Lifeboat Foundation

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Continue reading “GPT-5 Rumors and Predictions — It’s about to get real silly” »

In 1971, artist Harold Cohen (1928 – 2016) became a visiting scholar at Stanford’s Artificial Intelligence Laboratory. There, he created a computer program called Aaron to answer the question, “What are the minimum conditions under which a set of marks functions as an image?”

The first iteration of Aaron generated abstract drawings. Later iterations in the 1980s drew rocks, plants, people, and other animals. Cohen’s program was one of the first examples of how AI could be used in creative fields like art.

Continue reading “How an AI drawing program shook the art world in the 1970s” »

This video will cover the philosophy of artificial intelligence, the branch of philosophy that explores what artificial intelligence specifically is, and other philosophical questions surrounding it like; Can a machine act intelligently? Is the human brain essentially a computer? Can a machine be alive like a human is? Can it have a mind and consciousness? Can we build A.I. and align it with our values and ethics? If so, what ethical systems do we choose?

We’re going to be covering all those equations and possible answers to them in what will hopefully be an easy-to-understand, 101-style manner.

Continue reading “The Philosophy of A.I. Easily Explained — What is Artificial Intelligence & Its Implications?” »

Tokyo, Japan – Yu Takagi could not believe his eyes. Sitting alone at his desk on a Saturday afternoon in September, he watched in awe as artificial intelligence decoded a subject’s brain activity to create images of what he was seeing on a screen.

“I still remember when I saw the first [AI-generated] images,” Takagi, a 34-year-old neuroscientist and assistant professor at Osaka University, told Al Jazeera.

“I went into the bathroom and looked at myself in the mirror and saw my face, and thought, ‘Okay, that’s normal. Maybe I’m not going crazy’”.

The Open Letter proposing a pause on giant AI experiments exaggerates hypothetical future harms while ignoring steps that can be taken immediately to mitigate them.

DALL-E in the sidebar.

Large language models are drafting screenplays and writing code and cracking jokes. Image generators, such as Midjourney and DALL-E 2, are winning art prizes and democratizing interior design and producing dangerously convincing fabrications. They feel like magic. Meanwhile, the world’s most advanced robots are still struggling to open different kinds of doors. As in actual, physical doors. Chatbots, in the proper context, can be—and have been—mistaken for actual human beings; the most advanced robots still look more like mechanical arms appended to rolling tables. For now, at least, our dystopian near future looks a lot more like Her than M3GAN.

The counterintuitive notion that it’s harder to build artificial bodies than artificial minds is not a new one. In 1988, the computer scientist Hans Moravec observed that computers already excelled at tasks that humans tended to think of as complicated or difficult (math, chess, IQ tests) but were unable to match “the skills of a one-year-old when it comes to perception and mobility.” Six years later, the cognitive psychologist Steven Pinker offered a pithier formulation: “The main lesson of thirty-five years of AI research,” he wrote, “is that the hard problems are easy and the easy problems are hard.” This lesson is now known as “Moravec’s paradox.”

For 4 hours, I tried to come up reasons for why AI might not kill us all, and Eliezer Yudkowsky explained why I was wrong.

We also discuss his call to halt AI, why LLMs make alignment harder, what it would take to save humanity, his millions of words of sci-fi, and much more.

Continue reading “Eliezer Yudkowsky — Why AI Will Kill Us, Aligning LLMs, Nature of Intelligence, SciFi, & Rationality” »

Actuator: What’s this ‘general purpose’ stuff I keep hearing about?

In a blog post published last week, Meta asks, “Where are the robots?” The answer is simple. They’re here. You just need to know where to look. It’s a frustrating answer. I recognize that. Let’s set aside conversations about cars and driver assistance and just focus on things we all tend to agree are robots. For starters, that Amazon delivery isn’t making it to you without robotic assistance.

A more pertinent question would be: Why aren’t there more robots? And more to the point, why aren’t there more robots in my house right now? It’s a complex question with a lot of nuance — much of it coming down to the current state of hardware limitations around the concept of a “general purpose” robot. Roomba is a robot. There are a lot of Roombas in the world, and that’s largely because Roombas do one thing well (an additional decade of R&D has helped advance things from a state of “pretty good”).

Continue reading “The robots are already here” »