptography blind the state.” Anonymous transactions, markets beyond government control, reputation instead of a passport — that was his horizon. Hal Finney built the bridge to Bitcoin. In 2004 he assembled RPOW — a system of reusable proofs of work, a direct predecessor of mining; Satoshi sent him the first-ever bitcoin transaction. Finney tied together cypherpunk privacy, the Proof-of-Work line, and the network’s launch. Then comes the central irony. Bitcoin, celebrated as a cypherpunk victory, violated their core value. Chaum engineered untraceability — the first cryptocurrency is the opposite: every transaction is visible to everyone, forever. Satoshi acknowledged this in the Privacy section of the white paper: protection here rests only on the public key not being tied to a name. That’s pseudonymity, not anonymity. In essence, Bitcoin is the most transparent money in history — the opposite of Chaum’s design. Tellingly, May himself was disillusioned. Shortly before his death in 2018 he remarked: exchanges with passport checks, KYC requirements and frozen accounts are hardly what Satoshi intended. The prophet of crypto-anarchy didn’t recognize his idea in what the industry became. Thus “digital freedom” turns out to be a collage of incompatible parts: for Hayek it meant money independent of the state; for Chaum and May, people invisible to it. They were fused into one myth, but Bitcoin didn’t fully deliver on either promise: it became neither the Austrian’s stable money nor the cypherpunks’ untraceable cash. The slogans aligned — the substance diverged. Debate, Not Fulfillment So what remains of the lineage Bitcoin is routinely assigned? The common denominator is real. Hayek, Chaum, May and Friedman — for all their differences — aimed at one thing: to remove money from the state’s exclusive control. Bitcoin inherited that frame, which is why it’s so easily cast as each of their heirs. Beyond that, the overlap ends. The Austrian wanted a stable currency managed by a live issuer — Bitcoin delivered a hard cap and volatility. Hayek expected the most reliable money to win — a speculative asset won. Chaum and May built untraceable cash — the first cryptocurrency made the ledger public. Each would recognize a trait of his own and reject the whole. Infographic: ForkLog. That’s the paradox. Bitcoin prevailed not because it executed someone’s program, but because it didn’t fully execute any. It took from Hayek distrust of the state, from the Chicago School a hard rule, from the cypherpunks cryptography, and assembled from those parts something none of them designed. Friedman’s 1999 prediction came almost verbatim true: reliable electronic cash for peer-to-peer transfers arrived a decade later. But the result matched none of the thinkers’ blueprints — neither the monetarist’s managed money with a preserved central bank, nor the Austrian’s stable private currency, nor the cypherpunks’ anonymous cash. They guessed the future, but it wasn’t built to anyone’s plan. And perhaps that’s the strength. The first cryptocurrency rests not on anyone’s convictions, but on rules anyone can verify. Whether the Austrian, the monetarist or the cypherpunks would see their dream in it is irrelevant to the network’s operation. The Bitcoin Hayek didn’t ask for doesn’t need his approval.

bitcoinist.com US Senators Press Bank Regulators For ‘Fair’ Crypto Capital Rules

A group of Senate Republicans is pressing bank regulators to build on recent regulatory progress by creating a clearer capital framework for crypto activities and asset treatment. Related Reading: UK House Of Lords Urges BoE To Ease Stablecoin Rules Over Competitiveness Concerns US Senators Call For Clear Crypto Capital Rules On Thursday, Senate Banking Subcommittee […]

cryptobriefing.com House lawmakers unveil draft for national AI framework that could reshape decentralized AI projects

The draft's federal preemption could centralize AI regulation, impacting innovation dynamics and potentially influencing decentralized AI projects. The post House lawmakers unveil draft for national AI framework that could reshape decentralized AI projects appeared first on Crypto Briefing.

