Is the future of Artificial Intelligence tied to the future of Blockchain?
Since the beginning of modern times, each industrial revolution was driven by different automation. While factory machines and fossil fuels drove the previous industrial revolutions, the on-going automation revolution is based on data-driven artificial intelligence (AI). Understanding its impact and what will be required to support the AI-driven automation revolution is a fundamental necessity.
So, as we evaluate the impact and the support needed to harness this automation revolution, it seems that at the center of this revolution is the growing need for computing power. There are indicators that raw computing power is on its way to replacing fossil fuels and will be the most valued fuel in the rapidly emerging intelligence age. From where we are to where we want to reach in our intelligence automation journey, further advances in artificial intelligence require enormous amounts of computational power.
Just as computing power is essential to AI, so too is the data that is fed and how the results are used. This is mainly because, ultimately, the input of AI is the data through which complex algorithms provide connections, patterns, and useful insight that provide valuable output for individuals and entities across nations: its government, industries, organizations, and academia (NGIOA).
As seen across nations, many initiatives of blockchain currently provide computing power for the needs of AI. In addition to providing computing power, blockchain technologies also hold the promise of adding structure and accountability to AI algorithms and may help in much-needed areas like security, quality, and integrity of the intelligence AI produces. Now since big data fuels, artificial intelligence and blockchain generates big data, individually and collectively the future of AI is tied to the future of blockchain. That brings us to an important question: How can blockchain technology infrastructure that we have power AI currently for its computing needs of tomorrow when it is struggling to meet its own computing needs of today?
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