On December 29, the WSJ published “Will AI Help or Hurt Workers?,” an article based on a research paper by Aidan Toner-Rodgers, a second year PhD student in MIT’s Economics Department. One of the reasons the WSJ article caught my attention is that it featured a photo of the MIT graduate student in between two of the world’s top economists whose research I’ve closely followed for years: Daron Acemoglu, — who in October was named a co-receipient of the 2024 Nobel Memorial Prize in Economic Science, and David Autor (along with his dog Shelby) — who was a co-chair of a multi-year, MIT-wide Taskforce on the impact of AI on “The Work of the Future.”
Read MoreOver the past few decades, powerful AI systems have matched or surpassed human levels of performance in a number of tasks such as image and speech recognition, skin cancer classification, breast cancer detection, and highly complex games like Go. These AI breakthroughs have been based on increasingly powerful and inexpensive computing technologies, innovative deep learning (DL) algorithms, and huge amounts of data on almost any subject. More recently, the advent of large language models (LLMs) is taking AI to the next level. And, for many technologists like me, LLMs and their associated chatbots have introduced us to the fascinating world of human language and cognition.
Read MoreDecentralization and its impact on organizations as well as business transactions came through loud and clear throughout the conference. Examples of pragmatic applications with disintermediated interactions spanned healthcare, financial services, sports, education, government, non-profit, beauty, industrial applications and many more. A number of presenters emphasized the new era of decentralization with an ideology that empowers communities vs. centralized greedy brokers.
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