Хешрейт биткоина достиг нового исторического максимума

investing.ruPublicado em 2024-10-21Última atualização em 2024-10-21

Happycoin.club - 21 октября хешрейт биткоина, или совокупная вычислительная мощность, обеспечивающая безопасность сети, достигла нового исторического максимума в 769,8 Эх/с.

Согласно данным платформы BitInfoCharts, начиная с 2021 года хешрейт сети биткоина неуклонно увеличивается. Некоторые эксперты связывают рост этого показателя с совершенствованием оборудования для майнинга флагманской криптовалюты.

Хешрейт биткоина

Несмотря то, что хешрейт биткоина является показателем, который указывает на безопасность сети, он также означает, что цена добычи одного BTC постоянно дорожает. Из-за этого расходы на майнинг биткоина выросли более чем на 168%, по данным на конец августа. Для сравнения, в начале сентября 2023 года стоимость добычи одной монеты достигала $19 344, спустя год показатель составил $51 887 и продолжает увеличиваться.

Такой стремительный рост стоимости майнинга объясняется сразу несколькими факторами, в частности, повышением цен на электроэнергию, эксплуатационными расходами, а также халвингом биткоина, из-за которого сложность добычи возросла, а вознаграждение за блок сократилось в два раза.

Читайте оригинальную статью на сайте Happycoin.club

Leituras Relacionadas

What's It Like Working with Two "Madmen": Peter Thiel and Elon Musk? Palantir Co-founder Shares His Experience

Joe Lonsdale, co-founder of Palantir and a member of the "PayPal Mafia," shared his experiences working alongside Elon Musk and Peter Thiel. He described both as highly opinionated, ambitious, and intolerant of broken systems, demanding immediate fixes and rapid execution. Thiel is characterized as a strategic philosopher, while Musk is a hands-on engineer deeply involved in technical details. Musk is noted as one of the hardest workers Lonsdale has ever seen, a trait common in PayPal's early, passionate culture that later spawned numerous billion-dollar companies. Lonsdale recounted Palantir's origin story. While working at Thiel's hedge fund, he and Thiel discussed how Silicon Valley's technology far outpaced the government's, especially after 9/11. They saw an opportunity to build a platform to help stop terrorist attacks while protecting civil liberties. Their initial venture capital pitches were met with rejection and ridicule. However, Thiel viewed this as motivation. Critical funding eventually came from the CIA's venture arm and Thiel himself. Reflecting on Palantir's impact, Lonsdale believes their work helped neutralize thousands of terrorists and ensured government oversight, though he acknowledges the potential dangers if such powerful technology is misused. His key takeaway echoes Thiel's early advice: being rejected and laughed at can fuel the determination to prove the doubters wrong.

marsbitHá 30m

What's It Like Working with Two "Madmen": Peter Thiel and Elon Musk? Palantir Co-founder Shares His Experience

marsbitHá 30m

15 Reasoning Models Flip Collectively: Unpacking the Latent Risks Hidden in the Chain of Thought Behind Their Outputs

"15 Reasoning Models Collectively Fail: Revealing Hidden Risks in Chain-of-Thought Outputs" A systematic study led by researchers from Harvard, USC, Brown, and MIT warns that evaluating only the final output of large reasoning models (LRMs) is insufficient for safety. The research highlights that the intermediate reasoning chains (CoT) these models expose can contain dangerous content—like bomb-making instructions or poisoning recipes—even when the final answer appears safe. The core methodology involves separately assessing the reasoning chain and the final answer against 20 safety principles, each scored 1-5 for risk. This identifies three key failure modes: 'Unsafe' (both stages unsafe), 'Leak' (unsafe reasoning but safe answer), and 'Escape' (safe reasoning but unsafe answer). The team evaluated 15 reasoning models on a combined in-distribution dataset of 41K prompts from seven public harmful/jailbreak datasets. A universal finding across all 15 models was that reasoning chains are consistently riskier than final answers. Risk is concentrated in categories like misinformation, illegal activity, bias, and physical/psychological harm, with illegal compliance showing the starkest divergence. Case studies reveal instances where harmful operational details are 'leaked' in reasoning or a seemingly harmless chain 'escapes' into a dangerous final answer. To mitigate this, the researchers propose 'Adaptive Multi-Principle Steering,' a white-box, test-time intervention method. It identifies unsafe principles being activated during reasoning and gently steers the model's internal representations towards safer directions. Validated on open-source models, this approach reduced unsafe outputs by up to 40.8% while preserving 97.7% of benchmark performance. The work underscores the critical need to monitor and secure the entire reasoning process, not just the final output.

marsbitHá 34m

15 Reasoning Models Flip Collectively: Unpacking the Latent Risks Hidden in the Chain of Thought Behind Their Outputs

marsbitHá 34m

Trading

Spot
活动图片