In a recently published essay, Microsoft's Satya Nadella outlines a fundamental defect in today's centralized AI industry: The fact that customers must relinquish their personal or enterprise data to use advanced AI systems.
In the AI age, the buyer risks giving away knowledge, just in order to use what they bought.
You essentially pay for intelligence twice, once with money, and again with something even more valuable: the proprietary knowledge you must reveal to make that intelligence useful. The better you want the model to perform, the more of that knowledge you have to feed it!
Over time, the information asymmetry becomes increasingly skewed. The seller learns more and more about you as you use what you purchased, while you learn very little about what the seller is learning in return.
The CEO of Microsoft, the company that has invested in both OpenAI and Anthropic, goes on to critisize these same labs for preventing clients from studying their frontier models and using the insights to train their own models.
What Nadella presents as the solution is, in fact, what the Decentralized AI community has been championing for years: data ownership, proprietary learning infrastructure, and private AI inference.
That is why enterprises need a real trust boundary for their human capital and token capital to compound. It is where an organization’s data, traces, evals, adapted weights, and memory accumulate and improve together. And it is a hard boundary across which nothing crosses, not even the intelligence exhaust, without consent. Enterprises will demand the rights to use model outputs to fine tune and/or train their own models. I think of this as every firm’s right to align models to their enterprise accountability obligations.
The Reverse Information Paradox
I've been thinking a lot about what the net benefit of the AI platform wave is.
Moreover, he virtually urges enterprises to move away from relying on one single "generalist" model and instead build "orchestration layers" and "continuous learning loops" where it is easy to switch between different models. As TechCrunch comments:
While Nadella never uses the words “open source” as the method for retaining ownership, this is an obvious subtext. Yet, there’s another subtext.
After experimenting with proprietary model makers, [large companies] start asking themselves: “Can I take an open source model and run it on-prem? It will do almost 90% of what the big one’s doing. It will cost way less.”
Satya Nadella has issued a shocking warning to companies using AI | TechCrunch
Of all the debates raging about the potential downsides of AI, there is one worry causing the most hand-wringing among AI enthusiasts in Silicon Valley - that the giant AI labs that sell proprietary models are somehow acting like Trojan horses.
Though, Nadella goes even further - while echoing Alex Karp, he scolds "the current regime" for not allowing customers to have control over their own compute resources, models, data stack, and alpha:
As Alex Karp put it: “What the technical customers want is control over their compute, their models, their data stack, and their alpha. They want to know they own the means of production, and it’s not being transferred to someone else.” The current regime does precisely the transfer Karp and companies fear.
TechCrunch reads this as urging corporations to build their own AI infrastructure on the cloud - preferably, Microsoft Azure:
Nadella’s solution is the kind of thing the CEO of a giant cloud provider would suggest. He wants companies to “retain ownership” of their data, including prompts, feedback, etc. So he’s urging them to build their own “proprietary learning environments” on the cloud (where their data is likely already stored anyway and, conveniently, could mean Microsoft’s cloud, Azure).
But I don't. Microsoft's cloud is still a centralized Big Tech platform. As long as your AI stack depends on infrastructure you don't own or control, you cannot claim true sovereignty over your data, models, or compute. If a company truly wants to retain control over its AI infrastructure, it would be better served by a distributed cloud - a more resilient and cost-effective alternative.
I'm generally puzzled by Nadella's stance. Don't get me wrong - I appreciate the inadvertent endorsement, because his essay underscores exactly why Decentralized AI matters. For years, the DeAI community has advocated for distributed training and inference, verifiable computation, and open-source models as the only viable path to making AI private, safer, more affordable, and universally accessible.
Yet, Nadella - and, for that matter, Karp - is not a disinterested observer or some bistanding analyst. He is an integral part - not to say one of the architects - of that "current regime" he mentions. After all, Microsoft is the backbone of today's centralized AI industry.
Which begs the question: what is he really suggesting? His proposal cuts against the business models of OpenAI and Anthropic, and, by extension, Microsoft's own financial interests as their key partner.
