Venga在推出多功能加密应用程序之前任命Michael Stroev为首席执行官-CoinJournal

币界网2024-07-18 tarihinde yayınlandı2024-07-18 tarihinde güncellendi

币界网报道:
    Venga任命Michael Stroev为首席执行官,领导其多功能加密应用程序的发布。Venga旨在通过全球用户友好的界面简化web3访问。Stroev表示,他将致力于将去中心化创新与传统金融相结合。

Venga是一款开创性的通用加密应用程序,宣布任命Michael Stroev为新任首席执行官。

Stroev,前Nebeus首席运营官兼产品主管,为Venga带来了丰富的金融科技和区块链技术经验。他的领导预计将推动公司雄心勃勃的议程,将去中心化创新与传统金融相结合,以加速web3的采用。

什么是Venga?

Venga通过提供用户友好的界面和强大的技术在竞争激烈的加密货币市场中脱颖而出,旨在简化对web3产品的访问。

即将推出的一体化应用程序标志着Venga在助力全球用户有效探索和利用加密资产方面的一个重要里程碑。

该应用程序的设计不仅是为了迎合经验丰富的加密爱好者,也是为了通过其直观的服务吸引新来者。

迈克尔·斯特罗夫担任首席执行官对公司意味着什么?

随着Venga为即将在主要平台上发布的应用程序做准备,Michael Stroev的任命标志着该公司朝着实现其成为去中心化金融生态系统值得信赖的门户的愿景迈出了战略一步。

一位公司发言人表示:“在Michael Stroev的掌舵下,Venga完全有能力领导弥合去中心化金融与传统金融体系之间的差距。”

在Stroev的领导下,Venga计划坚持透明度和合规性原则,确保用户能够自信地参与加密货币交易。

该公司的积极策略包括获得许可证和认证,例如在西班牙银行注册和准备MiCA许可,进一步增强其在不断变化的监管环境中的信誉。

斯特罗夫在接受任命时说:

“我们的重点仍然是提供创新的产品和服务,使用户能够驾驭web3技术的复杂性。Venga有望成为领先的加密货币平台,为欧洲及其他地区的可访问性和用户体验设定新的标准。”

İlgili Okumalar

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

DeepSeek has updated its DeepSeek V4 model with the DSpark speculative decoding framework, achieving a significant 60-85% speedup in generation for Flash models and 57-78% for Pro models while maintaining the same overall throughput. This engineering-focused update, rather than a core architectural change, introduces DSpark to address latency and throughput bottlenecks in high-concurrency production environments. DSpark combines high-throughput parallel generation with adaptive load-aware verification. Its key innovations include a semi-autoregressive generation architecture to model dependencies within token blocks and a hardware-aware confidence-scheduled verification system. This system uses a confidence head to predict token acceptance probabilities, allowing it to dynamically optimize verification length per request and allocate compute only to tokens with the highest expected payoff. The asynchronous scheduler is designed for real-world deployment, ensuring zero-overhead scheduling and continuous CUDA graph replay while preserving the target model's output distribution. In tests across mathematical reasoning, code generation, and daily dialogue, DSpark outperformed state-of-the-art models like Eagle3 and DFlash, increasing average acceptance length by 26.7%-30.9% and 16.3%-18.4% respectively on Qwen3 target models. DeepSeek also open-sourced DeepSpec, a full-stack codebase for training and evaluating speculative decoding draft models, providing a standardized toolkit that includes data preparation tools, model implementations, training code, and evaluation scripts.

marsbit4 saat önce

Just now, DeepSeek V4 updates with DSpark, improving inference speed by 80%

marsbit4 saat önce

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

The Bitcoin mining industry is undergoing its most complex structural adjustment since inception. Despite Bitcoin's price holding near $61,000 and the network hash rate approaching a record 1 ZH/s, miner profitability is deteriorating. The industry is operating close to its breakeven point, with the 2028 halving expected to accelerate consolidation. The challenges extend beyond the halving's subsidy reduction; the industry's revenue model has yet to successfully transition towards a fee-driven structure. Increasingly, mining companies are evolving from simple Bitcoin producers into infrastructure and energy operators, including providers of AI/HPC computing power. Competition is shifting from pure hash rate expansion to business model upgrades. Economic pressure is evident. The theoretical daily mining revenue at current prices is around $78 million, yet the actual figure is only about $33 million—a 136% gap. Transaction fees remain low at roughly $220k daily, far below historical implied levels. With a current estimated industry-wide breakeven price near $65,000, mining alone is struggling to generate ideal profits. The 2028 halving is projected to push the fundamental production cost floor to approximately $93,289. This will likely accelerate a shift towards consolidation among larger, well-capitalized miners with diversified revenue streams. Competitive advantage will belong to institutionalized players with access to low-cost energy, AI/HPC hosting operations, and stronger balance sheets. In essence, Bitcoin mining is transitioning from a "mining business" to an "infrastructure business." Future profitability and resilience will depend less on block rewards and more on diversified income sources like energy management and computational infrastructure services. For investors, the key question is not the halving itself, but which miners can successfully navigate this business model transformation.

marsbit5 saat önce

BIT Research: The 2028 Halving Is Not the End, the Real Shake-Up of the Bitcoin Mining Industry Is Just Beginning

marsbit5 saat önce

This is How God Karpathy Uses Claude?

Andrej Karpathy, a prominent figure in AI, has reportedly joined Anthropic, leading to a noticeable decrease in his open-source contributions and social media activity. A document claiming to be his personal "CLAUDE.md" file—a set of instructions for the Claude AI to follow within a specific codebase—has been circulating online. While its authenticity is unverified, the content aligns closely with Karpathy's publicly shared principles on effective AI-assisted programming. The document outlines key rules for AI coding assistants, emphasizing the importance of reading existing code thoroughly before writing new code to maintain consistency. It advises against over-engineering, advocating for simple, surgical modifications that match the project's existing style. Other guidelines include clarifying assumptions upfront, writing meaningful tests, thoughtful debugging, and carefully considering dependencies. The core message is that these principles help prevent common AI coding failures, such as introducing unnecessary abstractions, style drift, or making invisible architectural decisions. The community has noted that even experts like Karpathy require detailed instructions to guide AI effectively, akin to managing a junior developer. A related GitHub repository, "andrej-karpathy-skills," which encapsulates these ideas, is reported to significantly reduce Claude's code error rate. Ultimately, the advice stresses that the best CLAUDE.md is tailored to one's own tech stack and coding practices.

marsbit5 saat önce

This is How God Karpathy Uses Claude?

marsbit5 saat önce

İşlemler

Spot
活动图片