Joe McKendrick is an author, independent researcher and speaker exploring innovation, information technology trends and markets. He’s covered the impact of AI on jobs, including 'Generative AI As A Killer Of Creative Jobs? Hold That Thought.' He served as co-chair of the 2023 AI Summit in New York, as well as the 2021 and 2022 Summits.
There has been quite a bit of press lately about the bursting of the AI hype bubble. “However, there’s actually nothing new about the rise and fall of the AI hype cycle. It’s been going on for decades., senior lecturer of IT at MIT Sloan School of Management."While AI technologies and techniques are at the forefront of today’s technological innovation, it remains a field defined — as it has from the 1950s — by both significant achievements and considerable hype," he told Forbes.
Machine learning, developed in the 1980s, revived AI’s momentum. “AI applications, fueled by increased compute power and availability of digital data, expanded into areas including expert systems and natural language processing,” McDonagh-Smith continued.
Data quality and availability are also currently the major issues that are slowing down or inhibiting AI from living up to its promise. “AI systems are fundamentally reliant on the quality of the data they are trained on,” said McDonagh-Smith. “I see many organizations struggling with data silos, inconsistent data formats, and complex privacy concerns that span geographies and jurisdictions.”
Alan Turing Marvin Minsky John Mccarthy MIT Sloan AI Hype
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