[Weekly Readings] Crypto Bounce Back As Bank Failures Easing

HTX NewsОпубліковано о 2023-04-01Востаннє оновлено о 2023-04-01

Анотація

Review the hot articles in the past week and help you quickly understand the crypto market.

Articles of this week, helping investors gain an in-depth view of the market.

Market Interpretation

$4 Billion Bitcoin Option Contract To Expire On Friday, What This Means For BTC

The company plans to use corporate resources to fill the gap, including external capital.

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Bitcoin Price Regains Strength As The Bulls Target Fresh Monthly High

Bitcoin price is rising above the $28,000 resistance. BTC bulls seem to be aiming a fresh surge above the $28,500 and $28,800 resistance levels.

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Why Bitcoin Could Be Less Than 120 Days Away From Retesting ATHs

Bitcoin price is currently pulling back alongside the broader crypto market following a strong move from $20,000 to $29,000 in a matter of two weeks. The sharp rally has the market speculating that a bottom might be in.

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Bitcoin Price Action Mirrors Q1 2021, Volatility Ahead?

The surge of the largest cryptocurrency in the market, Bitcoin (BTC), has caught the attention of investors and analysts, with many drawing parallels to BTC’s performance in Q1 2021. While the similarities are striking, some experts caution against assuming that history may repeat itself.

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ETH2.0

Withdrawals Are Coming! ETH Shapella Mainnet Launches April 12th with Exciting Upgrades

Ethereum, the second-largest cryptocurrency by market capitalization, has announced the launch of the Shapella Mainnet.

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Пов'язані матеріали

Just Now, Anthropic Unveils Physical MCP: Claude Begins Controlling the Real World

Anthropic has announced the Model Hardware Standard (MHS), a new standard enabling AI agents like Claude to safely control physical devices. Building on the Model Context Protocol (MCP), MHS standardizes communication between AI agents and hardware such as microscopes, robotic arms, and lasers, marking a significant step for AI from the digital into the physical world. Developed in collaboration with HHMI Janelia Research Campus, MHS uses standardized drivers to translate basic commands (e.g., read, write) into a format any programmable device can understand. This drastically reduces integration time from weeks to hours or minutes and allows agents to discover and operate new devices using natural language tags that describe machine properties and safety limits. Agents can control devices via MCP, command-line interfaces, or APIs. They can sequence operations, monitor results, adjust parameters in real-time, and generate deterministic scripts for long-running tasks. Early tests show Claude interacting with hardware exploratively, like a scientist, learning to calibrate a laser and scripting the process. Early adopters and partners include AWS, Automata, Danaher, Doosan Robotics, and Tecan, who are integrating MHS support into their platforms. While promising, challenges remain: Claude's physical reasoning is limited, requiring expert oversight, and MHS currently only works with programmable hardware. Anthropic plans further refinements and broader device support before open-sourcing the standard.

marsbit18 хв тому

Just Now, Anthropic Unveils Physical MCP: Claude Begins Controlling the Real World

marsbit18 хв тому

History's Only Asset with a 100% Win Rate After 4 Years of Holding

**Title: The Only Asset with a 100% Win Rate Over Any 4-Year Holding Period** This article analyzes which major, freely-tradable assets have historically never produced a nominal loss over any rolling 4-year holding window. It concludes that only two distinct categories achieve this: ultra-low-risk contractual assets and Bitcoin. Among traditional risk assets, none maintain a perfect 4-year record. The S&P 500 had negative 4-year periods (e.g., 1929-1932: -64.8%). The Nasdaq 100 fell roughly 60% from 2000-2003. Gold saw a ~47.7% loss from 1981-1984. US real estate declined about 23.3% from 2007-2010. Even long-term US Treasury bonds (e.g., 2021-2024: -19.8%) and corporate bonds can produce 4-year losses due to interest rate and market price risks. In contrast, the first category achieving 100% nominal success includes assets like rolling 3-month US Treasury Bills, 4-year certificates of deposit (CDs), and US Treasuries held to maturity within 4 years. Their "guarantee" stems from contractual obligations and credit backing (e.g., FDIC insurance, US sovereign promise), not price appreciation. The sole exception in the high-risk category is Bitcoin. Analysis of daily data from 2010-2026 across 4,419 rolling 4-year windows shows a 100% positive return rate. The worst 4-year period (April 2021 to April 2025) still yielded a +32.6% total return (~7.3% CAGR). This record is unique because Bitcoin has no issuer, promises no cash flows, and has endured severe drawdowns (70-90%), yet its market price has always recovered within a 4-year span. The key distinction is the source of the "100%": contractual assets offer known, low nominal returns, while Bitcoin's record stems purely from historical price appreciation despite extreme volatility. The article suggests that for Bitcoin, the ability to hold for 4+ years is more critical than active trading strategies.

