The Centralization Challenges of Modern Artificial Intelligence

The Centralization Challenges of Modern Artificial Intelligence

Decentralized AI is far from becoming mainstream but its addressing many important challenges of the current generation of AI technologies…

One of the pivotal challenges of the next decade of artificial intelligence(AI) is to determine whether data and intelligence are democratized or remain in control of a few large organizations. A few months ago, I wrote a three-part series of the decentralization of artificial intelligence(AI). In that essay, I tried to cover the main elements that justify the movement of decentralized AI ranging from economic factors to technology enablers as well as the first generation of technologies that are developing decentralized AI platforms. The arguments made in those articles were fundamentally theoretical because, as we all know, the fact remains that AI today is completely centralized. However, as I work more in real-world AI problems, I am starting to realize that centralization is an aspect that is constantly hindering the progress of AI solutions. Furthermore, we should start seeing centralization in AI as a single problem but as many different challenges that surface at different stages of the lifecycle of an AI solution. Today, I would like to explore that idea in more detail.

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