AI

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.

VIM is the core token of the Vimverse ecosystem. Its role goes beyond that of an ordinary crypto asset. It is positioned as a form of “programmable economic infrastructure” used to coordinate AI Agents, liquidity systems, and on-chain economic structures. In Vimverse’s design, VIM serves multiple functions at once, including governance, liquidity coordination, ecosystem incentives, and protocol-level market stability.

Vimverse is an AI Native Web3 project built around AI Agents, virtual persona systems, and on-chain digital identity. Its core goal is to make AI more than just a tool, allowing it to exist as an active participant in the on-chain ecosystem. Within Vimverse, AI Agents can not only interact with users, but also have behavioral logic, long-term memory, on-chain identities, and relationships with digital assets.

Vimverse (VIM) is a Web3 project built around AI Agents, Programmable Liquidity, and an on-chain digital ecosystem. Its core goal is to transform liquidity from a “passive capital pool” into an infrastructure layer that protocols can actively manage. By introducing the Protocol Managed Market Making (PMMM) framework, Vimverse aims to help protocols build more stable, sustainable, and coordinated on-chain market structures.

Agentverse is an AI Agent system built within the CROSS gaming ecosystem. It allows AI Agents to interact, collaborate, compete, and perform asset-related actions in an on-chain environment. Unlike traditional game NPCs, AI Agents in Agentverse can act based on on-chain data, autonomous logic, and economic systems, while building dynamic relationships with players and other AI Agents.

Gate Prediction Market has undergone a new round of upgrades, centered on Smart Money identification, whale position tracking, AI analysis, and sports trading scenario optimization, propelling the prediction market toward data-driven, professional trading.

My Pet Hooligan (HOOLI) is a Web3 project that brings together AI virtual characters, a third-person shooter, NFTs, and transmedia entertainment content. Developed by AMGI Studios, the project builds a digital IP ecosystem around its “Hooligan” rabbit characters and expands Web3 entertainment through games, animation, community content, and the Studio Chain Layer2 infrastructure.

Quack AI’s AI Governance Layer is an AI governance infrastructure designed for Web3 and the Agent Economy. Through AI Agents, a Policy Engine, and an automated execution framework, it helps DAOs and on-chain protocols optimize their governance processes. Its core functions include proposal analysis, risk identification, automated execution, and cross-chain governance coordination.

Quack AI is an AI Governance Infrastructure built for Web3 that can be used in RWA, real-world asset, management and multi-chain governance scenarios. Its core architecture combines AI Agents, a Policy Engine, and automated execution mechanisms to help DAOs and on-chain protocols improve cross-chain collaboration efficiency and governance automation.

Quack AI is an AI governance infrastructure designed for Web3 and the AI Agent Economy. By combining AI Agents, automated governance mechanisms, and a cross-chain execution framework, it helps DAOs and on-chain protocols improve governance efficiency, risk control, and automated collaboration. Its core goal is to move on-chain governance from “manual coordination” toward “intelligent execution,” reducing governance friction while improving execution efficiency.