Fetch.ai (FET), is leading the current boom amongst other Artificial Intelligence (AI) tokens with a 10.46% price increase within 24 hours. The token’s outstanding performance has led to discussions on possible reasons fueling such momentum.
Possible Reasons for Bullish Fetch AI Performance
According to data from CoinMarketCap, FET is trading at $1.592, with trading volumes and market cap standing at $497.35 million, and $1.35 billion respectively.
The outstanding performance of Nvidia’s stock could be a key factor propelling increases for FET. Nvidia, a prominent chipmaker and AI applications developer has seen its stock more than doubled year-to-date on increased demand for its AI-specific chips.
Nvidia’s momentum is extending into the crypto space since many blockchain initiatives with an AI focus depend on GPU technology. For instance, Fetch.ai utilizes machine learning algorithms to enable autonomous economic agents, requiring a tremendous amount of processing power. Similarly, Render (RNDR), another AI token, leverages underutilized GPUs to provide high-quality rendering for applications in gaming and media.
The recent AI token boom extends beyond the FET token. Other notable gainers include RNDR, Ocean Protocol (OCEAN), a platform for decentralized data exchange for AI training, and SingularityNET (AGIX), a space for creating and monetizing AI services.
According to current data, the market capitalization of AI tokens has grown to $29.9 billion, demonstrating a 2.6% surge in the past day. The boom in AI tokens signifies a growing recognition of synergy between AI and the crypto ecosystem. For instance, blockchain projects like Pantera Capital and brokerage firm Robinhood are actively competing for a central role in the AI revolution.
Functions of AI Tokens
AI tokens represent a unique niche within the crypto market. Their core purpose is to fuel decentralized networks and applications that leverage AI and machine learning. These tokens often act as an economic incentive layer within these ecosystems, rewarding users for contributing data, processing power, or AI models.
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