AI

Gate AI is a general-purpose AI assistant developed by Gate, capable of conversational Q&A, information search, data insights, and task execution, enabling users to efficiently obtain answers and complete tasks via natural language. By integrating platform content, real-time information, and intelligent recommendations, Gate AI delivers a seamless experience for information retrieval and solution generation, and is evolving into the unified entry point for the Gate AI ecosystem.

Alaya AI is an open, composable Web3 AI data infrastructure network. Its core architecture tightly integrates distributed data communities with AI training and auto data processing, leveraging blockchain and gamification mechanisms to enable both individuals and enterprises to participate in the collection, annotation, verification, and monetization of high-quality AI data with significantly reduced barriers to entry.

AGT (Alaya Governance Token) is the native platform token of the Alaya AI ecosystem, functioning as both a utility and governance token with a maximum circulation cap of 5 billion. It orchestrates critical network operations such as data contribution incentives, platform security staking, DAO voting, auto-annotation model development participation, NFT upgrades, and custom data requests. As the primary economic interface, it bridges decentralized data labor with the needs of AI projects.

Alaya AI is an open, composable Web3 AI data infrastructure network that seamlessly integrates distributed data communities, automated data processing for AI training, and blockchain-powered gamification incentives, delivering accessible, customizable, and auditable data pipelines for both individual and enterprise AI applications.

MPWR, also known as Monolithic Power Systems, is a global semiconductor company focused on power management chips and analog semiconductor technology. Its products are widely used in AI data centers, GPU servers, and high performance computing systems. Although Monolithic Power Systems does not directly develop AI GPUs or large model chips, its power management solutions are an important underlying part of AI infrastructure operations.

AlphaX is the AI-powered on-chain signal system within the DeAgentAI ecosystem. It is mainly used for on-chain data analysis, market trend identification, and automated information processing. The system combines AI Agents, on-chain behavioral data, and a multi-chain analysis framework to monitor capital flows, address behavior, and market trends in real time, then generate AI-driven on-chain signals. Compared with traditional quantitative tools, AlphaX places greater emphasis on automated AI analysis, multi-Agent collaboration, and verifiable on-chain execution, making it one of the key applications of AI Agent Infrastructure in on-chain data analysis.

DeAgentAI enables AI Agents to operate and collaborate autonomously within Web3 networks through its AI Agent Framework, Memory System, on-chain execution layer, and consensus verification mechanism. After a user initiates a task, the AI Agent calls tools, reads historical states, generates an execution plan, and completes on-chain operations through Executor nodes. The network’s validator nodes then confirm the execution results, enabling verifiable on-chain AI execution. Compared with traditional AI Bots, DeAgentAI places greater emphasis on persistent memory, multi-Agent collaboration, and decentralized trusted operation.

DeAgentAI (AIA) is a decentralized infrastructure for building on-chain AI Agents. It is designed to give AI Agents identity verification, persistent memory, and autonomous execution capabilities within Web3 networks. Its core architecture combines AI models, on-chain consensus, and multi-chain execution systems, allowing Agents to perform automated analysis, coordinate tasks, and interact on-chain. The AIA token is used for paying for Agent services, governance, staking, and ecosystem incentives.

GENCY AI is an advertising infrastructure platform that combines AI and blockchain to build a verifiable, automated digital advertising system. It analyzes how verifiable data and Smart Contracts can enhance transparency, protect privacy, and reshape the digital advertising industry.

Figure AI and Tesla Optimus are two of the most closely watched companies in the Humanoid Robot industry today, but their core strategies differ significantly. Figure AI places greater emphasis on an AI-first approach and Robotics Foundation Models, aiming to build a general-purpose robotics platform with reasoning capabilities through Helix AI. Tesla Optimus, by contrast, relies on Tesla’s autonomous driving technology, manufacturing system, and data feedback loop, with a stronger focus on large-scale production. Figure AI is more like an AI Robotics company, while Tesla Optimus is closer to a humanoid robot project driven by the automotive industry. Both companies aim to commercialize Humanoid Robots, but they differ fundamentally in AI architecture, hardware systems, business models, and long-term strategy.

Figure AI’s business model mainly revolves around Humanoid Robot deployment, Robot-as-a-Service（RaaS）, AI software systems, and enterprise automation solutions. Unlike traditional robotics companies, Figure AI does not simply sell robot hardware. Instead, it aims to build an “AI + Robotics” platform through Helix AI, enabling robots to perform long-term tasks in factories, warehouses, logistics, and home environments. Its BMW factory partnership is seen as an important validation of commercialization, while in the future, Figure AI may further expand into robot subscription services, robotic AI platforms, and the large-scale automated labor market.

Figure AI is a U.S. Humanoid Robot company focuses on building general-purpose AI robots that can work autonomously in the real world. Its core products include Figure 01, Figure 02, Figure 03, and its robotic AI system, Helix. Unlike traditional robotics companies, Figure AI places greater emphasis on the integration of “AI + Robotics,” aiming to use Vision-Language-Action（VLA）models to give robots the ability to understand, reason, and carry out complex tasks.

Unibase and Virtuals both serve the AI Agent ecosystem, but their core directions are different. Unibase focuses more on long-term memory, agent interoperability, and infrastructure for the Open Agent Internet, supporting multi-agent collaboration through Membase, AIP Protocol, and a data availability layer. Virtuals, by contrast, is more oriented toward AI Agent issuance, economicization, and on-chain operations, with an emphasis on AI Agent assetization and social ecosystems. The two projects represent two different development paths in the AI Crypto sector: “AI Memory Layer” and “AI Agent Marketplace.”

Unibase mainly operates through three components: Membase, AIP Protocol, and Unibase DA. AI Agents can store long-term context through Membase, communicate across platforms through AIP Protocol, and use the data availability layer to support on-chain state synchronization and data storage. This architecture is designed to build the Open Agent Internet, allowing AI to keep learning, share memory, and carry out multi-agent collaboration tasks.

Unibase (UB) is a decentralized infrastructure designed for AI Agents. It aims to provide autonomous AI with long-term memory, cross-platform agent interoperability, and verifiable data storage. Its core modules include Membase, AIP Protocol, and Unibase DA, which support AI memory management, agent identity and communication, and high-performance data availability.