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The Weight Of Intelligence By Satish Viswanathan

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Forbes
2026/06/07 - 07:12 502 مشاهدة
InnovationAIThe Weight Of Intelligence By Satish ViswanathanByJohn Werner,Contributor.Forbes contributors publish independent expert analyses and insights. I am an MIT Senior Fellow & Lecturer, 5x-founder & VC investing in AIFollow AuthorJun 07, 2026, 03:12am EDT--:-- / --:--This voice experience is generated by AI. Learn more.This voice experience is generated by AI. Learn more.Science and education concept. AI (Artificial Intelligence).gettyThere’s an interesting book on AI about to come out, and if you’re looking for deep insights into how the technologies in play are impacting business, you might want to check it out. Satish Viswanathan has written “The Weight of Intelligence,” a weighty tome with a table of contents that looks like an indexed survey on LLMs in enterprise.Viswanathan has AI bonafides, as former Managing Director at Accenture, and MIT ties, with a history of working with our academic labs in Boston. Now he’s scrutinizing the landscape of AI, and coming up with some applicable ideas about technology in our times.The Pace and Nature of ChangeIn the early pages of the book, Viswanathan goes into some of the ways that neural nets are bringing us a new reality.“Artificial intelligence is no longer advancing in isolated bursts,” Viswanathan writes. “Its capabilities are stacking. What once looked like separate breakthroughs now appears as a reinforcing sequence: better architectures, more data, more compute, broader interfaces, and then new layers of reasoning and action built on top of them. The story is no longer about one breakthrough at a time. It is about a system of breakthroughs that increasingly amplify one another.”This concept, of concentric circles, rocks dropped in a great body of water, is instructive in helping us to see not only the scope of AI, but the shape of it, and how things will be different moving forward.MORE FOR YOUA TimelineViswanathan also presents a timeline of historic change, with the following: deep learning break...
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