The Intelligence Revolution

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LLMs can outperform neuroscientists at predicting research outcomes

How Henry Kissinger Saw the Power and Potential of AI

Assuming that the primary agent exerts their agency solely through the human who is working with an AI, the spectrum of human-AI relationships look very much the same as it did within the two-actor model. But what is different is that the tasks the human is being asked to carry out are no longer self-generated. Rather, they are received from another agent within the system.

In other words, the human becomes a secondary agent within the model.

This is all well and good — until one asks what happens if the primary agent switches to working directly with the AI.  Read more

Check out this bold claim in Time Magazine.

See Dr. Jason Gulya's response (LinkedIn).

A two-hour interview is enough to accurately capture your values and preferences, according to new research from Stanford and Google DeepMind.

NATIONAL BESTSELLER • “The conscience of the AI revolution” (Fortune) explains how we’ve arrived at an era of AI harms and oppression, and what we can do to avoid its pitfalls.

“AI is not coming, it’s here. If we answer the beautiful call inside these pages, we can decide who we are going to be and how we’re going to use technology in service of what it means to be fully human.”—Brené Brown, #1 New York Times bestselling author of Dare to Lead

A LOS ANGELES TIMES BEST BOOK OF THE YEAR • Shortlisted for the Inc. Non-Obvious Book Award

In this report, we argue that there is a realistic possibility that some AI systems will be conscious and/or robustly agentic in the near future. That means that the prospect of AI welfare and moral patienthood, i.e. of AI systems with their own interests and moral significance, is no longer an issue only for sci-fi or the distant future. It is an issue for the near future, and AI companies and other actors have a responsibility to start taking it seriously.!

This episode was recorded in front of a live audience at the ‘Performance Journey Goes Dutch’ conference in Ermelo, The Netherlands, organised by Xpertise Learning. Donald and John explore a group of theorists who are giving us a new picture of how we think and learn that is distinctively different from what came before. They’re the Connectionists, and they see the brain as flatter than was previously thought, constantly trying to predict what will happen next, and to improvise a response. But what are the implications for learning of this New Psychology?!

• 00:00 - Intro
• 00:58 - Introducing The Connectionists
• 11:15 - Daniel Dennett (1942 - 2024)
• 19:15 - Geoffrey Hinton (1947–)
• 24:38 - Nick Chater (1965–)
• 35:17 - Karl Friston (1959–)
• 39:19 - Joshua Brett Tenenbaum (1972–)
• 43:49 - Andy Clark (1957–)
• 46:54 - Summing Up

From The Verge:  Ge Wang doesn’t use computers to make music the way most people use computers make music. He uses computers to make... computer music. Wang works at Stanford, as an associate professor in the Center for Computer Research in Music and Acoustics. He also conducts the school’s famed Laptop Orchestra, was a co-founder of the music app maker Smule, and created a programming language called Chuck that turns code into sound. He understands how computers, music, and humans interact more deeply than most. He also has some ideas about where it’s all headed.

On this episode of The Vergecast, the third and last in our mini-series about the future of music, we chat with Wang about what’s next for computer music. He tells us about teaching his students to play with technology rather than trying to master it, and how tool makers should be approaching their work in a time of AI.

More from The Verge

Ge Wang @ HCAI

I think society and our educational institutions haven’t given engineers and designers the tools to deal with the social, cultural, and historical contexts in which technology is being deployed. When designers and engineers create AI and other technology tools, they are literally designing today’s world. They basically have godlike power – the power to shape the way other people work, play, live, and relate to other people. And with that power comes responsibility. I think most of us do not know how to begin to think about how to create AI that, with humility, shapes the world for the benefit of humans in their messy human, social context.

It’s simplistic to say AI is dangerous. The potential for profound peril is ever present. The technology is developing so rapidly that we don’t have time to read the new AI papers that come out or even the headlines regarding what happened today in AI. And given that speed, how can we possibly hope that AI development is being done with our well-being and our community’s well-being – never mind society’s well-being – at heart? Which to me means AI should be a source of fundamental concern for us all. Read More