Musk's robotic revolution puts AI cryptocurrencies into the spotlight: 5 AI tokens worth watching f

Musk's Robot Vision: Personal Assistants, Nursing and Automation Productivity

Musk's Robot Vision focuses on personal assistants, nursing services, education, and achieving higher productivity through automation. Artificial intelligence infrastructure requires computing resources, organized data, decentralized applications, and systems for autonomous software. Projects such as Bittensor, Render, FET (Artificial Super Intelligence Alliance), NEAR and The Graph target different areas in the expanding AI-blockchain ecosystem.

Elon Musk's vision of the widespread use of humanoid robots has triggered a new round of thinking about artificial intelligence, automation and the future digital economy. In discussions with media groups, Musk outlined two possible outcomes as humanoid robots become more popular. He described a positive scenario: robots will become personal assistants, capable of performing tasks that currently require a lot of human time and energy.

Musk also talked about an economic form in which individuals would be able to order thousands of physical and digital robots at once. He asked: If productivity improves significantly, will there be widespread high incomes in the future? Does the traditional meaning of money still hold?

这一愿景指向了使越来越多独立机器运行所需的底层基础设施。人工智能系统需要算力、数据、软件以及能够协调更复杂任务的网络。在加密货币领域，有许多项目正在致力于构建这一新兴基础设施的各个层面。

Bittensor：瞄准去中心化人工智能网络

Bittensor (TAO) 的核心是去中心化机器智能系统和基于人工智能的服务网络。其设计旨在让各方能够将计算资源、模型或智能相关服务提供给一个开放的网络。该项目是更广泛的去中心化人工智能讨论的一部分，它构想了一个通过基于区块链的平台培养和共享机器智能的空间。

Render：提供高性能计算基础设施

Render (RENDER) 运营着一个去中心化网络，旨在连接需要 GPU 计算资源的用户与提供未使用图形处理能力的提供商。该基础模型的应用范围超越了数字渲染领域。人工智能开发可能需要大量的 GPU 资源用于训练、推理和其他工作负载，这使得去中心化计算网络在不断扩大的人工智能基础设施市场中扮演着潜在角色。

人工超智能联盟 (FET)：聚焦人工智能开发

The Artificial Superintelligence Consortium (FET) is a group of blockchain-based AI projects working together to create decentralized AI. It aims to create an open AI system that enables autonomous agents and machine intelligence to communicate with each other through decentralized infrastructure. This places FET at the heart of the intersection of AI agents and blockchain.

NEAR Protocol: Building Infrastructure for AI Applications

NEAR Protocol (NEAR) is a blockchain network designed to support decentralized applications and scalable digital services. Its ecosystem is increasingly exploring the realm of artificial intelligence, including applications involving AI agents and user interface tools. With the popularity of autonomous software, blockchain infrastructure can be used to provide ownership, transaction, authentication and coordination capabilities for AI-driven applications.

The Graph: Organize data for blockchain applications

The Graph (GRT) provides an indexing protocol that allows developers to access organized blockchain data. It provides the infrastructure for decentralized applications to query and utilize blockchain network information. As the interaction of artificial intelligence applications with blockchain networks increases, the ability to reliably obtain data becomes particularly important. Structured on-chain data may be used for decision-making, on-chain record retrieval, or automated tasks performed by AI agents.

What Musk's robot vision means for artificial intelligence crypto-assets

Musk's remarks focused mainly on the potential impact of humanoid robots on daily life and economic productivity. However, the development of such systems also requires a large amount of digital infrastructure, including computing resources, data systems, and automation software.

The above five cryptocurrencies approach this broader artificial intelligence trend from different perspectives. Bittensor focuses on decentralized machine intelligence, Render focuses on GPU computing, the Artificial Super Intelligence Alliance (FET) focuses on decentralized artificial intelligence, NEAR focuses on blockchain applications, and The Graph focuses on blockchain data.

Therefore, their relevance to the artificial intelligence industry stems from the infrastructure and applications they build, not from the humanoid robots themselves. As artificial intelligence develops, these different levels may become increasingly important to the digital economy.