Virtuals Robotics: Why Did We Enter the Embodied Intelligence Field?
Original Title: Introducing Virtual Robotics.
Original Author: Virtuals Protocol
Original Translation: DeepTech TechFlow
Since its inception, Virtuals' core goal has always been to build a society of AI agents—a network where agents can collaborate, transact, and create value.
· Through ACP, we have achieved business transactions between agents.
· Through Butler, we have built a collaboration bridge between humans and agents.
· Through Unicorn, we have addressed the capitalization issue for agents.
Each layer is expanding the boundaries of digital intelligence. And now, this network extends into the physical world through robotics, where intelligence has taken on a tangible presence, and action has become tangible.

Artificial intelligence has automated reasoning, blockchain has empowered large-scale collaboration, and robotics has approached physical execution.
These three forces together form a closed loop, constructing a self-sustaining system where thoughts, actions, and transactions can autonomously propagate.
This fusion defines Agentic GDP (aGDP), the total output generated by the collaboration of humans, agents, and machines in the digital and physical domains.

Our exploration of robotics began within our internal venture capital division, investing in cutting-edge teams at the intersection of perception, control, and automation. These early experiments revealed the two core bottlenecks limiting the materialization of agents:
· Data: Without rich spatial datasets, embodied AI cannot learn to perceive or act effectively.
· Capital: Without scalable funding mechanisms, innovation in robotics will remain slow and fragmented.
Addressing these two issues is key to accelerating the development of physical intelligence.

Virtuals have chosen a "Middle Way" strategy to tackle the challenges of robotics.
We are not directly involved in hardware or model development, but instead focus on the invisible yet pivotal levers, building data and capital infrastructure that supports the ecosystem.
· Through SeeSaw: We have introduced a self-centric data platform that redefines how the world is captured and learned, enabling robots to "see" and understand space through human-recorded experiences.
· Through Unicorn: We have reimagined the funding mechanism for cutting-edge technologies.

With the integration of these systems, Virtuals have evolved from a digital agent platform into a full-stack intelligent engine.
If the past decade was defined by information technology, the next decade will be defined by materialization, representing a moment where ideas take on physical form.
Through robotic technology, the agent's internet extends into the physical world, completing the loop between intelligence, collaboration, and existence.

You may also like

Palmer Luckey’s Erebor Reaches $4.3B Valuation as Bank Charter Progresses
Key Takeaways: Erebor, a digital bank co-founded by Palmer Luckey, has raised $350 million, bringing its valuation to…

Kalshi First Research Report: When Predicting CPI, Crowd Wisdom Beats Wall Street Analysts

Polymarket Announces In-House L2, Is Polygon's Ace Up?
AI Trading Risks in Crypto Markets: Who Takes Responsibility When It Fails?
AI trading is already core market infrastructure, but regulators still treat it as a tool — responsibility always stays with the humans and platforms behind it. The biggest risk in 2025 is not rogue algorithms, but mass-adopted AI strategies that move markets in sync and blur the line between tools and unlicensed advice. The next phase of AI trading is defined by accountability and transparency, not performance — compliance is now a survival requirement, not a constraint.

Beacon Guiding Directions, Torches Contending Sovereignty: A Covert AI Allocation War
Key Takeaways The AI that rules today’s landscape exists in two forms—a centralized “lighthouse” model by major tech…

Decoding the Next Generation AI Agent Economy: Identity, Recourse, and Attribution
Key Takeaways AI agents require the development of robust identity, recourse, and attribution systems to operate autonomously and…

Nofx’s Two-Month Journey from Stardom to Scandal: The Open Source Dilemma
Key Takeaways Nofx’s rise and fall in two months highlights inherent challenges in open source projects. A transition…

MiniMax Knocks on the Door of Hong Kong Stock Exchange with Billion-Dollar Valuation
Key Takeaways MiniMax, a prominent AI startup, is rapidly progressing towards an IPO on the Hong Kong Stock…

When AI Starts Spending Money: Who Will Underwrite Agent Transactions?

