AGIX and FET gained 11% last week, but AI tokens had mixed performances.
Since February, the trading volume for AI tokens has climbed to $8 billion per week.
AI tokens’ market share on Binance fell to 39%, while Korean and US exchanges increased.
While Nvidia Corporation (NVDA) reported better-than-expected profits, AI-linked tokens experienced mixed performance last week.
Both the AGIX decentralized AI marketplace from SingularityNET and the Fetch.ai (FET) AI-focused cryptocurrency protocol had 11% increases. However, Render (RNDR) and Akash Network (AKT) had lesser returns, and NEAR ended the week in the red.
Even with the uneven performance, AI tokens have largely outperformed this year. Year to date, they have enjoyed gains ranging from 60% to 250%, even outperforming the stellar performance of Nvidia.
Since February, the average weekly transaction volume for these tokens has increased dramatically, from a historic low of $300 million in the middle of 2023.
Remarkably, global AI trading volumes have shifted noticeably to regulated exchanges. While Binance continues to dominate rapidly-expanding market niches like meme tokens, as of last week, its market share for AI tokens fell from over 70% a year ago to 39%. By contrast, US and Korean exchanges have been expanding.
Although in February the 60-day correlation between AI tokens and Nvidia reached a multi-month high, it is still quite low, ranging between 0.2 and 0.3. Remarkably, this year, Worldcoin (WLD), which positions itself as a global identification and financial network for an AI-driven society, has shown a stronger correlation with NVDA than most other AI tokens.
The phenomenal performance of Nvidia and developments in AI technology are two of the reasons behind the spike in AI tokens. With a 769% increase in net income year over year, Nvidia has recently achieved financial success that has cemented its leadership position in the AI ecosystem.
This has bolstered tokens linked to AI in the cryptocurrency market. Further igniting interest in AI tokens are advancements like the text-to-video model Sora from OpenAI.
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