forklog.media Deribit Warns of Bitcoin Sell-Off Risk Below $60,000

A drop in Bitcoin below $60,000 could intensify selling due to mechanical sales and liquidations, according to Deribit. Analyst Jean-David Pequinot noted that some institutional buyers entered the market in the $60,000–$67,000 range and are now nearing breakeven. More than $1.2 billion in open interest is concentrated in put options at the $60,000 strike, which could prompt market makers to engage in hedging sales of spot or futures.

cryptobriefing.com Fed’s Mary Daly says monetary policy is ‘in a good place’ but won’t predict what comes next

The Fed's cautious stance on future policy highlights the need for vigilant economic data analysis, impacting market strategies and risk assessments. The post Fed’s Mary Daly says monetary policy is ‘in a good place’ but won’t predict what comes next appeared first on Crypto Briefing.

news.bitcoin.com Largest Solana Treasury Moves $32M in SOL to Coinbase Prime While Sitting $1.13B Underwater

Forward Industries, the largest corporate holder of SOL, has moved 455,784 SOL worth about $31.87 million to Coinbase Prime, its first major transfer in a month, all while sitting roughly $1.13 billion underwater on the position. A $32 Million Transfer Reignites Sell-off Fears Forward Industries, the Nasdaq-listed firm that built the largest corporate SOL treasury, […]

themerkle.com Hyperliquid Strategies Buys $95M Worth of HYPE in Seven Days While Barely Touching Its Cash

Hyperliquid Strategies, the decentralized autonomous trust behind the $PURR ticker, just pulled off something that turned heads across the crypto trading community. The fund bought 1.4 million HYPE tokens worth roughly $95 million over the last seven days, and somehow, its cash position only dropped by $15.5 million. That gap between what they spent on HYPE and how little cash they actually lost is the story here. It tells you exactly how the fund is financing its aggressive accumulation, and why the structure it operates under gives it a compounding advantage that keeps feeding itself as long as HYPE stays The post Hyperliquid Strategies Buys $95M Worth of HYPE in Seven Days While Barely Touching Its Cash appeared first on The Merkle News.

themerkle.com Jupiter Launches Forecast, Solana’s First Fully Native Prediction Market With Competing Market Makers

Jupiter is not done building. The team behind one of Solana’s most used trading platforms just announced Forecast, a fully native prediction market that plugs directly into the existing Jupiter ecosystem, and the way it handles liquidity is unlike anything currently live on Solana. The announcement landed on Jupiter Exchange’s official X account and immediately got the attention of traders, market makers, and DeFi builders across the Solana community. Forecast is not just another prediction market, it introduces a competing market maker model that has the potential to change how prediction markets execute trades on the network entirely. Jupiter is The post Jupiter Launches Forecast, Solana’s First Fully Native Prediction Market With Competing Market Makers appeared first on The Merkle News.

themerkle.com Arthur Hayes Dumps $18 Million in HYPE and NEAR

Arthur Hayes does not exit quietly. The BitMEX co-founder has liquidated his entire positions in Hyperliquid’s HYPE token and NEAR Protocol, offloading roughly $18 million worth of crypto in a single move and then told everyone exactly why he did it. The market heard him loud and clear. HYPE is down 5.8% and NEAR has collapsed 19.5% in the immediate aftermath, with on-chain data confirming the scale of what just hit the order books. This is not a routine portfolio rebalancing. Hayes is making a macro call, and he is putting his trading history behind it. The Sell: 247,000 HYPE The post Arthur Hayes Dumps $18 Million in HYPE and NEAR appeared first on The Merkle News.

