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- GT Airdrop Is Live! 1.92M GT Burned in Q2, Worth Over $39M
🎁 Complete simple tasks, get up to 13.2 GT per user
📅 From July 8 to July 20
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- 📢 #Gate Square Writing Contest Phase 1# is now officially launched!
Share your unique insights on the CROSS project and stand a chance to win $500 worth of CROSS rewards!
💰 Rewards:
1st Prize (1 winner): $150 worth of CROSS
2nd Prize (3 winners): $50 worth of CROSS each
3rd Prize (10 winners): $20 worth of CROSS each
👉 How to Participate:
1. Publish your unique insights on the CROSS project in Gate Square.
2. Add the tag #Gate Square Writing Contest Phase 1# to your post (minimum of 300 words).
3. Share your article or insights on X with the tags: Gate Square & CROSS.
Essay Content Directio
- 🎉 #Gate xStocks Trading Share# Posting Event Is Ongoing!
📝 Share your trading experience on Gate Square to unlock $1,000 rewards!
🎁 5 top Square creators * $100 Futures Voucher
🎉 Share your post on X – Top 10 posts by views * extra $50
How to Participate:
1️⃣ Follow Gate_Square
2️⃣ Make an original post (at least 20 words) with #Gate xStocks Trading Share#
3️⃣ If you share on Twitter, submit post link here: https://www.gate.com/questionnaire/6854
Note: You may submit the form multiple times. More posts, higher chances to win!
📅 End at: July 9, 16:00 UTC
Show off your trading on Gate Squ
- 🚀 Calling all Gate Square content creators!
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#GateSquare#
The Fourth Paradigm launches the large-scale model reasoning integrated solution SageOne IA
Jinshi data news on February 26th, Fourth Paradigm (06682.HK) launched the large model inference integrated machine solution SageOneIA today, further reducing the cost of large model inference. For example, the full version of DeepSeekV3/R1 only requires two integrated machines to use. In addition, the integrated machine solution also integrates intelligent Computing Power pooling technology. On the basis of supporting mainstream large models such as DeepSeekV3/R1, QWen2.5, LLama3.3, enterprises can flexibly switch between the full version and multiple distillation models, with GPU utilization rate increased by more than 30% and inference performance increased on average by 5-10 times.