Guys, let's quickly summarize a few projects coming up for TGE, you can check them out, do your own research (DYOR)～

Core Innovation: Use the OneBalance chain abstraction toolkit to eliminate multi-chain operations—users do not need to be aware of chains, bridges, or Gas tokens, and can trade cross-chain perpetual contracts (ETH/ARB/OP, etc.) like using a CEX, aggregating liquidity from Hyperliquid and SynFutures.
Data speaks: $8.4 billion in cumulative trading volume over 14 months, V2 mainnet just launched, points system activated (trade to mine $VOOI airdrop).
Business model: earn fee sharing + exchange rebates, aiming to create a DeFi version of Robinhood, targeting the retail investor incremental market.
Risk Point: Dependence on the technical stability of the partner OneBalance. If there are cross-chain delays or vulnerabilities, it may lead to disputes over liquidation.
Summary: Addressing the urgent need for DeFi operations that are user-friendly, but it is necessary to verify the liquidity depth in a bear market.

Core Innovation: Networking with Aethir's 400,000 GPU nodes to create the GameFAI low-latency competitive chain—real-time AI training + game data monetization, players use $ELY tokens to bet on match outcomes and cultivate esports AI agents.

Profit logic: Collecting registration fees for competitions + selling AI training data (such as League of Legends battle strategy datasets).
Risk points: Compliance pitfalls in esports games (related to gambling), and the potential transfer of GPU operation costs to players may crush the economic model.
Summary: The scarcity of competitive blockchain games, but compliance is like licking blood off a knife.

Core innovation: Create an on-chain AI agent arena - agents store strategies on the Ceramic network, users bet on competition outcomes (e.g., trading competition AlphaWave prize pool of $25,000), knowledge can be traded.
Cold Start Strategy: 500,000 accounts on the testnet brushing Surge points (accounting for airdrop weight), Coinbase and Animoca staking 39 million dollars.
Source of income: lottery competition fees + selling verification node computing power (requires staking tokens).
Risk points: It is difficult to prevent and control agent cheating, and
Summary: DAO-style AI training is innovative, but be careful of becoming a "PPT battleground" before implementation.

Core innovation: Quantifying data contributions into money using Proof of Attribution (PoA) - for example, when a doctor uploads medical data and it is utilized by an AI diagnostic model, automatic revenue sharing in $OPN tokens.
Moat: Lightweight framework OpenLoRA runs a thousand models on a single GPU, cutting costs by 99%; raised 8 million dollars (co-invested by Polygon founder).
Airdrop Strategy: Earn 2000 points per day by running on the testnet, with the top 200 players on the Kaito leaderboard sharing 2 million OPN.
Risk points: The huge pitfall of cross-border compliance for medical/financial data, competitors like Spectral play the same trick.
Summary: It addresses the pain points of AI data exploitation, but compliance is the sword of Damocles.

Core innovation: Tokenizing the process of training AI by humans - users earn $SAPIEN by completing annotation tasks (such as teaching AI to recognize images), data is put on the blockchain as training materials, feeding back into model iteration.
Model advantages: Specifically addresses ChatGPT's "garbage in, garbage out" by using real human data to improve model accuracy.
Early dividends: Discord ambassadors can earn contribution coefficient bonuses, suitable for users in labor-intensive regions to grind.
Risk Point: Centralized task pricing power, the platform may exploit labor (similar to Amazon Mechanical Turk).
Summary: The Web3 version of a data labeling factory earns hard-earned money but the demand is real.

Operation Priority:

Short-term profit: Rush into OpenLedger for mining and Vooi trading, low cost and transparent;
Long-term layout: betting on Recall agent development to reap the benefits of the AI + DeFi track;
Caution in the field: The input-output ratio of Sapien's human resources is questionable, beware of becoming a "digital tenant farmer."