forklog.media Anthropic Warns of AI Self-Improvement Risks

Members of the Anthropic team are increasingly delegating a significant portion of new model development to AI systems. The company identified this as a sign of approaching recursive self-improvement. According to internal data, more than 80% of the code for the company's current products was written by Claude. In the second quarter, the amount of code per engineer increased eightfold compared to 2024. Source: Anthropic Institute. Marina Favaro, head of the Anthropic Institute, and company co-founder Jack Clark wrote that with sufficient computing power, this trend could lead to a system capable of "designing and developing its successor entirely autonomously." "We have not yet reached the point of no return, and recursive self-improvement is not inevitable. But it may occur sooner than most institutions are prepared for," the experts emphasized. Benchmarks and Metrics In April, Claude completed over 800 corrections — according to the supervising engineer, it would have taken a human four years to accomplish this. In open tasks, the share of successful sessions by Claude increased to 76% in May 2026 — a 50 percentage point rise over six months. Source: Anthropic Institute. Anthropic stated that the duration of tasks that AI can reliably perform independently doubles approximately every four months (compared to the previous seven). In a task to accelerate the training of a small AI model, Claude Opus 4 in May 2025 provided an average speed increase of about three times, while Mythos Preview in April 2026 achieved approximately a 52-fold increase. Source: Anthropic Institute. During internal tests, the Mythos Preview model demonstrated the ability to solve research tasks in AI safety. Over 800 hours, a group of agents closed 97% of the problem gap in an experiment, while two human researchers managed only 23% of the volume in a week. New Bottlenecks Despite successes in code writing, humans still hold an advantage in "research judgment" and setting strategic goals. Anthropic believes that in the near future, the role of developers will shift from writing lines of code to deeply reviewing the results of neural network work. Human verification may become the main bottleneck in the speed of developing new models. The company also suggested that it might be beneficial for the world to have the ability to slow down or temporarily halt the development of advanced AI systems, allowing societal institutions and alignment research to keep pace with progress. Concurrently, startup representatives warned that unilateral slowing could backfire on those who decelerate — less cautious players could close the gap. Without a global coordination mechanism, safety decisions will have to be made under competitive and geopolitical pressure. In May, Anthropic published its first report on Project Glasswing — a program for identifying vulnerabilities using the Claude Mythos model. In the same month, the company released Claude Opus 4.8 and separately introduced a dynamic workflow feature for Claude Code.

btcmanager.com Stage 6 expires this weekend: Secure an allocation in 2026’s top crypto presale before missing it like the ICP ICO

Investors assess early-stage crypto opportunities as DOGEBALL gains attention alongside lessons from past launches. Missing out on early-stage blockchain opportunities is one of the most common regrets in the digital asset space. The investors who achieve life-changing returns are rarely…

bitcoinist.com Bitcoin Miner Inflows Hit Highest Level Since February Crash: Capitulation Or Distribution?

Bitcoin has experienced significant selling pressure following a 16% drop since Monday — a decline that has shaken the confidence built during the recovery from the April lows and forced participants to reassess where genuine structural support exists in the current market structure. Against that backdrop, CryptoQuant data has identified a specific development in the […]

btcmanager.com 2026’s 6 leading cloud mining platforms as Bitcoin mining enters a new era

Cloud mining regains momentum as platforms like SHRMiner simplify access to digital asset participation. The cryptocurrency market has changed dramatically over the past year. While Bitcoin continues to attract long-term holders, rising mining difficulty, increasing electricity costs, and expensive ASIC…

news.bitcoin.com Arthur Hayes Dumps His Entire ZEC Bag After Orchard Exploit, Prices Down Nearly 50%

Arthur Hayes has sold his entire ZEC position following the Zcash Orchard pool exploit, declaring that “the Holy Trinity is dead.” The high-profile exit has deepened a selloff that has knocked ZEC down nearly 47% over the past day. A High-Conviction Trade Unwinds BitMEX co-founder and one of crypto’s most-followed macro voices, Arthur Hayes told […]

blockonomi.com Whale BTC Deposits Surge as Bitcoin’s June Decline Deepens

TLDR: Whale BTC inflows on Binance peaked at 8,200 BTC on June 2nd, the highest since February’s drop. Monthly average whale inflows doubled from 1,200 BTC to over 2,800 BTC within a matter of weeks. MicroStrategy and ETFs absorbed over 1.24 million BTC since March 2024, yet price remains pressured. Bitcoin’s average investor cost basis [...] The post Whale BTC Deposits Surge as Bitcoin’s June Decline Deepens appeared first on Blockonomi.

