ai16zの‌価格AI16Z

Author: Haotian Several possible "transformations" regarding AI Agents: 1) Solana, Base, and BSC are in a three-way standoff. The entry of BSC into the fray will intensify the further "involution" of the AI Agent track. However, after the first wave of "chaotic battles," there will be a period of adjustment and reshuffling. Once the three-way standoff is established, various factions will produce some heroes of the chaotic era, and competition will further intensify, with winners and losers emerging; 2) The Virtual and ai16z dual engines need to change their "locomotives." After the first wave of barbaric growth, both the Virtual system and the ai16z system have left behind various chaotic phenomena and complex issues. How Virtual will take root after migrating to the Solana ecosystem, and how to streamline the tokenomics empowerment issues of ai16z, etc. Once these problems are resolved, driven by the innovative power of the open-source development community, a brand new "locomotive" pull will be more vigorous, which is worth looking forward to; 3) The status of ai16z as a major commercial IP may be threatened by the new force of Arc. Since ai16z announced its closure to catch up, Arc has been relentlessly pursuing it. Its high-performance Rust framework has repeatedly shown progress, and the early launch of the Arc Forge platform, along with $arc, all testify to Arc's ambition. As for whether the leadership of the Solana ecosystem will change, the market will gradually provide an answer; 4) The deepening of application scenarios for AI Agents poses challenges. @aixbt_agent is currently facing the issue of expanding commercial application scenarios, needing to add new DeFai trading decision-making application breakthroughs beyond information strategies. It can either be modularly combined into other AI Agent matrices or evolve its own commercial product PMF. In short, small AIXBT must quickly prove its capability limits; 5) There may be breakthrough AI Agent applications emerging from the subfields of DeFai and GamFai. DeFai can undoubtedly connect with the mature DeFi infrastructure and large capital volume, allowing AI Agents to have sufficient attractive value assessment dimensions such as TVL, Txs, UX, Fees, and multi-agent collaboration. Similarly for GamFai, how to make the implicit value experiences of AI Agents, such as "interaction and decision-making," intuitively integrated through explicit "game scenarios" is crucial.

Aprenda como as finanças descentralizadas da $ASI estão possibilitando novas oportunidades para empreendedores e inovadores #Asi #Senderasi

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关键要点： Memecoin 的涨势正在减弱，顶级 Memecoin 正努力从急剧崩盘中恢复。 RWA 和 AI 加密货币正在成为市场下一个主导趋势。 贝莱德、高盛等机构的支持正在推动 RWA 的采用。 在人工智能代理和重大技术投资的推动下，人工智能加密货币正在快速增长。 #Memecoin 炒作已结束 曾经由 Solana 和 Base 上的代币驱动的 memecoin 市场正在失去动力。上个月大幅下跌 40%，导致主要 memecoin 难以恢复。 狗狗币上个月曾达到0.43 美元的峰值，目前徘徊在0.25 美元。 柴犬的价格已回落至选举前的0.000015 美元水平。 Solana 的顶级 memecoin Official Trump已从其历史最高点75.96万美元暴跌80% ，目前交易价格仅为16 美元。 在 memecoin 苦苦挣扎的同时，比特币依然保持弹性，徘徊在96,000 美元左右，市场占有率为 60% ——较三个月前的 50% 大幅上升。 #风险资产管理公司吸引机构巨头巨额资金 代币化现实世界资产 (RWA) 正在获得关注，为传统金融提供了基于区块链的替代方案。各大机构正在涉足： 贝莱德推出BUIDL、瑞银推出uMint，两大风险资产增值投资基金相继问世。 Abrdn 使用 XRPL 将价值 38 亿英镑的基金代币化，实现了无缝跨境交易。 标记化加快了支付速度，将传统 SWIFT 交易时间从几天缩短到几秒钟。 人工智能加密货币正在重塑市场 人工智能加密的繁荣是由突破性的创新推动的： Virtuals Protocol引入了能够取代整个团队的 AI 代理，推动代币在 2024 年底激增 7000% 。 Deepseek 的法学硕士学位震撼了人工智能领域，仅花费 600 万美元就建立了这个学位，可与美国巨头相媲美。 Andreessen Horowitz 支持的 AI16z 获得了 650 万美元的巨额投资，表明人们对 AI 代币的兴趣日益浓厚。 唐纳德·特朗普提议设立 5000 亿美元的人工智能基金，该基金由马斯克、奥特曼和孙正义支持，可能会推动人工智能投资进入加密市场。 随着 ChatGPT 的 Operator 和 IBM Watson 等人工智能代理的快速发展，人工智能加密货币可能在 2025 年迎来爆炸式牛市。 结论：RWA 还是 AI Crypto？ 随着模因币逐渐淡出人们的视线，风险资产和人工智能加密货币正在引领加密货币的下一波浪潮。争夺主导地位的战斗才刚刚开始——机构支持的风险资产将接管，还是人工智能驱动的代币将推动下一轮牛市？

In a groundbreaking development, artificial intelligence is transforming flood forecasting, enabling real-time predictions that can save lives and protect infrastructure. By leveraging NVIDIA's Modulus framework, researchers have developed an AI-driven system that dramatically enhances disaster preparedness and risk mitigation. ▪️The Challenge with Traditional Flood Forecasting Traditional flood forecasting relies on physics-based numerical simulations, which, while accurate, are incredibly time-consuming. These simulations can take hours to model flooding events, making real-time forecasting impractical. The need for a faster, more efficient solution has led to the integration of AI, which can process complex flood data in seconds rather than hours. ▪️How AI is Changing the Game Using a deep learning approach, this new AI system emulates physics-based flood models. By training on vast amounts of detailed flood data, the model learns to predict flooding events almost instantly. What used to take hours on conventional computing systems can now be completed in milliseconds using AI-powered GPUs. One of the most impressive aspects of this AI model is its ability to predict flooded areas and flow rates in short intervals, extending several hours into the future. The AI is not just fast—it’s highly accurate, allowing authorities to make better decisions in real-time. ▪️Training AI for Real-World Impact The AI model was trained using large-scale flood data, processed on high-performance GPUs to ensure speed and precision. Through advanced machine learning techniques, it learned to simulate how water behaves across different landscapes, accounting for topography, infrastructure, and weather conditions. ▪️A Future of Real-Time Flood Predictions This breakthrough highlights the enormous potential of AI in environmental modeling. With this technology, emergency responders can receive rapid, reliable flood forecasts, allowing them to take proactive measures before disaster strikes. As AI continues to evolve, it’s expected to become an integral part of flood management systems worldwide. By combining AI with traditional physics-based approaches, we are moving toward a future where flood forecasting is no longer reactive but predictive—giving communities the time they need to prepare and respond. $ALICE $AI16Z