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1 month ago | 
bookoftheday.nextbigideaclub.com | Michael Kovnat |Arvind Narayanan |Sayash Kapoor
Upgrade to paid to play voiceoverA few days ago, we published a list of our favorite new books on AI, and today I’d like to call attention to one of those books, AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference. Written by two Princeton computer scientists, and , the book brings a clarifying lens to the hype currently surrounding artificial intelligence.
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Dec 13, 2024 | 
technewstube.com | Arvind Narayanan |Sayash Kapoor
Tech News Tube is a real time news feed of the latest technology news headlines.Follow all of the top tech sites in one place, on the web or your mobile device.
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Dec 13, 2024 | 
wired.com | Arvind Narayanan |Sayash Kapoor
OpenAI CEO Sam Altman expects AGI, or artificial general intelligence—AI that outperforms humans at most tasks—around 2027 or 2028. Elon Musk’s prediction is either 2025 or 2026, and he has claimed that he was "losing sleep over the threat of AI danger."But predictions of imminent human-level AI have been made for over 50 years, since the earliest days of AI. Those predictions were wrong—not merely in terms of timing but in a deeper, categorical sense.
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Nov 19, 2024 | 
spectator.org | Arvind Narayanan |Sayash Kapoor |Leonora Cravotta
AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the DifferenceBy Arvind Narayanan & Sayash Kapoor (Princeton University Press, 360 pages, $21.52)Artificial intelligence has become the proverbial elephant in the room. We vacillate between the fear that the mammoth creature will trample us into intellectual oblivion and the gut feeling that a mirage of our own making has duped us.
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Oct 15, 2024 | 
ssir.org | Arvind Narayanan |Sayash Kapoor
AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the DifferenceArvind Narayanan & Sayash Kapoor360 pages, Princeton University Press, 2024Buy the book »Imagine an alternate universe in which people don’t have words for different forms of transportation, only the collective noun “vehicle.” They use that word to refer to cars, buses, bikes, spacecraft, and all other ways of getting from place A to place B. Conversations in this world are confusing.
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Oct 10, 2024 | 
science.org | Dimitri Fabrèges |Stephanie E. Hampton |Rishi Bommasani |Sayash Kapoor
Information & AuthorsInformationPublished In ScienceVolume 386 | Issue 671811 October 2024CopyrightCopyright © 2024 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Article versionsSubmission historyPublished in print: 11 October 2024PermissionsRequest permissions for this article.
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Oct 1, 2024 | 
nonzero.substack.com | Sayash Kapoor |Robert Wright
This episode includes an Overtime segment that’s available to paid subscribers. If you’re not a paid subscriber, we of course encourage you to become one. If you are a paid subscriber, you can access the complete conversation either via the audio and video on this post or by setting up the paid-subscriber podcast feed, which includes all exclusive audio content.
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Sep 18, 2024 | 
open.substack.com | Sayash Kapoor
Last month, Sakana AI released an "AI scientist", which the company called "the first comprehensive system for fully automatic scientific discovery". It was touted as being able to accelerate science without suffering from human limitations. Unfortunately, the "AI Scientist" has many shortcomings. It has no checks for novelty, so generated papers could rehash earlier work.
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Aug 20, 2024 | 
slguardian.org | Sayash Kapoor
AI companies are collectively planning to spend a trillion dollars on hardware and data centers, but there’s been relatively little to show for it so far. This has led to a chorus of concerns that generative AI is a bubble. We won’t offer any predictions on what’s about to happen. But we think we have a solid diagnosis of how things got to this point in the first place. In this post, we explain the mistakes that AI companies have made and how they have been trying to correct them.
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Jul 3, 2024 | 
aisnakeoil.com | Sayash Kapoor
Some of the most exciting applications of large language models involve taking real-world action, such as booking flight tickets or finding and fixing software bugs. AI systems that carry out such tasks are called agents. They use LLMs in combination with other software to use tools such as web search and code terminals.
