Part of the magic of Generative AI is that most people have no idea how it works. At a certain level, it’s even fair to say thatis entirely sure how it works, as the inner-workings of ChatGPT can leave the brightest scientists stumped. It’s a black box. We’re not entirely sure how it’s trained, which data produces which outcomes, and what IP is being trampled in the process. This is both part of the magic and part of what’s terrifying.
Joined by her colleague Andrew Stanco , Spring shares how crypto can create more transparent AI, how these tools are already being deployed in service of climate change science, and why these open-sourced models can be more inclusive and representative of humanity at large.We're pioneering new solutions to build trust and innovation in AI. And generative AI is kind of the hot topic right now, and that's the most emergent property, so that's something that we're focused on.
So, in a process as complex as AI training, having those tamper-proof and verifiable attestations — both during the training and afterwards — really helps. It creates trust and visibility.What we do is that at each step of the AI life cycle and training process, there’s a notarization — or a stamp — of what happened. This is the decentralized ID, or identifier, that’s associated with the agent or human or machine that’s taking that action. You have the timestamp.