Hedera Co-Founder Leemon Baird Discusses the Future of AI and Blockchain

Leemon Baird, a pioneer in the field of distributed ledger technology, first introduced his work on hashgraph consensus in 2016. With a strong background in computer science and experience in both academia and industry, Baird co-founded Hedera to commercialize the technology. His early work in neural networks and reinforcement learning during the 1990s laid the foundation for his current endeavors. In a recent interview, Baird discussed the evolution of the Hedera project, the challenges of building a novel technology, and the importance of establishing a viable ecosystem. When asked about the technical limitations of earlier consensus mechanisms, Baird explained that he aimed to address the fundamental problems of speed, security, and energy efficiency. He described how his hashgraph algorithm emerged as a solution, offering a fast, secure, and energy-efficient alternative to traditional blockchain architectures. Baird also emphasized the importance of governance in blockchain systems, highlighting Hedera's decentralized approach, which involves a council of trusted organizations that balance and check each other. The conversation then shifted to the topic of AI, with Baird expressing his excitement about the potential of AI and the need for provenance, governance, and version control. He cited several key areas where Hedera is making a meaningful impact, including AI, real-world asset tokenization, stablecoins, and immutable data records. Regarding the comparison of Hedera's energy consumption to other proof-of-stake networks, Baird noted that Hedera's approach differs fundamentally, with a focus on energy efficiency from the outset. He pointed out that Hedera has the lowest carbon emissions per transaction of any blockchain, according to University College London. The discussion also touched on the integration of AI and blockchain, with Baird highlighting the importance of digital signatures, data permissioning, and trusted identity systems. Reflecting on his experience studying neural networks in the 1990s, Baird shared his perspective on today's large language models, expressing both astonishment and unpredictability about their capabilities and future development. He concluded by emphasizing the magnitude of the technological advancements on the horizon, which will surpass the impact of the Industrial Revolution.