與更廣泛的加密貨幣市場相比，與AI相關的加密代幣表現出很強的性能

2024年的數據表明，AI和大數據令牌從6月至11月的市值飆升了131％，達到421億美元

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.

近年來，與更廣泛的加密貨幣市場相比，與AI相關的加密代幣表現出色，這一趨勢似乎在2024年持續。這種績效通常歸因於人工智能及其與區塊鏈技術的整合的興起。

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.

根據2024年的數據，AI和大數據令牌從6月至11月的市值增長了131％，達到421億美元。比特幣公牛跑步促進了這一激增，該比特幣公牛跑步在2024年12月的旗艦加密貨幣上達到了103,332美元，投資者對AI對革新各種行業的潛力充滿信心。

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.

與比特幣和以太坊等主要加密貨幣相比，特定的令牌（例如渲染（rndr）和fetch.ai（FET））在某些時期展示了未來的回報。例如，渲染是一個提供分散式GPU計算的平台，在2024年，其代幣價格上漲了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.

同時，側重於建立分散的自主智能的機器學習網絡Bittensor（Tao）在2024年的30天內經歷了164％的集會。這些回報突出了AI代幣市場的投機性質，價格波動很大，投資者情緒的巨大變化發揮了作用。

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等社交媒體平台上，與比特幣相比，圍繞AI令牌的討論涉及其表現優於性，其中一位用戶強調了AI代幣的三年回報率為10,287％，而比特幣的回報率為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.

這篇文章還提到，自2024年第四季度以來，AI令牌繼續領先於市場彈跳，展示了該資產類別的韌性和恢復能力。但是，對某些AI代幣的懷疑是顯而易見的，一位用戶批評Tao是人們在“炒作高峰”中購買的“紀念物”。該評論說明了一些令牌周圍的投機性瘋狂，這可能會給從事FOMO（擔心錯過）購買的投資者帶來風險。

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.

對AI技術的興趣，尤其是在Chatgpt推出之後，對整合AI集成的區塊鏈項目的需求提高了。這些項目提供了分散計算（渲染），AI市場（fetch.ai）和機器學習網絡（Bittensor）的解決方案，可滿足更廣泛的Web3生態系統中的特定需求。

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，現實世界中的用例，例如針對交易者的預測分析和DEFI協議的自動交易策略突出了這些代價超出推測的潛力。

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.

更廣泛的加密貨幣市場激增也取消了山寨幣，Tao和Rndr等代幣看到的巨大收益 - Tao在2024年的30天內獲得了164％的收益，而RNDR +600％在六個月內獲得了164％的收益 - 歸因於AI轉型潛力的FOMO和敘事。

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.

最後，區塊鏈的權力下放與AI對安全，分佈式數據處理的要求相吻合，引起對fetch.ai和Bittensor等項目的興趣，這些項目側重於與AI技術相關的可擴展性和隱私問題。正如X討論中強調的那樣，這種協同作用是長期的價值驅動力。