{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/6717c0ffc054f5390726b1f8/691b2c0007a1a5c8875d5d00?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Can we resist the AI empire, Karen Hao?","thumbnail_width":200,"thumbnail_height":200,"thumbnail_url":"https://open-images.acast.com/shows/6717c0ffc054f5390726b1f8/1763388318096-0fd1fc5f-6626-4f93-8170-6446e59471a6.jpeg?height=200","description":"<p>There is no shortage of critical commentary on the dizzying pace of developments in artificial intelligence. Yet, few do it as astutely as Karen Hao, whose award-winning book, Empire of AI, unveils the inner workings of OpenAI and the tech sector more broadly, shining a light on an industry marked by both grandiose proclamations and notorious secrecy. In this episode of&nbsp;<em>Future Discontinuous</em>, hosts Misha Glenny and Eva Konzett revisit some of Silicon Valley‘s foundational myths and trace the ever-increasing impact of AI on our lives. Together with their guest, they examine how OpenAI has become the multi-billion-dollar empire it is today, discuss the differences between AI doomers and AI boomers, and take stock of the environmental costs of the data centers mushrooming around the globe.</p><p>&nbsp;</p><p><strong>Karen Hao</strong>&nbsp;is an award-winning journalist and author covering artificial intelligence. Having previously worked as an application engineer for a digital startup, a foreign correspondent for&nbsp;<em>The Wall Street Journal&nbsp;</em>covering American and Chinese tech companies<em>,</em>&nbsp;and a senior AI editor at&nbsp;<em>MIT Technology Review</em>, Hao regularly writes about tech and AI for high-profile publications like&nbsp;<em>The Atlantic</em>. She also leads the AI Spotlight Series, a program that trains journalists to cover AI. Her 2025 book,&nbsp;<em>Empire of AI</em>,<em>&nbsp;</em>was an instant&nbsp;<em>New York Times</em>&nbsp;bestseller.</p>","author_name":"FALTER and IWM"}