cryptobriefing.com Jamshid Ghomi arrested for allegedly smuggling US tech equipment to Iran’s nuclear and military sectors

The arrest highlights the critical need for stringent enforcement of tech export controls to prevent unauthorized access by sanctioned nations. The post Jamshid Ghomi arrested for allegedly smuggling US tech equipment to Iran’s nuclear and military sectors appeared first on Crypto Briefing.

bitcoinist.com Zcash Bug Could Have Minted Unlimited ZEC Undetected

A critical vulnerability in Zcash’s Orchard shielded pool could have allowed an attacker to create an unlimited amount of counterfeit ZEC without detection, according to a new disclosure from Zooko Wilcox, Jason McGee and security researcher Taylor Hornby. The flaw was discovered on May 29, remediated through an emergency ecosystem response completed by June 2, […]

cryptopotato.com Critical Zcash Vulnerability Revealed by Founder: Key Details and ZEC Outlook

Zcash’s native cryptocurrency, ZEC, crashed by roughly 45% today, as the market reacted to a notable disclosure from the protocol’s founder, Zooko Wilcox, and other key ecosystem figures. The post explained that researchers had recently found and patched a critical vulnerability associated with Zcash’s Orchard shielded pool – one that could have allowed an attacker […]

cryptopotato.com LBank Surpasses 25 Million Users Worldwide as AFA Partnership Continues to Drive Global Growth

[PRESS RELEASE – Singapore, Singapore, June 5th, 2026] Global cryptocurrency exchange LBank today announced that its registered user base has surpassed 25 million worldwide, marking a major milestone in the exchange’s global expansion journey. The achievement comes nearly one year after LBank became the Regional Sponsor of the Argentine National Team, a partnership that has […]

forklog.media US Proposes Restricting Prediction Markets for Congress Members

Bryan Steil, Chairman of the House Administration Committee, stated that the insider trading bill H.R. 7008 should include provisions regarding prediction markets like Polymarket and Kalshi. The updated rules propose a complete ban on the use of such platforms by Congress members, their spouses, and children, and also include fines of $2000 or 10% of the transaction amount with the confiscation of realized profits.

blockonomi.com Coinbase (COIN) Partners with Better Mortgage to Launch America’s First Bitcoin-Backed Home Loan

Coinbase (COIN) and Better Mortgage have completed the first U.S. Bitcoin-backed home loan approved by Fannie Mae, with nationwide launch coming in 2026. The post Coinbase (COIN) Partners with Better Mortgage to Launch America’s First Bitcoin-Backed Home Loan appeared first on Blockonomi.

cryptobriefing.com Iain Dunning: The exponential pace of AI is reshaping market predictions, current dynamics resemble gambling, and the complexity of models challenges traders’ interpretability | Odd Lots

AI advancements are transforming trading strategies, raising questions about sustainability and profitability in market predictions. The post Iain Dunning: The exponential pace of AI is reshaping market predictions, current dynamics resemble gambling, and the complexity of models challenges traders’ interpretability | Odd Lots appeared first on Crypto Briefing.

blockonomi.com South Korean Police Opens First Criminal Probe into Domestic Polymarket Users Over Illegal Gambling

TLDR: South Korean police launched their first-ever criminal investigation into domestic Polymarket users for illegal gambling. Local users face fines of up to 10 million won under Article 246 of South Korea’s Criminal Act. Bets on South Korea’s June 3 local elections reached hundreds of billions of won on Polymarket. Polymarket remains fully accessible in [...] The post South Korean Police Opens First Criminal Probe into Domestic Polymarket Users Over Illegal Gambling appeared first on Blockonomi.

news.bitcoin.com HYPE Whales Pull $64.9M off Exchanges as One Trader’s $46.5M Short Bet Backfires

