AI heading back to the trough
I like Gartner’s concept of the technology hype cycle. It assumes that expectations of new technologies quickly ramp to an inflated peak, drop into a trough of disillusionment, then gradually ascend a slope of enlightenment until they plateau. Of course, not all technologies complete the cycle or transition through the stages at the same pace. Artificial intelligence (AI) has arguably been in the trough for 60 years. I am thinking of Kubrick’s HAL and Roddenberry’s “computer” that naturally interact with humans. That’s a long trough, and despite popular opinion, the end is nowhere in sight. + Also on Network World: Using artificial intelligence to teach computers to see + There’s so much excitement and specialized research taking place that AI has fragmented into several camps such as heuristic programming for game-playing AI, natural language processing for conversational AI, and machine learning for statistical problems. The hype is building again, and just about every major tech company and countless startups are racing toward another inflated peak and subsequent trough. What changed with AI? The reason expectations are so high is because of breakthroughs in three broad categories: compute, data and algorithms. The compute innovations refer to general cloud services and specific improvements…
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