the first ever Monad Testnet Fantasy Top tournament goes live in <24 hours
over 200,000 players have signed up to compete for more than 5,000 whitelist spots for NFT collections on Monad
set your deck now at https://t.co/s3anlNr8Ss
NFT week is live on Monad testnet
Expect ecosystem mints and experiences, including weekly NFT whitelists for Fantasy Top winners
Explore here: https://t.co/m9sDIlucxu
Interested in joining the 60,000 GPU workers on https://t.co/WLXlHkvE4z and building the largest AI compute DePIN in the world?
Check out the installation guide from our Turkish community ambassador @okansariirmak
Bring AI to the world.
BREAKING: https://t.co/ZuybGWvRkH has raised $30M to build the largest decentralized GPU network in the world and solve the AI compute shortage.
The Series A round was led by Hack VC with participation from Multicoin Capital, 6th Man Ventures, M13, Delphi Digital, Solana Labs, Aptos Labs, Foresight, Amber, Longhash, SevenX, ArkStream, Animoca Brands, Continue Capital, MH Ventures, Sandbox Games.
Prominent industry leaders also joined the funding round, including Solana founder Anatoly Yakovenk, Aptos founders Mo Shaikh and Avery Ching, Yat Siu of Animoca Brands, Sebastien Borget of The Sandbox, and Jin Kang of Perlone Capital.
https://t.co/uFcYdqYmHL
What makes @ionet_official different from other GPU aggregators on the market?
@ionet_official's ability to form decentralized clusters by aggregating GPUs across multiple locations.
Without clustering, it would be virtually impossible to train today's machine learning models, which are highly complex.
This creates the opportunity for a 'structural arbitrage', allowing @ionet_official to offer unmatched cost efficiency and low latency GPU compute up to 90% cheaper than the competition.
What makes @ionet_official different from other GPU aggregators on the market?
@ionet_official's ability to form decentralized clusters by aggregating GPUs across multiple locations.
Without clustering, it would be virtually impossible to train today's machine learning models, which are highly complex.
This creates the opportunity for a 'structural arbitrage', allowing @ionet_official to offer unmatched cost efficiency and low latency GPU compute up to 90% cheaper than the competition.