Hyperliquid whales are accumulating, with one wallet withdrawing $64.9 million worth of HYPE from exchanges in three days. Meanwhile, a trader who lost $46.5 million shorting the token flipped long and is down another $840,000. Whales Quietly Stack HYPE Large holders are pulling HYPE off exchanges at a steady clip, suggesting accumulation rather than an […]

forklog.media Grayscale Describes Strategy’s Bitcoin Sale as a ‘Stress Test’

Grayscale referred to Strategy's first Bitcoin sale in a long time as a 'stress test' of its financial model. The small transaction to 'unload' reserves triggered a negative market reaction and cast doubt on the aggressive accumulation strategy. On June 1, the firm sold 32 BTC and also liquidated its own shares worth $128 million. Amid this, the price of the leading cryptocurrency fell by 16%, despite the sale's minor volume compared to the company's total reserve of 843,706 BTC. Grayscale's Director of Research, Zach Pandl, noted that by June 5, the company's stock (MSTR) had dropped 12.8%, reaching a two-month low of $126. Grayscale also pointed out the decline in STRC with a floating rate. The paper was intended as an instrument priced around $100 with an 11.5% dividend, but it is currently trading at about $95. If Strategy raises the dividend to close the discount, the company's financial obligations will increase—potentially prompting further sales of digital gold, adding pressure to the market. Source: Grayscale. Grayscale believes that at current STRC and MSTR levels, Strategy's ability to continue aggressive Bitcoin accumulation is limited. Pandl added that in the long term, the ecosystem benefits from a broader distribution of Bitcoin across diversified corporate balances, rather than concentration in companies increasing their position through debt leverage. SignalPlus partner Augustin Fan commented to Cointelegraph that it is becoming harder for investors to maintain a bullish stance amid the STRC discount. Meanwhile, CoinEx's chief analyst Jeff Ko believes that transitioning to more flexible portfolio management will help Strategy more effectively control risks, rather than adhering to an accumulation strategy in all market conditions. In May, Strategy repurchased its own convertible bonds maturing in 2029 for $1.5 billion. The transaction was completed at a discount of about 8% to the nominal value.

blockonomi.com ZEC Price Crashes 48.4% as Orchard Pool Bug and Arthur Hayes Exit Trigger Mass Liquidations

TLDR: ZEC dropped 48.4% to $272.79 on Binance following the Orchard pool soundness bug discovery. Total ZEC liquidations hit $81.91M in 24 hours, with $70.55M from long positions alone. Arthur Hayes sold his entire ZEC position after the Orchard exploit news broke publicly. A ZEC whale holding $174M saw holdings lose over $70M in value [...] The post ZEC Price Crashes 48.4% as Orchard Pool Bug and Arthur Hayes Exit Trigger Mass Liquidations appeared first on Blockonomi.

forklog.media What Are Quantum Supremacy, Utility and Advantage?

