Web3, as the next generation of the Internet, is characterized by decentralization, user-centricity and the integration of artificial intelligence (AI). This revolutionary paradigm shift is moving away from centralized platforms, where control over data and resources is concentrated in the hands of the few, to an ecosystem where users have greater autonomy and ownership of their data. Web3 marks the transition from passive content consumption to active user participation. Users become creators, owners and actors in this new digital ecosystem. AI makes this possible by providing data analysis, prediction and decision-making tools that help users take better control of their online experience. In this new environment, Web3 and artificial intelligence play a key role, leading to revolutionary changes in the way we interact with data and personalize our own experiences. Companies specializing in Web3 in synergy with AI are coming to the fore, developing innovative solutions for decentralized data markets. These platforms empower users to own, control and monetize their data, eliminating monopolies and promoting greater transparency and honesty. Thanks to AI algorithms, these data markets have become more efficient, secure and flexible, opening up new opportunities for collaboration and information sharing.

What are Web3’s specific AI projects?

Smart contracts with AI

This is heavily exploited by the Zilliqa blockchain platform, which takes a significant step forward in computing by relying on its own Scilla smart contract programming language and an innovative parallel processing architecture based on sharding. Through sharding, the blockchain is broken up into smaller, more manageable networks known as subnets. This allows you to distribute computing tasks between them, making their execution parallel. Zilliqa differs from other blockchain platforms, such as Bitcoin and Ethereum 1.0 due to its unique architecture that allows for high scalability. Although Zilliqa uses a Proof-of-Work (PoW) consensus mechanism similar to those platforms, it solves the scaling problem. Sharding, in turn, breaks the decentralized Zilliqa network into smaller segments called shards. This allows for parallel processing of transactions in different shards, greatly increasing the throughput and efficiency of the blockchain. The company became the first public blockchain platform to implement sharding when its main net launched in 2019. This is a significant achievement that underscores Zilliqa’s leadership in blockchain innovation and scaling.

*Predictive modeling and data analysis
*

A clear example is Numerai, a decentralized artificial intelligence platform based on the Ethereum blockchain. It enables anyone to submit their own machine learning models to predict stock market movements. The project is a kind of collective artificial intelligence for forecasting the stock market. The main goal of the project is to create more accurate and reliable machine learning models by combining the predictions of thousands of data scientists from around the world. Numerai is based on encrypted data that will prevent manipulation and abuse of underlying financial data. Numerai is a unique platform that combines blockchain, encryption and artificial intelligence to create a new paradigm in stock market quantitative analysis and forecasting. Instead of using traditional forecasting methods, the project uses the collective mind of the machine learning community. This will find its direct application on crypto-exchanges, where everyone will be able to do their job well. For example, we have a wide selection of exchanges, especially popular ones such as Upbit, KuCoin or WhiteBIT.

Computing platforms

DeepBrain Chain combines artificial intelligence and blockchain and is a computing platform in its essence. Its goal is to create a decentralized neural network that will significantly reduce the cost of artificial intelligence calculations. DeepBrain Chain combines the power of mining machines to create a decentralized network that offers affordable and scalable GPU computing power for deep learning and AI. By using inactive mining resources, DeepBrain Chain significantly lowers the cost of access to computing power, making AI more accessible to a wider range of users. The platform can run deep neural network models and algorithms for training artificial intelligence systems, and has its own DBC token that incentivizes network participants and rewards resource providers. The main application areas of the platform could be fraud detection systems that can analyze transactions and user behavior to detect suspicious activities. Also in the space of healthcare, in particular drug development, disease diagnostics and personalized medicine.

Conclusion

Growing investments and research in the space of blockchain and artificial intelligence give reason to expect significant progress in the coming 5–10 years. Improvements in blockchain platforms and AI models will likely lead to exponential growth in the possibilities these technologies can offer together.

The synergy between blockchain and artificial intelligence has the potential to drive innovation in both directions. The decentralized and stable nature of the blockchain can be the foundation for the scaling and secure operation of artificial intelligence algorithms. On the other hand, artificial intelligence can optimize and automate many aspects of blockchain operation, making it more efficient and user-friendly.

Although projects combining blockchain and artificial intelligence are in the early stages of development, they already show enormous potential. Thanks to the synergy of these technologies.