Lithium Finance announcing its Mainnet Beta Launch

The Mainnet Beta launch introduces three essential features to deliver decentralized NFT valuations.

1. Machine Learning

Lithium Finance's proprietary algorithm analyzes millions of transactions to produce instant valuation for every NFT. Its quantitative models also identify potentially inaccurate Machine Learning valuation, such as unreliable price prediction for rare NFTs due to insufficient trading history. In those cases, Lithium Finance supplements machine learning with wisdom from the community via its hybrid pricing model.

2. Collective Intelligence

Crowd wisdom from the community is what sets Lithium Finance apart. Lithium finance approaches NFT valuation from a behavioral finance perspective. It consults the community to fill the pricing information gap where there is statistically insufficient trading data. The community is incentivized to contribute genuine market insights through the protocol to earn rewards.

3. Hybrid Real-time Valuation

Lithium Finance's hybrid valuation model incorporates both traditional machine learning and community inputs to provide holistic valuation for any NFTs in real-time, even when there is a lack of historical trading data.

Lithium Finance harnesses collective intelligence to provide accurate illiquid assets valuation through its sustainable tokenomics. Initially, the project will focus on providing valuation for NFT collections.

FIRST Pricing Quest & Airdrop

In their FIRST Pricing Quest, Lithium Finance will be giving out 1 Million $LITH in prizes. You can join their Pricing Quest starting from 12 December 10am UTC.

To celebrate their Mainnet Beta launch, the project will also give away 1212 $LITH to 1212 participants who joined the first quest! A launch party will be held on 14 December 2022 in Taiwan during the Taipei Blockchain Week. Join their discord for more information.

Hashtag: #DeFi #NFT #Price2Earn #Web3 #ETH #Polygon #Valuation

The issuer is solely responsible for the content of this announcement.

References

1. ^{^} Media OutReach (www.media-outreach.com)