Cycle Capital：SATS与Unisats近期关键叙事发展

长文源：区块律动Published on 2017-07-24Last updated on 2024-07-17

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Yen stablecoin issuer JPYC’s Series B reaches $38M

Japanese yen stablecoin issuer JPYC has raised an additional 1 billion yen, bringing its Series B funding round total to approximately 6 billion yen ($38 million). The extension includes logistics group AZ-COM Maruwa Holdings as a new investor, though the exact investment amount was not disclosed. JPYC intends to use the funds to expand its financial and Web3 ecosystem and accelerate adoption of its yen-pegged stablecoin. AZ-COM is reportedly exploring using the stablecoin for payments to its delivery partners. The partnership aims to integrate commercial, logistics, and payment flows through onchain finance.

cointelegraph13m ago

Yen stablecoin issuer JPYC’s Series B reaches $38M

cointelegraph13m ago

Arthur Hayes Steps Up Purchases of This Altcoin, Investing $2 Million Over the Past Five Days!

Arthur Hayes, the founder of BitMEX, has significantly increased his investment in $ENA, the native token of the Ethena ecosystem, by purchasing approximately 2 million dollars' worth over the past five days. His most recent transaction involved acquiring 10.9 million $ENA tokens, valued at around $985,000, bringing his total recent purchases to 22.64 million tokens. This buying activity has drawn renewed investor attention to Ethereum-based projects and the DeFi sector. Hayes is known for his macroeconomic analyses and positive outlook on the crypto market. His substantial investment in $ENA is being interpreted as a sign of his confidence in the long-term prospects of Ethereum and specific DeFi projects. Ethena is noted for developing synthetic dollar products on the blockchain, with its $ENA token used for governance and within its ecosystem. While such large-scale purchases by prominent figures are seen as a key market indicator, experts caution that they alone are insufficient to drive price increases. Multiple factors, including overall market conditions, liquidity, investor demand, and macroeconomic events, continue to influence price movements. Analysts suggest Hayes's actions may reflect sustained interest from institutional and large investors in Ethena, but they emphasize that investment decisions should not rely solely on whale activity. A thorough evaluation of a project's fundamentals, utility, and broader market trends remains essential.

cryptonews.ru34m ago

Arthur Hayes Steps Up Purchases of This Altcoin, Investing $2 Million Over the Past Five Days!

cryptonews.ru34m ago

AI Takes Over the Lab? Latest Research from USTC Puts It to the Test in the Real Physical World

This study from the University of Science and Technology of China presents a real-world stress test for AI in scientific research. Researchers developed a machine-readable, modular laboratory for catalysis, consisting of 45 automated workstations. They evaluated 48 configurations combining 6 agent frameworks and 9 large language models (LLMs) across 32 expert-defined research tasks, conducting 4,608 tests. The key findings reveal a significant gap between AI's planning ability and reliable physical execution. Only 3.3% of all generated workflows (151 out of 4,608) could be executed without human correction. The best-performing agent/LLM combination achieved a 28.1% success rate. In a five-round closed-loop experiment, the AI could adjust local parameters based on results but failed at higher-level scientific replanning, such as redesigning analytical methods or correcting persistent critical omissions. Maintaining logical integrity for long-sequence workflows (over 30 steps) also proved challenging. The research distinguishes three often-conflated AI capabilities: generating plausible experimental plans, creating physically executable workflows, and performing evidence-driven strategic replanning. Results show the first does not guarantee the second, and parameter tuning is not equivalent to scientific reasoning. The platform serves as both a "testing ground" to quantify AI's scientific aptitude and a potential "training ground." By forming a "plan-execute-feedback-replan" loop with real-world feedback, it can expose AI shortcomings and generate data for iterative improvement, moving toward true end-to-end autonomous discovery.

marsbit38m ago

AI Takes Over the Lab? Latest Research from USTC Puts It to the Test in the Real Physical World

marsbit38m ago

Token Plummets 99% and Founder Faces Charges: NFT Startup Few and Far Costs Investors $10 Million

U.S. prosecutors have charged Taj Tarsha, 34, founder of NFT startup Few and Far, with securities fraud and wire fraud. He is accused of raising over $10 million from at least 67 investors via Simple Agreements for Future Tokens (SAFT) for the FAR token, meant to power an NFT marketplace on NEAR Protocol. Instead of developing the project, Tarsha allegedly misused investor funds for online gambling, cryptocurrency speculation, personal expenses including a Miami condominium loan, interior design, and his DJ hobby. An audit in June 2023 revealed the misappropriation. Despite this, Tarsha allegedly continued the deception for about another year, dismissing staff while creating an appearance of ongoing work. When the FAR token launched in May 2024 at approximately $0.13, it crashed by over 99% almost immediately and ceased trading. Arrested on June 6, 2026, Tarsha faces up to 20 years imprisonment per charge. The case highlights a recurring pattern in the NFT industry and raises questions about the SAFT mechanism's lack of oversight before a token's listing.

cryptonews.ru43m ago

Token Plummets 99% and Founder Faces Charges: NFT Startup Few and Far Costs Investors $10 Million

cryptonews.ru43m ago

Fei-Fei Li's Latest Interview: Humans Don't Rely Solely on Real Data for Learning

Fei-Fei Li's latest interview on a16z explores the vision for **spatial intelligence** as AI's next frontier, with robotics as its primary testing ground. She discusses World Labs' acquisition of SceniX, a robotics startup co-founded by her former postdoc Yunzhu Li, aiming to tackle the core challenge of scarce and expensive real-world training and evaluation data for robots. The key strategy involves creating scalable, realistic **simulation environments** via a "real-to-sim-to-real" pipeline. This allows for safe, efficient, and controllable data generation, training, and robust evaluation of robotic systems, complementing physical data collection. The combined strengths of World Labs' generative world models (like Marble) and SceniX's simulation and robotics expertise aim to build foundational **infrastructure**—a digital proving ground agnostic to specific robot hardware or AI models. The discussion highlights the necessity of simulation for **counterfactual reasoning**, reliability, and accelerating development, drawing parallels to human learning and industries like autonomous vehicles. The near-term focus is on practical deployment in **semi-structured environments** (e.g., warehouses) rather than fully unstructured ones like homes, emphasizing a calibrated, stepwise approach to achieving robust and commercially viable robotic automation.

marsbit52m ago

Fei-Fei Li's Latest Interview: Humans Don't Rely Solely on Real Data for Learning

marsbit52m ago

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4.3k Total ViewsPublished 2024.03.29Updated 2026.06.02

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