marsbit25 хв тому

History's Only Asset with a 100% Win Rate After 4 Years of Holding

marsbit25 хв тому

How One Article Moved 45 Billion: The Collapse of a 25-Year-Old 'AI Stock Guru'

This article details the dramatic rise and near-collapse of a hedge fund built by Leopold Aschenbrenner, a 24-year-old former OpenAI researcher. The fund, named Situational Awareness, amassed $45 billion in assets within two years. Its explosive growth stemmed from Aschenbrenner's influential 165-page manifesto predicting AGI's arrival by 2027 and his high-profile Silicon Valley connections. The fund employed an extremely aggressive strategy: high concentration and 400% leverage to bet long on AI infrastructure stocks while shorting legacy software firms. In July, this structure backfired when both sides of the trade reversed simultaneously—AI stocks plunged while shorted stocks rallied—triggering massive losses that nearly wiped out all equity. Major player Jane Street reportedly lost billions. The fund's leveraged public portfolio was ultimately sold at a discount to Citadel. The SEC is now investigating banks like Goldman Sachs for their role in facilitating the fund's high-leverage trades. The article compares this to past blow-ups like Archegos, highlighting systemic failures in risk management where the pursuit of short-term profits overrode due diligence. It questions whether such risky leverage concentrated in the AI sector, currently at record highs, poses a broader systemic threat. Ironically, Aschenbrenner, who studied AI safety at OpenAI, designed a fund structure prone to uncontrolled failure. Days after the crisis, he reportedly raised another $400 million for new investments.

marsbit39 хв тому

How One Article Moved 45 Billion: The Collapse of a 25-Year-Old 'AI Stock Guru'

marsbit39 хв тому

AI Accelerates Everything: Mathematics's Line of Defense Has Fallen, Physics is Already in AI's Crosshairs

This summer, the mathematics community was shaken as OpenAI's Astra model reportedly solved 10 long-standing open problems, and Claude Fable 5 found a potential counterexample to the Jacobian conjecture. This was followed by a major shift in physics: renowned physicist Gavin E. Crooks presented an open problem in stochastic thermodynamics to Claude, which the AI solved completely in days—a task that might take a skilled graduate student months. The problem concerned constraints on entropy production statistics under the Detailed Fluctuation Theorem (DFT), a core concept in non-equilibrium physics. Claude provided a unifying geometric answer: all possible DFT-compatible distributions correspond to a convex "moment body." Its key insight was that for a fixed "gap," the distribution is uniquely determined, making any general DFT distribution a mixture of these basic two-outcome distributions. This structure implies that for given lower-order moments, the nth moment only has a sharp lower bound, with no upper bound. Claude demonstrated that numerous previously published bounds on entropy production are merely low-dimensional projections or "shadows" of this single, unified convex body. The AI-authored paper offers a complete hierarchical characterization of the moment constraints. This case signifies a potential paradigm shift: AI is progressing from solving known problems to aiding in the exploration of fundamental, unsolved scientific questions, heralding an AI-accelerated era for physics.

marsbit39 хв тому

AI Accelerates Everything: Mathematics's Line of Defense Has Fallen, Physics is Already in AI's Crosshairs

marsbit39 хв тому

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