Leemon Baird first published his work on Hashgraph -Consensus in 2016 and placed it as an alternative to traditional blockchain architectures. With a background in computer science and a career that spans both academia and industry, Baird Hedera founded to commercialize technology.
His academic course is remarkable for his early work in neural networks and reinforcement learning in the 1990s, a period when AI research navigated in what would later be called “Ai Winter.” Since then, the Hedera project has evolved in a landscape filled with competing distributed headbox methods, each claiming technical superiority and targeting different segments on the market.
Baird, a speaker in Consensus 2025, easily transcends between technical explanations and business strategy, reflecting the double challenges of building both a new technology and a viable ecosystem around it.
This interview has been condensed and easily edited for clarity.
Coindesk: Your Hashgraph algorithm emerged in 2016 during a period when many alternative consensus mechanisms were suggested. What technical restrictions on previous approaches did you specifically try to tackle?
Baird: I love computer science and the mathematical side of it – to initiate things and solve problems. When I became an entrepreneur 25 years ago, it was the same process. The essence of what I always do is try to understand the basic problem we are trying to solve. What is the real question? What are we really trying to achieve? And then you build on it and solve this problem. In Blockchain was the basic question I asked: Bitcoin is cool but it is slow and not as safe as it could be with abt [Asynchronous Byzantine Fault Tolerance]. It burns a lot of energy and is not as flexible as we might. I was wondering if the lower layer of consensus itself is a way to avoid burning lots of energy while still fast and safe. Is it possible to achieve ABFT – the strongest kind of security – while I am also super -fast and not burning electricity or dumping carbon in the atmosphere?
I started working on this in 2012 as one of many math problems I explored. Originally, I was convinced that it could not be done. I wanted to pick up the problem, play with it and convince myself that it was impossible – over and over. But in 2015, I realized that it suddenly falls into place by throwing two hashish, suddenly in place. You can have the ultimate speed – essentially at the speed of the internet – while also having the ultimate security with ABFT. And that’s a proof of the spell so you don’t waste electricity.
From a business perspective was the question: What is the right way to control this? When we look at Blockchains, they often claim, “We have no governance. Anyone can help do it.” But power over time can consolidate – you end up with a handful of developers or people behind the scenes that control everything.
With Hedera we started differently. We made governance decentralized right from the beginning. We brought in some of the largest organizations in the world – top universities and businesses spread globally that people have confidence in and who have reputation to protect. They balance each other, create control and balance, and together they control the system.
It was about tackling the basic question: What do you really want in governance? What will give you genuine trustlessness, or at least a lower confidence beam needed to fully rely on the system? That was our answer – approximately business questions with the same rigor as mathematical.
Coindsk: You have mentioned RWA tookenization, carbon credits and stableecoins such as key use cases. These are areas where almost all major blockchain focuses. What specific implementations on Hedera have shown meaningful transaction volumes or user recording?
Baird: I will highlight four key areas:
First, AI is extremely exciting right now. The dangers of AI also relate to why we need to establish origin, governance and version control for AIS. People need to know if they can trust what’s happening. Hedera helps with AI in several ways, including permission data and potential handling of royalties to people who provide training data. The work that Eqty Lab does with Nvidia and Intel at Hedera is especially exciting.
Secondly, the active of the real world has transformed how we handle valuable assets. We have several projects that tokenize real estate, gold, diamonds, carbon credits and even carbon emissions at Hedera. From the beginning of Blockchain technology, I have maintained that what is important is not images of monkeys or games – that is that all things of value on the planet will eventually be posted on these headbooks.
Third, Stablecoin is important if you want adoption in the real world. We have created a stable coin study to make the stableecoin development easy on Hedera. The Hedera Council includes many financial institutions that perform impressive work with stableecoins.
Fourth, unchanging data registrations are almost unique to Hedera through our Hedera consensus service. This makes it possible to send messages to items with access control and unchanging admission. Companies like Hyundai and KIA use this for emission tracking throughout their supply chain.
Coindsk: UCLS research on energy consumption compared different networks, but methodology means significant in these comparisons. Proof-of-Stake systems generally have similar profiles, with differences that come down to the node and hardware requirements. Does Hedera’s approach differ fundamentally from other POS networks, or is the efficiency primarily from the current network configuration?
Baird: We have been thought -provoking of energy consumption right from the beginning. Everything – from our algorithms to how nodes are run and controlled, and the fact that we use evidence of rod instead of evidence of work – laid the basis for low emissions from day one.
This created a virtuous cycle. Early adopters who want to tokenize carbon credits chose the green blockchain. Then people who wanted to tokenize emissions and credits wanted to use the same blockchain where all other similar work performed. This flywheel effect has made Hedera perhaps the most popular blockchain in the green technology room.
According to University College London, Hedera has the lowest carbon emissions per year. Transaction of any blockchain. We also buy carbon credits to be carbon -negative. Being green was baked into our structure from the start, which is why we have become a leader in this area.
Coindesk: We see a lot of projects trying to combine AI and blockchain technologies. Given the different calculation paradigms, these systems work below what realistic integration points do you look beyond the marketing tales?
Baird: The intersection of AI and Blockchain is more significant than most people are aware of. At Hedera we see real traction in several areas:
Providence and governance are critical. When we enter a world where everything will be AI-generated, we need to know that we can trust AI. This requires digital signatures to verify origin-what is either human or AI created.
Permission of data is another important cross. When thousands of people contribute small amounts of data to train an AI, each person needs control over their data – the ability to give or withdraw permission.
Looking forward, I’m most excited to use Hedera for identity and incorporate identity into AI systems. We reach a point where you cannot distinguish AI-generated media from reality. The only solution is digital signatures – content must be signed by the photographer or reporter. But then you need trusted identity systems to verify these signatures.
Coindesk: After studying neural networks in the 1990s, long before the current AI boom, what is your perspective on today’s big language models? Has something fundamentally changed in the technology, or do we just see the results of scale?
Baird: Many AI developments have unfolded exactly as I expected. When AlphaGo defeated the world’s go -champion when Alphazero mastered chess when Ais conquered poker – I expected it all. They even used almost the same techniques that I had imagined. We simply needed faster computers.
Self -driving cars are also progressing exactly, which I predicted using the methods in Forsaw.
But chatgpt and large language models (LLMS) have completely amazed me. The 2017 transformer architecture – described in the paper “Attention is all you need” – represented a breakthrough that no one could have expected. Back in the 90s, we were completely blunted by language treatment – tried different approaches, but failed at each turn.
The features of today’s LLMs are still amazing me and their future remains unpredictable. Will they reach up to superintelligence? Or will they hit a ceiling? I don’t know – and I would claim no one does.
Humanoid robots have also surpassed expectations. While their physical development has matched my predictions, their conversation skills – driven by LLMs – have far exceeded what I imagined possible. In the coming years, they will start with basic factory work before moving on to skilled trades such as welding, plumbing and electrical work.
These technological advances make the industrial revolution look less in comparison. Most people have not understood the size of these changes or how fast they are approaching.
