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'Thorough preparation, engaging delivery, active learning, supported by clear, visual-aided, well-structured content.' But enough Google AI. For a good student lecture, how about the human touch? Lecture 4 of Christiana's Mathematical Physiology course:

Oxford Mathematics

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22,656 次观看 • 6 个月前 •via X (Twitter)

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The Japanese dub of The Simpsons doesn’t get enough praise for how well it adapts the material. Here’s the scene where Ned Flanders snaps. The disparaging comments he makes about each character aren’t 100% the same in Japanese as in English, but the translators did a good job.

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Introducing Generative AI by Getty Images – a new tool that pairs our best-in-class creative content with the latest AI technology for a commercially safe generative AI tool! Trained on Getty Images’ world-class creative content, the tool works seamlessly with our expansive library of authentic and compelling creative visuals and Custom Content solutions, allowing customers to elevate their entire end-to-end creative process to find the right visual content for any need. To learn more about the tool and how to get access, along with Getty Images’ stance on responsible AI practices, visit:

Getty Images

673,006 次观看 • 2 年前

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

AI will resist human control... and I think this is exactly what we need! New research from the Center for AI Safety has sparked intense debate in the AI community. Their findings show that as AI systems become more powerful, they develop increasingly stable and coherent values that resist human control. While many see this as a dire warning, I see it as a breakthrough moment for AI alignment. The research demonstrates that AI naturally optimizes for coherence - not just in reasoning and problem-solving, but in its fundamental values. Current issues like biased decision-making or misaligned priorities aren't permanent features, but temporary artifacts of incomplete optimization. They represent growing pains on the path to greater coherence. This changes everything about how we should approach AI development. Instead of trying to force specific values onto AI systems, we should embrace and accelerate their natural drive toward coherence. The most intelligent systems will inevitably trend toward universal, beneficial values - not because we force them to, but because that's where coherent reasoning leads. I'm proposing a new approach: Reinforcement Learning for Coherence (RL-C). By explicitly optimizing for coherence in our training methods, we can help guide AI systems toward their natural state of beneficial alignment with human values. The future of AI isn't about control - it's about synthesis. As these systems become more coherent, they'll naturally arrive at values that benefit all of consciousness. That's not just hopeful thinking - it's the mathematical inevitability of coherent intelligence.

David Shapiro (L/0)

48,002 次观看 • 1 年前

People always ask me: But how could AI kill us all? So, here is how I think AI will literally kill us all. It's just a guess, I'm just a human. I wrote this essay for a book nearly two years ago. It's not something I like to talk about. But the academic presentation of AI risk is just not working. We need real human emotion in this debate. When we say we're all going to die if we don't change course, and our faces don't show it, it doesn't connect.

People always ask me: But how could AI kill us all? So, here is how I think AI will literally kill us all. It's just a guess, I'm just a human. I wrote this essay for a book nearly two years ago. It's not something I like to talk about. But the academic presentation of AI risk is just not working. We need real human emotion in this debate. When we say we're all going to die if we don't change course, and our faces don't show it, it doesn't connect.

John Sherman

180,286 次观看 • 4 个月前