Recently, Binance Labs, the venture capital arm of Binance, has increased its investment in the field of AI. Investment director Max Coniglio publicly stated that "AI and blockchain are a powerful combination."
So, what is the appeal of AI+blockchain?
The key point is that they can complement each other and overcome each other's weaknesses. On the one hand, AI can improve the user experience of blockchain and enhance decentralized systems. On the other hand, blockchain can ensure the authenticity of AI data, promote collaboration of open source projects, and support the computing needs of AI.
At the same time, the AI track is also a hot spot in this round of cycles. Therefore, in this article, Biteye has reviewed the AI projects invested by Binance Labs and the corresponding ways to participate.
Project Inventory
Note: Total financing is all disclosed financing
1. Sahara:AI network infrastructure, helping AI assetization. Total financing of 49 million US dollars, invested by Binance Labs, Pantera Capital, etc.
2. MyShell:Decentralized AI Agent generation platform. Total financing of 16.6 million US dollars, invested by Binance Labs, OKX, Dragonfly, etc.
3. DIN:Modular AI native data preprocessing layer. Total financing of 8 million US dollars, invested by Binance Labs, HashKey Capitall, etc.
4. Pentagon Games: Web3 artificial intelligence game publisher. Total financing of 6 million US dollars, invested by Binance Labs, Animoca Brands, etc.
5. Privasea: AI privacy computing platform based on fully homomorphic encryption. Total financing of 5 million US dollars, invested by Binance Labs, OKX, etc.
6. Swan Chain: L2 OP super chain built specifically for AI computing. Total financing of 3 million US dollars, invested by Binance Labs, SNZ Holding, etc.
7. CoralApp: Launched Coral Phone, Binance's first mobile phone project. Total financing of $3 million, invested by Binance Labs and others.
8. Aggregata: A decentralized data market based on AI. Total financing was not disclosed, invested by Binance Labs, etc.
9. StarryNift: A gamification platform integrating NFT creation and trading. Total financing was not disclosed, invested by Binance Labs, OKX, etc.
10. QnA3.AI: An AI-driven Web3 knowledge sharing platform. Total financing of $250 million, invested by Binance Labs, etc.
11. NFPrompt: A privacy-centric, scalable proof-of-stake (PoS) Layer 1 smart contract platform. Total financing of $45 million, invested by Binance Labs, a16z, Polychain, etc.
12. Hooked Protocol:Integrates AI, Metaverse and Web3 education. Total financing of $8.5 million, invested by Binance Labs, Hongshan, etc.
13. Arkham:Based on AI encryption analysis platform and data tracking dashboard. Total financing of $2.5 million, invested by Binance Labs, etc.
14. Sleepless AI:AI-based virtual companion game. Total financing is not disclosed, invested by Binance Labs, Foresight Ventures, etc.
Prospect Analysis
Binance Labs' investment in AI aims to promote the combination of AI and blockchain technology, thereby promoting the development of decentralized applications (DApps). For example, by investing in decentralized platforms such as Sahara AI and MyShell, AI is used to enhance the user experience of blockchain and ensure the authenticity and security of data.
The AI track showed obvious development potential in the first half of 2024. With technological progress and the growth of market demand, we expect the AI track to further develop in the second half of the year. However, despite the optimistic outlook, the market still faces challenges. For example, the life cycle of AI applications is generally short, and users are less willing to pay, which may inhibit innovation and sustainable development. In addition, the overall environment of the market is also affected by factors such as regulation and liquidity, and future investment opportunities will depend on the market's ability to respond to these challenges.
Therefore, although the AI track shows strong growth potential, these risks still need to be carefully assessed. For a good project, an innovative technical foundation and a sustainable business model are both indispensable. Whoever can seize the opportunity may become the winner in the future AI track.