In a 2017 Hype Cycle-related article, Gartner, an American Research and Advisory firm, put Deep Learning and Machine Learning at the top of the Hype Cycle.
In a follow-up article about Artificial Intelligence, Gartner mentioned 5 AI myths, including #1 "Buy an AI to solve your problems." The article says, "Enterprises don’t need an “AI.” They need business results in which AI technologies may play a role."
An independent investigation by Stats.com seems to confirm the conclusion. The publication considered the track record of IBM's Watson for Cancer, an AI system deployed in many hospitals around the world, and found that "the supercomputer isn’t living up to the lofty expectations IBM created for it." Furthermore,
Perhaps the most stunning overreach is in the company’s claim that Watson for Oncology, through artificial intelligence, can sift through reams of data to generate new insights and identify, as an IBM sales rep put it, “even new approaches” to cancer care. STAT found that the system doesn’t create new knowledge and is artificially intelligent only in the most rudimentary sense of the term.IBM denies the assertions and says that the technology is on track "to offer guidance about treatment for 12 cancers that account for 80 percent of the world’s cases" by the end of the year.
1) Do you agree with the Gartner's assessment that AI in general, and Deep Learning and Machine Learning in particular are overhyped? Explain your opinion and provide supporting evidence.
2) In your opinion, which technology and business areas will benefit the most from rapid adoption of various forms of AI? Which forms of AI will play the most significant role? Explain briefly.