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Razib Khan에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Razib Khan 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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David McKay: AI and the end of the world as we know it

1:06:57
 
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Manage episode 361263682 series 3005967
Razib Khan에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Razib Khan 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

This week on Unsupervised Learning, Razib and his guest, David McKay, of the Standing on the Shoulders of Giants podcast (Razib was an early guest), discuss the rise of artificial intelligence (AI) and the prospects for artificial general intelligence (AGI). This discussion arose after Razib heard McKay’s explainer, Zen and the Art of ChatGPT, a 30-minute layman’s intro to the topic, where he breaks down the technical elements that come together to allow for AI. In this episode, McKay, a Cambridge University-trained computer scientist who has worked at Hotmail and Google, digs deeper into the nature of Large Language Models (LLMs) and how they give rise to probabilistic generative AI like ChatGPT and whether we should be worried.

Razib’s conversation with McKay follows another recent episode on AI. I the earlier podcast, Nikolai Yakovenko: GPT-3 and the rise of the thinking machines, the interviewee, a computer scientist, was relatively sanguine about the world-ending possibilities of AGI. McKay generally takes the same position, highlighting the reality that most computer scientists and AI researchers are less worried about science-fictional apocalyptic scenarios than the general public or AI-skeptics like Eliezer Yudkowsky and Nick Bostrom (the author of Superintelligence: Paths, Dangers, Strategies) are. And yet the reason that AI is so topical is it seems that the development of the technology is proceeding along an exponential path; ChatGPT 4 was released months after ChatGPT 3. McKay and Razib also discuss the release of Bard, Google’s chatbot, and the offering from Microsoft’s Bing, and how they are similar and different from ChatGPT.

While McKay is optimistic about the possibilities of AI as a tool, ultimately, he is in the camp that believes it really isn’t intelligent in the same way as a human. Because it relies on the corpus from the internet, ChatGPT cannot really do math. It lacks true conceptual understanding that would allow it to grasp truth beyond what the internet might tell it. Razib and McKay also talk about the energetic resources that LLMs consume (Microsoft had to reallocate compute resources after the release of Bing’s chatbot), and how that might be a limitation on their scalability.

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185 에피소드

Artwork
icon공유
 
Manage episode 361263682 series 3005967
Razib Khan에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Razib Khan 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

This week on Unsupervised Learning, Razib and his guest, David McKay, of the Standing on the Shoulders of Giants podcast (Razib was an early guest), discuss the rise of artificial intelligence (AI) and the prospects for artificial general intelligence (AGI). This discussion arose after Razib heard McKay’s explainer, Zen and the Art of ChatGPT, a 30-minute layman’s intro to the topic, where he breaks down the technical elements that come together to allow for AI. In this episode, McKay, a Cambridge University-trained computer scientist who has worked at Hotmail and Google, digs deeper into the nature of Large Language Models (LLMs) and how they give rise to probabilistic generative AI like ChatGPT and whether we should be worried.

Razib’s conversation with McKay follows another recent episode on AI. I the earlier podcast, Nikolai Yakovenko: GPT-3 and the rise of the thinking machines, the interviewee, a computer scientist, was relatively sanguine about the world-ending possibilities of AGI. McKay generally takes the same position, highlighting the reality that most computer scientists and AI researchers are less worried about science-fictional apocalyptic scenarios than the general public or AI-skeptics like Eliezer Yudkowsky and Nick Bostrom (the author of Superintelligence: Paths, Dangers, Strategies) are. And yet the reason that AI is so topical is it seems that the development of the technology is proceeding along an exponential path; ChatGPT 4 was released months after ChatGPT 3. McKay and Razib also discuss the release of Bard, Google’s chatbot, and the offering from Microsoft’s Bing, and how they are similar and different from ChatGPT.

While McKay is optimistic about the possibilities of AI as a tool, ultimately, he is in the camp that believes it really isn’t intelligent in the same way as a human. Because it relies on the corpus from the internet, ChatGPT cannot really do math. It lacks true conceptual understanding that would allow it to grasp truth beyond what the internet might tell it. Razib and McKay also talk about the energetic resources that LLMs consume (Microsoft had to reallocate compute resources after the release of Bing’s chatbot), and how that might be a limitation on their scalability.

  continue reading

185 에피소드

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