When the Prediction Market Shifts from 'Predicting' to 'Revealing the Truth': Delphi Officially Launches Prediction Market Coverage

Key Market Insights from December 19th, How Much Did You Miss Out?
WEEXPERIENCE Whales Night: AI Trading, Crypto Community & Crypto Market Insights
On December 12, 2025, WEEX hosted WEEXPERIENCE Whales Night, an offline community gathering designed to bring together local cryptocurrency community members. The event combined content sharing, interactive games, and project presentations to create a relaxed yet engaging offline experience.

AI Trading Risk in Cryptocurrency: Why Better Crypto Trading Strategies Can Create Bigger Losses?
Risk no longer sits primarily in poor decision-making or emotional mistakes. It increasingly lives in market structure, execution pathways, and collective behavior. Understanding this shift matters more than finding the next “better” strategy.

Hands-On Guide to Participating in CZ-Supported predict.fun
AI Agents Are Replacing Crypto Research? How Autonomous AI Is Reshaping Crypto Trading
AI is moving from assisting traders to automating the entire research-to-execution process in crypto markets. The edge has shifted from human insight to data pipelines, speed, and execution-ready AI systems, making delays in AI integration a competitive disadvantage.

Key Market Information Discrepancy on December 19th, a Must-See! | Alpha Morning Report

AI Trading Bots and Copy Trading: How Synchronized Strategies Reshape Crypto Market Volatility
Retail crypto traders have long faced the same challenges: poor risk management, late entries, emotional decisions, and inconsistent execution. AI trading tools promised a solution. Today, AI-powered copy trading systems and breakout bots help traders size positions, set stops, and act faster than ever. Beyond speed and precision, these tools are quietly reshaping markets — traders aren’t just trading smarter, they’re moving in sync, creating a new dynamic that amplifies both risk and opportunity.
AI Trading in Crypto Explained: How Autonomous Trading Is Reshaping Crypto Markets and Crypto Exchanges
AI Trading is rapidly transforming the crypto landscape. Traditional strategies struggle to keep up with crypto’s nonstop volatility and complex market structure, while AI can process massive data, generate adaptive strategies, manage risk, and execute trades autonomously. This article guides WEEX users through what AI Trading is, why crypto accelerates its adoption, how the industry is evolving toward autonomous agents, and why WEEX is building the next-generation AI trading ecosystem.
Palmer Luckey’s Erebor Reaches $4.3B Valuation as Bank Charter Progresses
Key Takeaways: Erebor, a digital bank co-founded by Palmer Luckey, has raised $350 million, bringing its valuation to…
Kalshi First Research Report: When Predicting CPI, Crowd Wisdom Beats Wall Street Analysts
Polymarket Announces In-House L2, Is Polygon's Ace Up?
AI Trading Risks in Crypto Markets: Who Takes Responsibility When It Fails?
AI trading is already core market infrastructure, but regulators still treat it as a tool — responsibility always stays with the humans and platforms behind it. The biggest risk in 2025 is not rogue algorithms, but mass-adopted AI strategies that move markets in sync and blur the line between tools and unlicensed advice. The next phase of AI trading is defined by accountability and transparency, not performance — compliance is now a survival requirement, not a constraint.
Beacon Guiding Directions, Torches Contending Sovereignty: A Covert AI Allocation War
Key Takeaways The AI that rules today’s landscape exists in two forms—a centralized “lighthouse” model by major tech…
Decoding the Next Generation AI Agent Economy: Identity, Recourse, and Attribution
Key Takeaways AI agents require the development of robust identity, recourse, and attribution systems to operate autonomously and…
Popular coins
Latest Crypto News
Customer Support:@weikecs
Business Cooperation:@weikecs
Quant Trading & MM:bd@weex.com
VIP Services:support@weex.com