Futures
Access hundreds of perpetual contracts
TradFi
Gold
One platform for global traditional assets
Options
Hot
Trade European-style vanilla options
Unified Account
Maximize your capital efficiency
Demo Trading
Introduction to Futures Trading
Learn the basics of futures trading
Futures Events
Join events to earn rewards
Demo Trading
Use virtual funds to practice risk-free trading
Launch
CandyDrop
Collect candies to earn airdrops
Launchpool
Quick staking, earn potential new tokens
HODLer Airdrop
Hold GT and get massive airdrops for free
Pre-IPOs
Unlock full access to global stock IPOs
Alpha Points
Trade on-chain assets and earn airdrops
Futures Points
Earn futures points and claim airdrop rewards
Promotions
AI
Gate AI
Your all-in-one conversational AI partner
Gate AI Bot
Use Gate AI directly in your social App
GateClaw
Gate Blue Lobster, ready to go
Gate for AI Agent
AI infrastructure, Gate MCP, Skills, and CLI
Gate Skills Hub
10K+ Skills
From office tasks to trading, the all-in-one skill hub makes AI even more useful.
GateRouter
Smartly choose from 30+ AI models, with 0% extra fees
Deputy Director of the National Institute of Scientific Research: Incorporate computing power and power grid planning into a unified spatial system, moderately ahead of schedule, dynamically adapting to AI development
Mars Finance News, April 29—On April 28, a thematic exchange activity on data development theory and practice, hosted by the National Institute of Data Development, was held in Fuzhou. During the event, the “Computing-Power Coordination Technology and Industry Integration Innovation Consortium” was established. Yuan Jun, Deputy Director of the National Institute of Data Development, spoke to the media about the background and significance of the consortium’s formation.
He said that currently, the development of computing-power coordination faces a coordination dilemma among three goals—security, green development, and economic outcomes—namely the “impossible triangle” challenge. First, the rapid growth in demand for computing power is mismatched with the long construction cycle of energy infrastructure, making “electricity waiting for computing” prone to over-allocation and resource waste. A whole-country approach is needed: incorporate computing power and power grid planning into a unified spatial framework, with moderately forward-looking planning and dynamic adaptation to AI development. Second, the intermittency of renewable energy conflicts with the high-reliability requirements of intelligent computing, and there is insufficient energy storage for peak shaving and lagging collaborative scheduling. We need to strengthen technological breakthroughs, overcome load-forecasting and cross-domain collaborative dispatching technologies, and improve flexible interaction capabilities. Finally, projects integrating computing and power require large investments, but the environmental premium of green electricity and the benefits of carbon-reduction are difficult to internalize, and the electricity-carbon market is not yet connected. We need to improve the electricity-carbon coordination mechanism, form a market-oriented investment return system, and unleash the motivation for participation by multiple stakeholders.
(The Paper)