The rapid normalization of artificial intelligence is forcing a reckoning with how much of the future is being shaped by hype rather than utility. The writers Charles Duhigg, Cal Newport, and Anna Wiener join Tyler Foggatt for a conversation about artificial intelligence and the promises, myths, and anxieties surrounding it. The discussion was recorded before a live audience at The New Yorker Festival this fall. They explore the gap between Silicon Valley's sweeping claims and what generative A.I. can actually do today; how people are using the technology for work, creativity, and emotional support; and why the tech's most immediate political consequences may be the hardest to grapple with. " The Biggest Threat to the 2026 Economy Is Still Donald Trump," by John Cassidy What Can We Do Instead?," by Jay Caspian Kang When an Ivy League school turned against a student .

If you stayed awake in science class as a kid, the payoff comes when you get a good laugh out of Freya McGhee's jokes. Stop me if you've heard this one before. An aspiring chemist goes to college, realizes she's not good at chemistry, and bombs her dissertation. She takes a class in standup comedy and decides the best way to talk about STEM is to make jokes at its expense. Based in London, the comedian had a strong interest in science as a kid, but after attending the University of Brighton to study chemistry, she realized that she liked learning science more than she liked applying it. Her thesis dissertation--"Synthesis of Iron Nitroxide radical species using radical derivatized ligands and its use as a single-molecule magnet"--flopped.

Obtaining high-quality generations in modern LLMs has largely been framed as a selection problem: identifying a single winning generation from a diverse pool of N samples, the Best-of-N (BoN). Yet, this approach is inherently zero-sum, discarding diverse and potentially useful information from the pool. Instead, we explore a collaborative setup, where all candidates can potentially contribute to the final winning generation. To this end, we propose Fusion-of-N (FusioN): a method that uses a general LLM judge to synthesize the most informative elements of each sample into a single final answer. We compare FusioN to BoN in two settings, (i) test-time scaling, where we sample and aggregate from a single model at test-time (ii) synthetic data generation, where we fuse samples from a pool of diverse teachers to improve a student model. We extensively benchmark both setups across 11 languages, 3 diverse tasks and varying model scales. Across the bench, FusioN consistently outperforms BoN showing versatility and robustness both in test-time scaling and in downstream gains from synthetic data generation. We also perform extensive analysis on FusioN, where it shows surprising strengths and robustness under challenging settings. These results show that we should shift how we think about evaluating and utilizing LLM generations from a monolithic measure of quality, to embracing their polylithic nature. This shift allows us to integrate diverse strengths, unlock latent potential, and achieve improvements that were previously inaccessible through selection alone.

One of the four pillars of good conversation is levity. You needn't be a comedian, you can but have some fun Conversation lies at the heart of our relationships – yet many of us find it surprisingly hard to talk to others. We may feel anxious at the thought of making small talk with strangers and struggle to connect with the people who are closest to us. If that sounds familiar, Alison Wood Brooks hopes to help. She is a professor at Harvard Business School, where she teaches an oversubscribed course called "TALK: How to talk gooder in business and life", and the author of a new book, Talk: The science of conversation and the art of being ourselves.

Legendary comedian and actor Kevin Nealon performed on "Saturday Night Live" for almost a decade, acting in some of the series' most iconic sketches. After 40 years in the business, he recently spoke with Fox News Digital about the current state of stand-up comedy and where he feels the industry is headed. Though the medium has evolved into something bigger than ever before, Nealon described the attention spans of modern comedy audiences as much shorter -- something that those involved in the business of humor have had to cater to. "When I started comedy, it was totally different. And it was a totally different time and generation. And it was not as much short attention span. Like, I look back at some of the sketches on'SNL,' and they're a lot longer than they are now because of the short attention span, and a lot of people don't watch'SNL' at that time. They watch it on YouTube, snippets of it," said the comedian, pointing to social media as something that's gotten hundreds of millions of people accustomed to consuming content in short clips and blurbs.

Comedian Anthony Rodia discusses the comedy industry and talks about the inspiration behind his jokes on'One Nation.' Though he may be covered in tattoos from head to toe -- quite literally -- the only thing more obvious than comedian Shayne Smith's body art lately might be his newfound Catholicism. And the former motorcycle gang member is certainly in good company. Jim Gaffigan, Kevin James, Stephen Colbert, Tom Leopold, Russell Brand, and Rob Schneider are just a few other comedians who share in the same faith -- the latter half of the boisterous bunch having converted to Catholicism in their adulthood. The former half has been just as busy keeping Catholicism alive: Gaffigan recently performed at The Sheen Center for Thought & Culture, at which Cardinal Timothy Dolan is a board member; Kevin James reportedly hosted a Catholic retreat before the pandemic; and Stephen Colbert is known for teaching Sunday school.

In this position paper, we review the eclectic recent history of academic and artistic works involving computational systems for humor generation, and focus specifically on live performance. We make the case that AI comedy should be evaluated in live conditions, in front of audiences sharing either physical or online spaces, and under real-time constraints. We further suggest that improvised comedy is therefore the perfect substrate for deploying and assessing computational humor systems. Using examples of successful AI-infused shows, we demonstrate that live performance raises three sets of challenges for computational humor generation: 1) questions around robotic embodiment, anthropomorphism and competition between humans and machines, 2) questions around comedic timing and the nature of audience interaction, and 3) questions about the human interpretation of seemingly absurd AI-generated humor. We argue that these questions impact the choice of methodologies for evaluating computational humor, as any such method needs to work around the constraints of live audiences and performance spaces. These interrogations also highlight different types of collaborative relationship of human comedians towards AI tools.

Election day is here and so too is the anxiety that has parked itself in the middle of the room. Some people are trying their best to meet the moment -- with mixed results -- while others have simply chosen not to let the race for president and control of Congress dominate their lives. For most all of the voters we spoke to, it's easier said than done. They planned to go for a hike and visit art galleries around downtown L.A. but admitted they were stressed about the election. "We're just sort of out walking around and trying to have a pleasant day and not think about it too much," Mark "I think we'll be glued to our TVs tonight to find out how the rest of our lives are gonna go."

Telling a well-crafted joke that hits just right might seem like it requires a uniquely human touch. But there's bad news for comedians - as researchers from the University of Southern California say that AI is now funnier than most humans. In their study, ChatGPT was able to craft punchlines that were rated funnier than human efforts 70 per cent of the time. And this isn't a laughing matter, as the researchers warn that joke-writing robots could pose a'serious employment threat' to professional comedians. So, can you tell which of these jokes were written by a robot?

Researchers from Google DeepMind asked 20 professional comedians to use popular AI language models to write jokes and comedy performances. The comedians said that the tools were useful in helping them produce an initial "vomit draft" that they could iterate on, and helped them structure their routines. But the AI was not able to produce anything that was original, stimulating, or, crucially, funny. My colleague Rhiannon Williams has the full story. As Tuhin Chakrabarty, a computer science researcher at Columbia University who specializes in AI and creativity, told Rhiannon, humor often relies on being surprising and incongruous.