Data is the backbone of the modern world and is driving innovation in various industries. When it comes to blockchains and decentralized finance (DeFi), data plays an even more crucial role. With a new solution called Flare Network, data can now be utilized in a more efficient and secure manner. During the second day of Token2049 in Singapore, we sat down with Hugo Phillion to discuss his thoughts on the current state of the blockchain industry and his project, Flare Network.
The Role of Artificial Intelligence For Blockchain
As the Co-Founder and CEO of Flare Network, Hugo Phillion has extensive knowledge and experience in both the blockchain and artificial intelligence (AI) industries. The conversation starts off with a brief overview about large language models' role in the blockchain space.
With the rise of AI and machine learning, large language models have become increasingly important for data processing and analysis but to fine tune and optimize them, layers of tailored blockchain embedding is needed. Hugo expresses that a Hackathon is planned in the near future to gather feedback and improve the current model.
AI can make blockchains better but the opposite is also true. As blockchain technology continues to evolve and scale, it provides a more robust and secure platform for AI applications. With the help of smart contracts, data can be shared between different parties securely and efficiently. Blockchain can give resistance to malicious actors and ensure the integrity of data, making it an ideal infrastructure for AI.
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The Flare Network's Approach To 'Connect Everything'
If someone in the street came to you and said, "Can I borrow a million dollars," you'd be unsure if you can trust them or not. In the loan industry, collateral is used to minimize risk and give assurance that the borrower will repay the amount borrowed. This is what's known as a security model. As an analogy, the problem with current oracle systems (which are used to supply data to smart contracts) is that they do not provide any collateral. Users essentially have to just trust the provider of the data, which can lead to potential vulnerabilities and manipulation.