Artificial Intelligence: Why now?

For the last 35 years Artificial Intelligence (AI) has been promising much yet not delivering outside of the academic world. So what exactly is AI? There is actually a fair bit of confusion about even the definition of AI, and here I would like to take Gartner’s viewpoint, avoiding marketing terms like ‘cognitive’ in that AI stands for “Amazing Innovation”. Fundamentally, AI gives us solutions that we never thought were possible. So this is not an evolutionary change (solutions that are incrementally better) but a step change in what is even possible. What we can say is that there are some common characteristics of artificially intelligent solutions, in that: They have training, validation and operational phases with the associated data Most solutions require large amounts of data to be genuinely useful There is a ‘feedback loop’, meaning that the models get ‘better’ over time There is a degree of unpredictability, in that the system learns by randomly exploring the solution space Alignment of two planets As far as buzzwords go right now I am not sure if there is a bigger one in technology circles. Again Gartner has AI and Machine Learning (ML) surfing the crest of their hype cycle.…


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