Entering the Age of Decentralized AI

When we hear about advancements in artificial intelligence today, it typically comes from a single entity. These organizations control the lifecycle of their own discoveries and technology, molding them so that they fit within the company’s overall goal.

While this may help them, it doesn’t do a whole lot of good at furthering additional advancements for the betterment of society. There’s a shelf life to this and further developments will be stuck in an echo chamber with no room to evolve and, more importantly, learn.

This shouldn’t be AI’s path forward. The future of AI will become a reality when different organizations or entities are able to come together to bring their own individual knowledge to solve a problem. This path forward is through decentralized AI.

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Decentralized AI brings different ideas and data sets based on intelligence, or pseudo intelligence, together to solve a set of complex challenges.

Decentralized AI is a model that allows for the isolation of processing without the downside of aggregate knowledge sharing. By virtue, it enables you to process information independently, among varying computing devices.

By going this route, you’re allowing yourself to achieve a variety of results, analyze the knowledge, and create new solutions to a problem which a centralized AI system would not be able to. When you combine a decentralized computing model, such as blockchain with an intelligence system (AI), you can leverage the best of both worlds for a scale of resources.

Through this, we’ll have a definitive and continual structure in place that explains how things work. There is incredible potential behind decentralized AI across business, sciences, and society. Devices will be able to overcome adversity through real-world challenges, through reasoning, and through trial and error, while having the results recorded.

Over the next ten years, devices that learn through a decentralized AI network would benefit from those that have come before them and all of the other devices currently existing in the network. They will be able to leverage that domain knowledge gathered and convert that data into knowledge.

But we need to understand the steps that are needed to realize this potential – it’s not enough to just be aware that it’s happening. There’s a real need for platforms to contain the computing power required, with storage and (very) high-speed communications. After that, you need to ensure that the appropriate security framework is set up to protect these assets and the data surrounding it.

Ultimately, decentralized AI will provide a hierarchy of achievement that is created through the advancement of knowledge. At the root of this achievement is individualized collaboration. When disparate parts come together to share their findings, new or consistent understandings can be presented to help overcome challenges and, thus, unlocks decentralized AI’s true potential.

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