When President Donald Trump began his tariff rollout, the business world predicted that his unprecedented attempt to reshape the economy would lead to a major recession, if he went through with it all. But the markets stabilized and, in recent months, have continued to surge. That has some people worried about an even bigger threat: that overinvestment in artificial intelligence is creating a bubble . Andrew Ross Sorkin, one of today's preëminent financial journalists, is well versed in what's happening; his début book, " Too Big to Fail," was an account of the 2008 financial crash, and this year he released " 1929: Inside the Greatest Crash in Wall Street History--and How It Shattered a Nation ." He tells David Remnick that the concern lies in the immense borrowing to build the infrastructure for a future A.I. economy, without the sufficient revenue, currently, to pay off the loans.

Kant's life was famously dull, but he was less of a hermit than is often supposed.

The Luddites have a bad reputation. These days, the word is most commonly used as an insult--shorthand for somebody who doesn't understand new technology, is skeptical of progress, and wants to remain stuck in the ways of the past. That perception couldn't be more wrong, according to Brian Merchant. In his new book, Blood in the Machine, Merchant argues that understanding the true history of the Luddites is vital for workers today grappling with the rise of artificial intelligence (AI) and automation in the workplace. "At least in my lifetime, the Luddites have never been more relevant," Merchant, 39, tells TIME. "We are confronting a series of cases where technology is being used by tech companies and executives in different industries as a means of trying to drive down wages and worsen conditions so that the entrepreneurial class can make more money."

If Socrates was the wisest person in Ancient Greece, then large language models must be the most foolish systems in the modern world. In his Apology, Plato tells the story of how Socrates's friend Chaerephon goes to visit the oracle at Delphi. Chaerephon asks the oracle whether there is anyone wiser than Socrates. The priestess responds that there isn't: Socrates is the wisest of them all. At first, Socrates seems puzzled.

The tech industry is all-in on AI. Tech giants are pumping massive resources into research and new products. Microsoft and Google are suggesting they'll revamp their entire product lines. AI start-ups have collectively raised tens of billions of dollars in the past year, during a tech slowdown. The buzz has broken Silicon Valley containment, as regular people have had the chance to interact with new and surprising tools.

Technology can be a topic difficult to understand and make predictions on, even for those with a strong technical background and perceived expertise. From Ethernet's creator Robert Metcalfe's 1995 prediction that the internet would "catastrophically collapse" by the next year to Intel's prediction that 3D TV was the future, it is clear that predicting tech trends is a difficult endeavor. No matter how hard predicting the future of technology is, every new technology that creates disruption will go through this cycle. Most recently, we have gone through multiple hype cycles with innovations like blockchain, cryptocurrency, the metaverse, VR, and now, AI. Every single of these technologies has captivated not only the public but also developers and investors, blurring the line between facts and fiction.

In episode 61 of The Gradient Podcast, Daniel Bashir speaks to Ken Liu. Ken is an author of speculative fiction. A winner of the Nebula, Hugo, and World Fantasy awards, he is the author of silkpunk epic fantasy series Dandelion Dynasty and short story collections The Paper Menagerie and Other Stories and The Hidden Girl and Other Stories. Prior to writing full-time, Ken worked as a software engineer, corporate lawyer, and litigation consultant. Have suggestions for future podcast guests (or other feedback)?

If it becomes impossible to distinguish truth from fiction, will readers become more willing to pay for human judgment they can trust? Tools such as OpenAI's ChatGPT threaten to disrupt everything from academia (undetectable cheating) to Google (the AI agent is already more useful than a search engine for some queries). For journalists, it is potentially an existential threat, because OpenAI's technology can generate serviceable content with very little input.

In his book Outliers, Malcom Gladwell unveils the "10,000-Hour Rule" which postulates that the key to achieving world-class mastery of a skill is a matter of 10,000 hours of practice or learning. And while there may be disagreement on the actual number of hours (though I did hear my basketball coaches yell that at me about 10,000 times), let s say that we can accept that it requires roughly 10,000 hours of practice and learning exploring, trying, failing, learning, exploring again, trying again, failing again, learning again for one to master a skill. If that is truly the case, then dang, us humans are doomed. Think about 1,000,000 Tesla cars with its Fully Self Driving (FSD) autonomous driving module practicing and learning every hour that it is driving. In a single hour of the day, Tesla s FSD driving module is learning 100x more than what Malcom Gladwell postulates is necessary to master a task.

An area of focus for chatbots is avoiding and reducing conflict during their human-AI interactions. Whether making a product inquiry or trying to resolve a customer service issue, most of us have interacted with AI or chatbots. Anyone who uses Siri or Alexa is likely to have tales of queries gone wrong or frustrated attempts at seemingly simple requests. But in dismissing these as simplistic machines, what we may not appreciate is that they are often sophisticated tools. Their complex programing is designed not only to solve a wide range of queries but also to emulate more complicated interpersonal skills, such as minimizing conflict, essential in many customer service applications.