与更广泛的加密货币市场相比，与AI相关的加密代币表现出很强的性能

2024年的数据表明，AI和大数据令牌从6月至11月的市值飙升了131％，达到421亿美元

In recent years, AI-related crypto tokens have displayed remarkable performance compared to the broader cryptocurrency market, a trend that appears to be continuing in 2024. This performance is often attributed to the burgeoning interest in artificial intelligence and its integration with blockchain technology.

近年来，与更广泛的加密货币市场相比，与AI相关的加密代币表现出色，这一趋势似乎在2024年持续。这种绩效通常归因于人工智能及其与区块链技术的整合的兴起。

According to data from 2024, AI and big data tokens experienced a surge in market capitalization by 131% from June to November, reaching $42.1 billion. This surge was fueled by the Bitcoin bull run, which saw the flagship cryptocurrency reach $103,332 in December 2024, and investor confidence in AI’s potential for revolutionizing various industries.

根据2024年的数据，AI和大数据令牌从6月至11月的市值增长了131％，达到421亿美元。比特币公牛跑步促进了这一激增，该比特币公牛跑步在2024年12月的旗舰加密货币上达到了103,332美元，投资者对AI对革新各种行业的潜力充满信心。

Specific tokens, such as Render (RNDR) and Fetch.ai (FET), showcased outstanding returns during certain periods compared to major cryptocurrencies like Bitcoin and Ethereum. For instance, Render, a platform offering decentralized GPU computing, saw its token price surge by 600% over six months in 2024.

与比特币和以太坊等主要加密货币相比，特定的令牌（例如渲染（rndr）和fetch.ai（FET））在某些时期展示了未来的回报。例如，渲染是一个提供分散式GPU计算的平台，在2024年，其代币价格上涨了600％。

Meanwhile, Bittensor (TAO), a machine learning network focused on building decentralized autonomous intelligence, experienced a 164% rally over 30 days in 2024. These returns highlight the speculative nature of the AI token market, with large price swings and shifts in investor sentiment playing a role.

同时，侧重于建立分散的自主智能的机器学习网络Bittensor（Tao）在2024年的30天内经历了164％的集会。这些回报突出了AI代币市场的投机性质，价格波动很大，投资者情绪的巨大变化发挥了作用。

On social media platforms like X, the discussion around AI tokens touched upon their outperformance compared to Bitcoin, with one user highlighting a three-year return of 10,287% for AI tokens versus 133% for Bitcoin.

在X等社交媒体平台上，与比特币相比，围绕AI令牌的讨论涉及其表现优于性，其中一位用户强调了AI代币的三年回报率为10,287％，而比特币的回报率为133％。

This post also mentioned that AI tokens continue to lead in market bounces since Q4 2024, showcasing the resilience and recovery capabilities of this asset class. However, skepticism toward certain AI tokens was evident, with one user criticizing TAO as a "memecoin" that people are buying "at the peak of the hype." This comment speaks to the speculative frenzy surrounding some tokens, which could pose risks to investors engaging in FOMO (Fear Of Missing Out) buying.

这篇文章还提到，自2024年第四季度以来，AI令牌继续领先于市场弹跳，展示了该资产类别的韧性和恢复能力。但是，对某些AI代币的怀疑是显而易见的，一位用户批评Tao是人们在“炒作高峰”中购买的“纪念物”。该评论说明了一些令牌周围的投机性疯狂，这可能会给从事FOMO（担心错过）购买的投资者带来风险。

The interest in AI technologies, especially following the launch of ChatGPT, has boosted demand for blockchain projects integrating AI. These projects offer solutions in decentralized computing (Render), AI marketplaces (Fetch.ai), and machine learning networks (Bittensor), catering to specific needs within the broader Web3 ecosystem.

对AI技术的兴趣，尤其是在Chatgpt推出之后，对整合AI集成的区块链项目的需求提高了。这些项目提供了分散计算（渲染），AI市场（fetch.ai）和机器学习网络（Bittensor）的解决方案，可满足更广泛的Web3生态系统中的特定需求。

Moreover, real-world use cases such as predictive analytics for traders and automated trading strategies on DeFi protocols highlight the potential of these tokens beyond speculation.

此外，现实世界中的用例，例如针对交易者的预测分析和DEFI协议的自动交易策略突出了这些代价超出推测的潜力。

The broader crypto market surge has also lifted altcoins, and the huge gains seen by tokens like TAO and RNDR—with TAO gaining 164% over 30 days in 2024 and RNDR +600% in six months—are attributed to FOMO and narratives around AI's transformative potential.

更广泛的加密货币市场激增也取消了山寨币，Tao和Rndr等代币看到的巨大收益 - Tao在2024年的30天内获得了164％的收益，而RNDR +600％在六个月内获得了164％的收益 - 归因于AI转型潜力的FOMO和叙事。

Finally, blockchain's decentralization aligns with AI's requirement for secure, distributed data processing, driving interest in projects like Fetch.ai and Bittensor, which are focused on scalability and privacy issues related to AI technology. This synergy is a long-term value driver, as highlighted in the X discussions.

最后，区块链的权力下放与AI对安全，分布式数据处理的要求相吻合，引起对fetch.ai和Bittensor等项目的兴趣，这些项目侧重于与AI技术相关的可扩展性和隐私问题。正如X讨论中强调的那样，这种协同作用是长期的价值驱动力。