Cato Institute Policy Analyst, Nick Anthony, used the 55th anniversary of the Bank Secrecy Act (BSA) to argue that U.S. financial surveillance has grown “hidden and unjustified,” capturing mostly legal transactions while imposing heavy compliance costs. He warned that expansions through the GENIUS Act now bind stablecoin issuers to the same monitoring obligations as banks, calling it “a step in the wrong direction.” Anthony contended that outdated $10,000 reporting thresholds, unchanged since the 1970s, should be adjusted to reflect inflation and privacy concerns. He urged stronger Fourth Amendment protections against warrantless financial searches and noted lawmakers like Rep. John Rose and Sen. Mike Lee are pushing reforms. As payments become more digital, he said, maintaining options like cash and prepaid cards will be key to preserving financial autonomy and resisting state overreach.
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Bitcoin mining has evolved from hobbyist experimentation into a finely tuned industrial pursuit, where profitability depends on precise data rather than raw power. In Hashprice and Hashvalue Explained: The Real Metrics of Bitcoin Mining Profitability, James identifies two key benchmarks, hashprice and hashvalue, that determine how efficiently miners convert computation into returns. Hashprice, measured in USD per terahash per day, reflects a miner’s revenue potential based on Bitcoin’s price, transaction fees, and network difficulty. Hashvalue, denominated in BTC per terahash, reveals how much Bitcoin is earned regardless of fiat volatility. “Hashprice is your miner’s daily paycheck,” James writes, while hashvalue “cuts through the noise of market price swings.” Understanding both enables miners to forecast earnings, refine energy strategies, and time necessary BTC sales. James argues in an increasingly competitive landscape, information, not electricity is the most valuable mining input.
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Dan Goodin of Ars Technica reports that Google’s analysis of five AI-developed malware families, PromptLock, FruitShell, PromptFlux, PromptSteal, and QuietVault, found them ineffective, easily detected, and derivative of existing code. Despite media hype, the study revealed “no breakthrough capabilities,” with each sample failing to evade even basic antivirus systems. Independent researcher Kevin Beaumont said the findings show that “threat development is painfully slow,” while another expert noted, “AI isn’t making any scarier-than-normal malware.” The report challenges claims from firms like Anthropic and OpenAI that AI-driven tools are transforming cyberattacks, finding instead that generative AI’s role remains largely experimental. Google added that one actor briefly bypassed its Gemini model’s guardrails by impersonating white-hat hackers, prompting tighter controls. For now, the most credible threats continue to rely on traditional, human-crafted malware rather than automated AI systems.
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Quantinuum has unveiled Helios, its third-generation ion-based quantum computer, a system designed to simplify error correction and scale more efficiently than superconducting rivals from Google or IBM, reports Sophia Chen for MIT Technology Review. The Colorado-built machine uses 98 barium-ion qubits, up from 56 ytterbium qubits in its predecessor, and can form one logical qubit from just two physical qubits, compared with IBM’s 12 and Google’s 105. “Helios is an important proof point in our road map about how we’ll scale,” said Quantinuum vice president Jennifer Strabley. Researchers cited its 99.921% entanglement accuracy as unmatched, due to its all-to-all ion connectivity and GPU-assisted real-time error correction. The company plans a fourth-generation “Sol” system by 2027 and a fault-tolerant “Apollo” by 2029, positioning ions as strong contenders in the global race toward commercially viable quantum computing.
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