Has AI (Finally) Reached a Tipping Point?

Irving Wladawsky-Berger, Oct 24, 2016
Commentary by Stephen Downes

Irving Wladawsky-Berger offers a useful overview of contemporary artificial intelligence (AI) from a non-technical perspective referencing Stanford University's One Hundred Year Study on Artificial Intelligence  (AI100, 52 page PDF) including the list of 'hot' areas of current study (quoted, p.9):

  • Large-scale machine learning - algorithms to work with extremely large data sets.
  • Deep learning - has facilitated object recognition in images, video labeling, and activity recognition
  • Reinforcement learning -  experience-driven sequential decision-making
  • Robotics - train a robot to interact with the world around it
  • Computer vision - form of machine perception; automatic image and video captioning.
  • Natural Language Processing - systems that are able to interact with people through dialog; machine translation
  • Collaborative systems - autonomous systems that can work collaboratively with other systems and with humans
  • Crowdsourcing and human computation - make automated calls to human expertise
  • Algorithmic game theory and computational social choice draw - handle potentially misaligned incentives
  • Internet of Things (IoT) -  devices interconnected to collect and share their abundant sensory information
  • Neuromorphic - mimic biological neural networks

The report notes, "Contrary to the more fantastic predictions for AI in the popular press, the Study Panel found no cause for concern that AI is an imminent threat to humankind.  No machines with self-sustaining long-term goals and intent have been developed, nor are they likely to be developed in the near future."

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