The podcast discusses the reality of quantum computing, challenges faced in the tech industry, and the importance of open source and code refactoring. Topics include AI acceleration, independence from corporate control, and valuable advice for first-time open source contributors.
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Quick takeaways
There is a bear case for near-term quantum computing applications, indicating skepticism towards optimistic timelines proposed by quantum computing companies.
In the realm of artificial intelligence, technologists are adopting a cautious approach to their own power, amidst a moral panic and tech backlash, leading to introspection about societal impacts.
Deep dives
Quantum Computing's Bear Case
The podcast episode discusses the bear case for near-term quantum computing applications, highlighting the growing pushback against optimistic timelines proposed by quantum computing companies. While some have hyped the impact of quantum computing on real-world problems in a few years, the article suggests that such expectations may be unrealistic. The episode also mentions the ongoing debates around the validity, timeliness, and long-term effects of quantum computing, comparing it to other computing endeavors with smart people on either side of the argument.
The Power and Caution of AI
The podcast episode delves into the topic of artificial intelligence (AI) and the growing movement of technologists being proactively cautious about their own power before any demonstrable harm has been done. The host explores the moral panic arising within the industry, which contrasts with historical technological revolutions. The episode also mentions a writer named Nadia and references a quote from her writing, which highlights the tech backlash experienced in the 2010s. Overall, the episode portrays AI as a domain where technologists engage in introspection and raises questions about the societal impact of technological advancements.
Ship It is back! IEEE Spectrum writes about quantum computing’s reality check, Maxim Dounin announces freenginx, Nadia Asparouhova goes deep on AI & the “effective accelerationism” movement, Angie Byron helps first time open source contributors avoid common pitfalls & Miroslav Nikolov writes up his advice for high-risk refactoring.
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