What Is Quantum Supremacy and When Was It Achieved? Theoretical physicist John Preskill coined the term “quantum supremacy” in 2012. In scientific terms, it marks a fundamental computational threshold: the point at which a quantum device solves a specific task in acceptable time while a classical supercomputer, though in principle capable, is so inefficient that the result would take years, centuries or even millennia. Early demonstrations were strictly laboratory exercises because devices were highly susceptible to computational noise (errors). To prove the technology’s viability under such conditions, engineers turned to synthetic algorithms — for example, sampling from random quantum circuits (RCS). These tests had no direct commercial value, but they served a critical purpose: they recorded quantum architecture’s superiority over classical machines in a narrow niche and opened the industry’s path toward useful applications. In 2019, Google’s research team first claimed quantum supremacy. Its 53-qubit superconducting Sycamore processor completed an RCS task in 200 seconds. The researchers said the then-most-powerful classical supercomputer, Summit, would have needed about 10,000 years. IBM disputed the announcement. The company said Summit could handle the task in just two and a half days. By efficiently leveraging not only processors but also the supercomputer’s vast RAM and disk storage, IBM argued, one could sidestep the apparent exponential complexity. Chinese research teams later reported crossing the threshold on two different physical architectures: the photonic quantum computer Jiuzhang, which uses photons for boson sampling, and updated superconducting systems with a QPU, Zuchongzhi 3.0. In March 2025, the system generated one million samples in just a few minutes. According to the Chinese team’s estimates, exact simulation of this specific process would take Frontier, the world’s most powerful classical supercomputer, about 6.4 billion years. While tasks like RCS lack practical or commercial utility, they play a vital role: they prove that as the number of high-quality qubits grows, quantum power becomes insurmountable for the von Neumann classical architecture. What Is Quantum Utility? At the stage of quantum utility, quantum computers stop being laboratory record-setters and become tools for scientific research. They don’t yet outpace supercomputers across all metrics, but they can already probe physical problems at scales inaccessible to direct classical simulation. Quantum utility is the ceiling for the NISQ era. For the next stage — FTQC — engineers prioritize suppressing errors (error mitigation) over merely adding qubits. The method extracts accurate results from “noisy” systems before they lose their quantum state. Error mitigation must be strictly distinguished from full-fledged hardware error correction, the hallmark of the next historical phase. The concept was proposed and demonstrated by IBM in 2023, effectively launching the period of quantum utility, which continued in 2026. In the experiment, the 127-qubit Eagle processor modeled properties of complex magnetic materials. Using noise-mitigation techniques, the processor produced results that could not be computed exactly by classical methods. To realize quantum utility, teams often deploy hybrid architectures that use a QPU, a CPU and a GPU together — a balance that efficiently allocates workloads. In May 2026, IBM, Cleveland Clinic and Japan’s RIKEN, using such heterogeneous computation, simulated a giant protein–ligand complex of 12,635 atoms. The task ran on two quantum computers and two classical supermachines. What Is Quantum Advantage? The media often uses “quantum supremacy” and “quantum advantage” as synonyms, but in scientific and business contexts they mark different stages in the technology’s evolution. Supremacy is a laboratory proof of quantum hardware’s fundamental computational power. Advantage is broader: it is achieved when a device solves a concrete applied task faster, cheaper or more accurately than the best classical supercomputer. The key criterion is practical and economic viability. A business doesn’t need a complex, expensive QPU if a conventional cluster can simulate a molecule for a new drug or calculate the properties of a super-strong alloy in comparable time and budget. Achieving quantum advantage, alongside FTQC, is a primary goal for leading technology companies and startups over the next three to four years. Examples from roadmaps: IBM. By the end of 2026, the company will demonstrate “the first examples of practical quantum advantage” using the Nighthawk processor. It will be able to run deep circuits of 7,500 gates in tight hybrid coordination with classical supercomputers. By 2029, developers aim to release a full-scale FTQC system operating 200 logical qubits — Starling; QuEra Computing. The neutral-atom specialist plans to ship a system with 100 fault-tolerant logical qubits in 2026. Engineers estimate this will be enough to begin tackling the first commercially meaningful problems in chemistry and materials science that are out of reach for classical computers; Quantinuum with Microsoft. The company intends to hit business targets by 2030. Its main bet is the fifth-generation Apollo quantum computer. The trapped-ion system is slated to deliver hundreds of logical qubits with deep error correction, integrated with AI platforms and Microsoft Azure Quantum cloud infrastructure; Google Quantum AI. After presenting the 105-qubit Willow processor in late 2024, the company made progress in error mitigation. The goal is to complete a large-scale quantum computer with hardware error correction, capable of reliably processing data for commercial tasks, by the end of this decade. IBM roadmap. Source: IBM. Where Are Quantum Computations Most Effective? The first real results are emerging in disciplines that require simulating complex quantum-mechanical systems. Classical processors are inefficient at calculating molecular interactions: each additional electron drives exponential data growth. By contrast, quantum devices model molecular structures natively, following the laws of quantum physics. The industry is moving from lab tests to solving the toughest problems of the physical world. Key application areas where quantum utility is expected or being tested: chemistry and industrial catalysis. Today, fertilizer production consumes about 2% of all generated energy. Quantum algorithms are used to model the nitrogenase enzyme to create new, revolutionary catalysts. That would enable ammonia synthesis at room temperature, radically cutting global energy use; materials science. Leading corporations are applying quantum computing power to discover new chemical structures. Core goals include lightweight, ultra-dense solid-state batteries for EVs and high-temperature superconductors that could transmit electricity with zero loss; pharmacology and biophysics. Drug discovery could avoid lengthy, costly blind screening. In theory, quantum technology will enable targeted protein design and ultra-precise prediction of how a new molecule binds to a target virus or cancer cell in the human body; fundamental science. Quantum systems are already used in theoretical physics. Researchers simulate the behavior of exotic states of matter, wormholes and materials at the quantum level — work that could lead to discoveries classical science doesn’t yet foresee. Where Are Quantum Computations Hard to Achieve? Business is preparing for the quantum era: major logistics operators such as DHL and financial conglomerates including HSBC and JPMorgan are testing process-optimization algorithms. But in the scientific community these fields are officially recognized as the most challenging and farthest from real quantum advantage. For most combinatorial problems — the classic traveling-salesman problem or portfolio optimization — the best quantum algorithms (QAOA or Grover’s algorithm) deliver only a quadratic speedup. Beating silicon would require millions of ideal, fault-tolerant logical qubits. Other areas where marketing outpaces scientific progress: quantum machine learning. For a quantum neural network to process a dataset (say, a million images or a terabyte of text), the data must be converted from classical “0” and “1” into a superposition of amplitudes. This requires quantum random-access memory (QRAM). The problem is that an efficient technology does not yet exist. Loading massive datasets into qubits takes so long (growing linearly or even superlinearly) that it kills any quantum speedup at the outset; working with databases. Today’s QPUs run at frequencies thousands of times lower (kilohertz or megahertz) than CPUs. Because of this huge gap, Grover’s quadratic speedup only becomes useful when the database size is truly astronomical. But such a database can’t be loaded into a quantum computer due to the QRAM problem; cybersecurity threat. To crack a standard RSA-2048 key, a quantum computer needs roughly 4,000 logical qubits with FTQC. According to most major project roadmaps, that result may be reached sometime in the 2030s.

