{"id":92957,"date":"2024-09-23T10:53:52","date_gmt":"2024-09-23T14:53:52","guid":{"rendered":"https:\/\/danielschristian.com\/learning-ecosystems\/?p=92957"},"modified":"2024-09-23T10:58:19","modified_gmt":"2024-09-23T14:58:19","slug":"ai-humans-and-work-10-thoughts-tobaccowala-other-items-re-ai-in-general","status":"publish","type":"post","link":"http:\/\/danielschristian.com\/learning-ecosystems\/2024\/09\/23\/ai-humans-and-work-10-thoughts-tobaccowala-other-items-re-ai-in-general\/","title":{"rendered":"&#8220;AI, Humans and Work: 10 Thoughts.&#8221; [Tobaccowala] + other items re: AI in general"},"content":{"rendered":"<p><iframe loading=\"lazy\" title=\"YouTube video player\" src=\"https:\/\/www.youtube.com\/embed\/yMGGpMyW_vw?si=4V9YOWrh5fYhPDGs\" width=\"560\" height=\"315\" frameborder=\"0\" allowfullscreen=\"allowfullscreen\"><\/iframe><\/p>\n<p style=\"padding-left: 40px;\">AI researcher Jim Fan has had a charmed career. He was OpenAI\u2019s first intern before he did his PhD at Stanford with \u201cgodmother of AI,\u201d Fei-Fei Li. He graduated into a research scientist position at Nvidia and now leads its Embodied AI \u201cGEAR\u201d group. The lab\u2019s current work spans foundation models for humanoid robots to agents for virtual worlds. Jim describes a three-pronged data strategy for robotics, combining internet-scale data, simulation data and real world robot data. He believes that in the next few years it will be possible to create a \u201cfoundation agent\u201d that can generalize across skills, embodiments and realities\u2014both physical and virtual. He also supports Jensen Huang\u2019s idea that \u201cEverything that moves will eventually be autonomous.\u201d<\/p>\n<hr \/>\n<p><a href=\"https:\/\/runwayml.com\/news\/runway-partners-with-lionsgate\" target=\"_blank\" rel=\"noopener\"><strong>Runway Partners with Lionsgate<\/strong><\/a> &#8212; from runwayml.com via The Rundown AI<br \/>\n<em>Runway and Lionsgate are partnering to explore the use of AI in film production.<\/em><\/p>\n<p style=\"padding-left: 40px;\">Lionsgate and Runway have entered into a first-of-its-kind partnership centered around the creation and training of a new AI model, customized on Lionsgate\u2019s proprietary catalog. Fundamentally designed to help Lionsgate Studios, its filmmakers, directors and other creative talent augment their work, the model generates cinematic video that can be further iterated using Runway\u2019s suite of controllable tools.<\/p>\n<p><span style=\"color: #800000;\"><strong>Per The Rundown:<\/strong> <\/span>Lionsgate, the film company behind The Hunger Games, John Wick, and Saw, teamed up with AI video generation company Runway to create a custom AI model trained on Lionsgate\u2019s film catalogue.<\/p>\n<p><strong>The details:<\/strong><\/p>\n<ul>\n<li>The partnership will develop an AI model specifically trained on Lionsgate\u2019s proprietary content library, designed to generate cinematic video that filmmakers can further manipulate using Runway\u2019s tools.<\/li>\n<li>Lionsgate sees AI as a tool to augment and enhance its current operations, streamlining both pre-production and post-production processes.<\/li>\n<li>Runway is considering ways to offer similar custom-trained models as templates for individual creators, expanding access to AI-powered filmmaking tools beyond major studios.<\/li>\n<\/ul>\n<p><strong>Why it matters:<\/strong> As many writers, actors, and filmmakers strike against ChatGPT, Lionsgate is diving head-first into the world of generative AI through its partnership with Runway. This is one of the first major collabs between an AI startup and a major Hollywood company \u2014 and its success or failure could set precedent for years to come.<\/p>\n<hr \/>\n<p><a href=\"https:\/\/www.washingtonpost.com\/technology\/2024\/09\/18\/energy-ai-use-electricity-water-data-centers\/\" target=\"_blank\" rel=\"noopener\"><strong>A bottle of water per email: the hidden environmental costs of using AI chatbots<\/strong> <\/a>&#8212; from washingtonpost.com by Pranshu Verma and Shelly Tan\u00a0<span style=\"color: #800000;\"><em>(behind paywall)<\/em><\/span><br \/>\n<em>AI bots generate a lot of heat, and keeping their computer servers running exacts a toll.<\/em><\/p>\n<p style=\"padding-left: 40px;\">Each prompt on ChatGPT flows through a server that runs thousands of calculations to determine the best words to use in a response.<\/p>\n<p style=\"padding-left: 40px;\">In completing those calculations, these servers, typically\u00a0housed in data centers, generate heat. Often, water systems are used to cool the equipment and keep it functioning. Water transports the heat generated in the data centers into cooling towers to help it escape the building, similar to how the human body uses sweat to keep cool, according to Shaolei Ren, an associate professor at UC Riverside.<\/p>\n<p style=\"padding-left: 40px;\">Where electricity is cheaper, or water comparatively scarce, electricity is often used to cool these warehouses with large units resembling air-conditioners, he said. That means the amount of water and<b>\u00a0<\/b>electricity an individual query requires can depend on a data center\u2019s location and vary widely.<\/p>\n<hr \/>\n<p><a href=\"https:\/\/rishad.substack.com\/p\/ai-humans-and-work-10-thoughts\" target=\"_blank\" rel=\"noopener\"><strong>AI, Humans and Work: 10 Thoughts.<\/strong> <\/a>&#8212; from rishad.substack.com by Rishad Tobaccowala<br \/>\n<em>The Future Does Not Fit in the Containers of the Past. Edition 215.<\/em><\/p>\n<p><strong>10 thoughts about AI, Humans and Work in 10 minutes:<\/strong><\/p>\n<ol>\n<li>AI is still Under-hyped.<\/li>\n<li>AI itself will be like electricity and is unlikely to be a differentiator for most firms.<\/li>\n<li>AI is not alive but can be thought of as a new species.<\/li>\n<li>Knowledge will be free and every knowledge workers job will change in 2025.<\/li>\n<li>The key about AI is not to ask what AI will do to us but what AI can do for us.<\/li>\n<li>Plus 5 other thoughts<\/li>\n<\/ol>\n<hr \/>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI researcher Jim Fan has had a charmed career. He was OpenAI\u2019s first intern before he did his PhD at Stanford with \u201cgodmother of AI,\u201d Fei-Fei Li. He graduated into a research scientist position at Nvidia and now leads its Embodied AI \u201cGEAR\u201d group. The lab\u2019s current work spans foundation models for humanoid robots to [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[356,86,271,210,82,533,37,35,178,408,869,309,437,480,195,321,367,299],"tags":[],"class_list":["post-92957","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence-agents-llms-and-related","category-change","category-creativity","category-emerging-technologies","category-engineering","category-experimentation","category-future","category-game-changing-environment","category-generational-differences","category-mediafilm","category-open-ai","category-platforms","category-robotics","category-society","category-tools","category-united-states","category-vendors","category-workplace"],"_links":{"self":[{"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/92957","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/comments?post=92957"}],"version-history":[{"count":11,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/92957\/revisions"}],"predecessor-version":[{"id":92985,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/92957\/revisions\/92985"}],"wp:attachment":[{"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/media?parent=92957"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/categories?post=92957"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/tags?post=92957"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}