I completely agree with Nadella that the future of the AI belongs to open-source, privacy-preserving alternatives. But where would that leave OpenAI, Anthropic, Meta, SpaceXAIA, and the rest of the hyperscalers that Microsoft ultimately supports?
Demis Hassabis, CEO and co-founder of Google DeepMind and a laureate of The Nobel Prize for his work on AlphaFold, calls for a global framework for Frontier AI security, but one lead by the United States of America.
At first glance, what Hassabis suggests is sensible. He turns to the AI industry, and the world as a whole, and pleads: AI will be creating unprecedented challenges, so instead of racing each other, let's collectively try to mitigate the risks. I'm paraphrasing. However, what he proposes in practice is much more nuanced:
The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous. The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organisation, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives.
This US-initiated effort would provide a strong starting point for creating shared international standards on Frontier AI. Since this technology is going to affect the entire planet, ideally this framework would spur the international community to reach a consensus on how to manage the most serious risks while ensuring everyone has access to and can benefit from the opportunities that AI brings.
The article was met with a hint of indignation and provoked two reasonable questions which I was also inclined to ask while reading: why should the US lead these efforts, and isn't an "industry-funded watchdog" an oxymoron? Two comments left under Hassabis's article on LinkedIn summed up these concerns perfectly, so I'm sharing them with you - the first is by Adi Gaskell and the second - by André Carmo.
I'm curious why this should be US-led, especially when the UN met last week on this very topic. This is a global issue, and I'm not sure there's any appetite in the world for US values to lead the way on this, especially under the current administration. It also seems highly problematic for the standards body to be funded by the industry itself. Responsible AI has already shown that self-regulation is not the way to go.
The FINRA analogy is the part worth stress-testing. Industry-funded standards bodies work when their incentives are structurally independent of the firms they assess. When they aren't, they drift toward legitimizing incumbents. The proposal hints at this with held-out evals and independent board seats, but one design question will decide most of it: can this body actually afford to fail a model its funders spent a billion dollars training? If it can, then it's real governance. If it can't, it becomes a compliance ritual that makes everyone feel safer than they are. Getting the incentive design of the Standards Body right looks as hard as designing the benchmarks themselves, and probably matters more.
Moreover, Hassabis clearly writes with the conviction that AGI is imminent. He goes as far as posing questions, which, in my opinion, are way premature:
Even if we solve these hard technical challenges, there will be further complex economic and philosophical questions to tackle: what sorts of new economic models will be needed to help everyone thrive in a post-scarcity world? What values do we want to live by, what will meaning and purpose be, and how might even the human condition itself change?
Shouldn't we take a step back and focus on agreeing what AGI even means first? If we still don't have a clear definition of AGI, who and how will determine when we've actually reached it? After all, a general artificial intelligence that surpasses human capabilities in every domain possible is still only hypothetical.
Also - and that is quite unfortunate - there appears to be no evidence whatsoever that the current advancement of AI is leading us towards a post-scarcity world. On the contrary, wealth is becoming increasingly concentrated in the hands of a few (US-based) tech founders.
So let's start there. Should we empower these same tech founders to set the AI standards for the rest of the world? I don't think so.
A Framework for Frontier AI and the Dawning of a New Age
This is a pivotal moment in human history. Artificial General Intelligence (AGI), a system that exhibits all the cognitive capabilities the brain has, is probably only a few short years away.
Thank you for reading! My name is Albena, and every day I share insights into the groundbreaking convergence of blockchain and AI. If you’re enjoying them, hit the subscribe button and never miss a key Crypto × AI update.
The Web3 + AI Newsletter is an independent, ad-free publication that I have been building on my own since 2023. If you find value in my work, please consider supporting it by choosing one of the subscription tiers available at the link below. I greatly appreciate it.
The Web3 + AI Book Club is live on Fable! Join us in exploring our July title - 'Empire of AI' by Karen Hao. Follow the link below to read with us.
I'm looking forward to connecting with fellow Crypto x AI enthusiasts, so don't hesitate to reach out on social media.
Disclaimer: None of this should or could be considered financial advice. You should not take my words for granted; rather, do your own research (DYOR) and share your thoughts to encourage a fruitful discussion.