Today, eyes were on the PCE data. Although the statements seem positive, the decline in the crypto market continues due to Fed expectations and tariff uncertainties caused by #TrumpTariffs . Despite all this decline, $LPT has returned over 100% to its investors in a short time. It is still unclear at what level #bitcoin will close May.
In such a turbulent environment, it's important to focus not only on price movements, but also on the infrastructural and technological developments that projects offer. Today, we will be looking for answers to the following question: Can projects that go beyond short-term market fluctuations and offer user-oriented technological solutions really create lasting value?
We are in the age of artificial intelligence. We use it, we develop it, we even integrate it into our daily lives. But how much do we know about how it works? #AutonomysNetwork CEO Todd Ruoff's interview with Authority Magazine takes a serious look at this question. If AI systems are not controllable, isn't it an illusion to think that we really control them?
There is a lot of truth in this statement. Many of the AI models we use today are closed boxes: decision-making processes are not visible from the outside, data usage is unclear, and systemic errors or biases can be easily hidden. According to Todd Ruoff, an advocate of open source and on-chain architecture, this can only be changed with radical transparency. As a user myself, I can tell you that as you start to understand how the system works, instead of accepting every output as it is, you can actually see that your questions increase. What makes a model reliable is not only the answer it gives, but also being able to see how that answer is formed. This is why I would like to draw your attention to the Agentic Framework developed by Autonomys.
Here, all the decision processes of AI agents are recorded in the chain, including the thinking and planning steps. Agents like Argu-mint learn from social media interactions and transparently document this process. In theory, this sounds impressive. In practice, I wonder how such a detailed logging system is optimized, because there is always a trade-off between user experience and in-system efficiency. But this structure certainly sets a standard, at least for users who want control.
Ruoff's warnings about the centralization of AI are also hard to ignore. The fact that the most powerful models today are under the control of a few tech giants is not just a technical problem, it's a societal one. Decentralized structures are promising, but I still have questions about their sustainability. The “data ownership” model proposed by Autonomys, the idea that the user can control and monetize their own data, is impressive. But I can't speak for sure until I see it become widespread on a user basis.
The real impact of the interview lies not so much in the technical details, but in the clear vision of how AI should be governed, by whom and with what values.
Todd Ruoff CEO of Autonomys argues that AI should not be a system controlled by a few private entities, but should take shape on a decentralized and transparent infrastructure. For him, this is not just a design choice, but a process in which ethical responsibilities must be shared across society.
The approach behind this vision is not limited to technological development. Together with @DAO Labs ' #SocialMining model, Autonomys aims to build communities of conscious users in the age of artificial intelligence. Because there is a need for a community that not only uses AI, but also understands how it works and questions it when necessary. In the background is the Subspace Protocol, which does not require energy consumption and works with PoAS consensus based on Nakamoto's honest majority assumption. Autonomys builds all the infrastructure needed to create AI-powered super dApps and autonomous agents on this decentralized layer.
In conclusion, AI is not only a technological evolution, but also a matter of governance, ethics and participation. If we are to build the future together, we need to define together how the systems we use work. Autonomys' proposed model reminds us that we need to be participants in this process, not just spectators.
