DISCLAIMER: This video is not medical, financial, or legal advice. This is just my personal story and research findings. Always consult a licensed professional.
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.
In a paper titled “How to Make a Drawing,” which Cohen submitted to the National Bureau of Standards in 1982, he predicted that advancements in AI would result in a “cultural shock-wave of unprecedented proportions.”
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.
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0:00 Introduction. 0:45 What is Artificial Intelligence? 1:13 Rene Descartes. 2:11 Alan Turing & the ‘Turing Test’ 3:42 A.I.M.A. & A.I. 4:45 Intelligent Agents. 5:40 Newell’s Definition. 6:26 Weak A.I. vs Strong A.I. 7:31 Narrow A.I. vs General A.I. vs Super Intelligence. 10:00 Computationalism. 10:44 Approaches to A.I. 13:32 Can a Machine Have Consciousness? 14:23 The ‘Chinese Room’ 16:30 Critical Responses. 17:18 The ‘Hard Problem of Consciousness’ 18:47 Philosophical Zombies. 21:20 New Questions in the Philosophy of A.I. 21:34 Singularitarianism. 24:40 A.I. Alignment. 26:45 The Orthogonality Thesis. 27:36 The Ethics of A.I. 30:56 Conclusion.
Descartes, 1,637, R., in Haldane, E. and Ross, G.R.T., translators, 1911, The Philosophical Works of Descartes, Volume 1, Cambridge, UK: Cambridge University Press.
Russell, S. & Norvig, P., 2009, Artificial Intelligence: A Modern Approach 3rd edition, Saddle River, NJ: Prentice Hall.
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.
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.
If you want to get to the crux of the conversation, fast forward to 2:35:00 through 3:43:54. Here we go through and debate the main reasons I still think doom is unlikely.
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”).
It’s not so much that the premise of the question is flawed — it’s more a question of reframing it slightly. “Why aren’t there more robots?” is a perfectly valid question for a nonroboticist to ask. As a longtime hardware person, I usually start my answer there. I’ve had enough conversations over the past decade that I feel fairly confident I could monopolize the entire conversation discussing the many potential points of failure with a robot gripper.
Facebook Gaming, a division of Meta, has announced that you can now play games during video calls on Messenger. At launch, there are 14 free-to-play game available in Messenger video calls on iOS, Android and the web. The games include popular titles like Words With Friends, Card Wars, Exploding Kittens and Mini Gold FRVR.
To access the games, you need to start a video call on Messenger and tap the group mode button in the center, then tap on the “Play” icon. From there, you can browse through the games library. The company notes that there must be two or more people in your call to play games.
“Facebook Gaming is excited to announce that you can now play your favorite games during video calls on Messenger,” the company wrote in a blog post. “This new, shared experience in Messenger makes it easy to play games with friends and family while in a video call, allowing you to deepen connections with friends and family by engaging in conversations and gameplay at the same time.”
