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Simile a Tech Policy Podcast
Show notes are at https://stevelitchfield.com/sshow/chat.html
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Download This Show is your weekly guide to the world of media, culture, and technology. From social media to gadgets, streaming services to privacy issues. Each week Marc Fennell and a team of people far smarter than him (his words, not ours) take a fun deep dive into how technology is reshaping our lives.
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Tech Life discovers and explains the ways technology is changing our lives, wherever we are in the world. We meet the people with bright ideas for rethinking the way we work, learn and play, and get hands-on with the products they dream up. We hold tech giants to account for their huge power to affect our lives, and ask who wins, and who loses, in the technology transformation. Tech Life is your guide to a future being made, and remade, at lightning speed in front of our eyes.
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385: AI Snake Oil
Manage episode 441427012 series 2533159
Contenuto fornito da TechFreedom. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da TechFreedom o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
Sayash Kapoor (Princeton) discusses the incoherence of precise p(doom) predictions and the pervasiveness of AI “snake oil.” Check out his and Arvind Narayanan’s new book, AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference.
Topics include:
- What’s a prediction, really?
- p(doom): your guess is as good as anyone’s
- Freakishly chaotic creatures (us, that is)
- AI can’t predict the impact of AI
- Gaming AI with invisible ink
- Life is luck—let’s act like it
- Superintelligence (us, that is)
- The bitter lesson
- AI danger: sweat the small stuff
Links:
AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference
AI Existential Risk Probabilities Are Too Unreliable to Inform Policy
393 episodi
Condividi
Manage episode 441427012 series 2533159
Contenuto fornito da TechFreedom. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da TechFreedom o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
Sayash Kapoor (Princeton) discusses the incoherence of precise p(doom) predictions and the pervasiveness of AI “snake oil.” Check out his and Arvind Narayanan’s new book, AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference.
Topics include:
- What’s a prediction, really?
- p(doom): your guess is as good as anyone’s
- Freakishly chaotic creatures (us, that is)
- AI can’t predict the impact of AI
- Gaming AI with invisible ink
- Life is luck—let’s act like it
- Superintelligence (us, that is)
- The bitter lesson
- AI danger: sweat the small stuff
Links:
AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference
AI Existential Risk Probabilities Are Too Unreliable to Inform Policy
393 episodi
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Simile a Tech Policy Podcast
Africa-focused technology, digital and innovation ecosystem insight and commentary.
…
continue reading
Show notes are at https://stevelitchfield.com/sshow/chat.html
…
continue reading
Download This Show is your weekly guide to the world of media, culture, and technology. From social media to gadgets, streaming services to privacy issues. Each week Marc Fennell and a team of people far smarter than him (his words, not ours) take a fun deep dive into how technology is reshaping our lives.
…
continue reading
We help founders make something people want.
…
continue reading
Monday through Friday, Marketplace demystifies the digital economy in less than 10 minutes. We look past the hype and ask tough questions about an industry that’s constantly changing.
…
continue reading
A podcast featuring panelists of engineers from Netflix, Twitch, & Atlassian talking over drinks about all things software engineering.
…
continue reading
Tech Life discovers and explains the ways technology is changing our lives, wherever we are in the world. We meet the people with bright ideas for rethinking the way we work, learn and play, and get hands-on with the products they dream up. We hold tech giants to account for their huge power to affect our lives, and ask who wins, and who loses, in the technology transformation. Tech Life is your guide to a future being made, and remade, at lightning speed in front of our eyes.
…
continue reading
Android Backstage, a podcast by and for Android developers. Hosted by developers from the Android engineering team, this show covers topics of interest to Android programmers, with in-depth discussions and interviews with engineers on the Android team at Google. Subscribe to Android Developers YouTube → https://goo.gle/AndroidDevs
…
continue reading
The Fragmented Podcast is the leading Android developer podcast started by Kaushik Gopal & Donn Felker. Our goal is to help you become a better Android Developer through conversation & to capture the zeitgeist of Android development. We chat about topics such as Testing, Dependency Injection, Patterns and Practices, useful libraries, and much more. We will also be interviewing some of the top developers out there. Subscribe now and join us on the journey of becoming a better Android Developer.
…
continue reading
Discover a whole new take on Artificial Intelligence with Squirro's educational podcast! Join host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and their incredible impact on society, and y ...
…
continue reading
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Vai offline con l'app Player FM !
Vai offline con l'app Player FM !