bitcoinist.com Record Retail Buying Cannot Push Ethereum Higher – Someone Bigger Is On The Other Side

Ethereum is struggling below $1,800 as selling pressure and uncertainty keep the price well below the levels that defined the earlier phases of this cycle’s recovery. The decline has been persistent rather than sudden — and CryptoQuant data has surfaced a combination of on-chain signals that reveals the behavioral dynamic beneath the price action in […]

forklog.media Zcash Drops 48% Following Critical Network Vulnerability Fix

The price of Zcash (ZEC) fell by 48% to $302.48 after a critical vulnerability was discovered in the protocol. The flaw allowed for the infinite and undetectable creation of counterfeit coins. Hourly chart of ZEC/USDT on Binance. Source: TradingView. The issue in the anonymous Orchard pool was discovered by security engineer Taylor Hornby on May 29. https://t.co/v7BiOdzU9E— zooko🛡🦓🦓🦓 ⓩ (@zooko) June 4, 2026 He used the Opus 4.8 AI model from Anthropic to analyze the code. Hornby managed to create a working bug that successfully generated tokens in the test network. Developers from Shielded Labs acknowledged that the issue had existed since the launch of Orchard in May 2022. Due to the privacy features of the blockchain, it is impossible to determine if anyone exploited this vulnerability over the past four years. The Zcash team fixed the bug on June 1. Developers believe the vulnerability was unlikely to have been exploited in practice, as it was too complex to find. To restore trust, Shielded Labs proposed launching a new protected pool. This will allow verification of the actual ZEC issuance volume. The organization also plans to conduct a formal verification of the Orchard code to mathematically prove the absence of other bugs. In May, the price of the privacy coin broke the $585 mark for the first time since November 2025.