Generative AI is growing fast, bringing new ways for machines to learn, think, and create. At the same time, Web3 is working to make the internet more decentralized, where users have more control over data, privacy, and digital ownership. As these two technologies develop, they will start to connect in many ways.
Web3 should prepare for some important AI trends that could change how decentralized networks and AI-powered systems work. Here are five key trends to watch.
AI is Getting Smarter at Thinking
Recent AI models like DeepSeek R1 are learning how to think in steps, thus helping them solve complex problems more accurately. A technique called Chain of Thought allows AI to explain its reasoning, making it easier to understand how it reaches conclusions.
One issue with AI is that its decision-making process is not always clear. Web3 can help solve this by using blockchain to track AI decisions. This way, anyone can check and verify AI’s reasoning, making it more trustworthy and transparent.
AI is Learning from Synthetic Data
AI models need a lot of data to train, but gathering real-world data is expensive and sometimes unreliable. To fix this, researchers are now using synthetic data which is created by AI itself instead of being collected from real sources.
Web3 can help by rewarding users who contribute to making and verifying synthetic data. This could create a decentralized AI data-sharing network, where people earn tokens for helping AI models learn.
AI Training is Changing
Training AI models is expensive and requires powerful computers. But a new trend is shifting the focus from early training to mid-training and post-training. This means AI can keep learning and improving even after it is first created.
The change allows smaller groups or individuals to help fine-tune AI without needing large companies. Web3 can support this by letting people contribute computing power or expertise to AI training in exchange for rewards.
AI Models are Getting Smaller and Faster
Many AI models are huge and need powerful computers to run. But new techniques allow these models to be made smaller while staying just as smart. This means AI can run on personal devices instead of only on big cloud servers.
Web3 can use this trend by creating networks where smaller AI models work together across multiple devices thus reducing reliance on big tech companies and making AI more accessible to everyone.
AI Needs Better Testing
AI models sometimes memorize answers instead of truly understanding them, making it hard to know if they are actually smart or just repeating patterns they’ve seen before. Web3 can help by using blockchain to store and verify AI test results. This way, AI models can be checked fairly, ensuring they are truly improving and not just gaming the system.
As AI continues to change the world, Web3 has a chance to make sure it stays fair, open, and accessible. By embracing these trends, smarter AI reasoning, synthetic data, better training, smaller models, and fair testing, Web3 can help build a future where AI is decentralized and trusted.
As these trends take root, it is likely that a lot more innovations will be brought to market and entities like Horizon Fintex will find helpful in their operations.
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