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In this paper, we examine why an understanding of causality takes machines beyond learning towards having abilities that mean they might reasonably be described as machine scientists.
The Real AI Revolution: Machines That Learn Like Scientists
Whilst the exponential increase in computational power has propelled the usage of ML techniques, such as deep learning, these techniques have no comprehension of causality. Fundamentally, all of the latest ML methods rely on building models from statistical associations present in historical data, without first understanding if they are meaningful.
We must shake off the misconception that ML is synonymous with AI to start the real AI revolution.
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