Artificial intelligence (AI) research is going through a new peak in interest and investment. Intense activity in generative AI and neural network architecture development is pushing more organizations to experiment with novel approaches to automation. As part of this trend, machine learning (ML) models are being embedded into mainstream business and desktop applications, driving an unexpected demand for additional data center capacity.
However, while technological progress continues to move forward, a broad consensus on AI — what it is, what it is not, and what it can and cannot do — is still out of reach. This lack of agreement has only become more widespread since generative AI burst onto the scene, creating diverging, even polarizing opinions.
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