Once thought of as distinct trends in technology—artificial intelligence and blockchain—are rapidly converging. These diverse sub-sectors include everything from decentralized energy and decentralized physical infrastructure networks to model fine-tuning and computation infrastructure. Some skeptics might balk at startups that advertise their use of AI and blockchain, the two biggest buzzwords in business today, believing that they are simply trying to ride the hype of both. After all, if some companies already engage in AI washing, why not go a step further and also add blockchain to the mix? In truth, the intersection of AI and blockchain is not marketing hype. As I wrote in the H1 2024 report at HashKey Capital, AI and blockchain are uniquely complementary, enabling solutions far greater than the sum of their parts. Just imagine how much data you input into ChatGPT and other similar tools daily. Now multiply that by all the daily active users, along with the LLM developers who are ingesting terabytes of data for model training. In short, the world is entrusting a staggering amount of data to AI. GenAI thus represents a major attack vector for data breaches. For example, hackers could blackmail enterprises by releasing their employees’ GenAI logs, similar to how they threaten the leak of private data in ransomware attacks. These logs are especially sensitive given the breadth and depth of questions, content, data, and confidential information we input into our prompts. Fortunately, one of the key tenets of blockchain is privacy: Through decentralization, users are spared the public scrutiny that often accompanies centralized systems, where they are subject to vetting by intermediaries and other large players. To this end, blockchain has developed several technologies that can enhance privacy, such as ZKML, OPML, and TEEML.

Full opinion : How Blockchain can help in building trust and privacy in artificial intelligence apps.