Podcast appearances and mentions of Steven Johnson

Steven Johnson, retired Iowa State Extension farm management specialist; Ken Ericksen, Polaris Analytics and Consulting, trends in ag trade and barge transport

The entirety of DJ & PK for May 28, 2025: HOUR ONE Recapping the night in sports Steve Cleveland, Former BYU Basketball Coach Steven Johnson, Fort Worth Star-Telegram HOUR TWO What is Trending Hot Takes or Toast Golf and NBA Playoffs collide HOUR THREE What could the Utah Jazz get for Lauri Markkanen? Matt Murschel, Orlando Sentinel Big 12 race should be wild this fall HOUR FOUR Andy Bailey, Bleacher Report Slacker Radio Headlines Feedback of the Day

Hour one of DJ & PK for May 28, 2025: Recapping the night in sports Steve Cleveland, Former BYU Basketball Coach Steven Johnson, Fort Worth Star-Telegram

The Zoar Methodist Episcopal Church in Odessa recently received grant funding for restoration work on the historic building.In this edition of History Matters, Delaware Public Media's Joe Irizarry is joined by The Friends of Zoar's Steven Johnson to learn more about the Zoar Church's restoration efforts and plans to preserve its history.

The Verge's Will Poor recently came home from vacation and discovered he had an insect problem. More specifically, his Sonos speaker had an insect problem. Will brings us the story of what really happened there, and what he discovered about how the animal kingdom — and the electronics world — works. After that, The Verge's Andru Marino tells us about his research on all things AI podcasts. He tells us why people are so hooked on NotebookLM's Audio Overviews, where these generated shows fall short, and what all us human podcasters could learn from the bots. Finally, The Verge's Jennifer Pattison Tuohy helps us answer a question on the Vergecast Hotline (call 866-VERGE11 or email vergecast@theverge.com!) all about smart lights. Which get complicated faster than you think. Further reading: Oh no, Google is turning everything into a podcast Google's NotebookLM AI podcasts add ‘interactive' mode for some Q-and-A Steven Johnson on Google, NotebookLM, and AI research A guide to getting started with smart lighting: When to use smart switches and smart bulbs Inovelli smart switches Learn more about your ad choices. Visit podcastchoices.com/adchoices

On this edition of Parallax Views, you will hear an incredible story that, on its surface, you may mistake as being just about professional wrestling: the life and career of "The Golden Greek" Jim Londos. He was the biggest star of not only pro wrestling in the 1920s and 1930s, but arguably of sports itself. His popularity eclipsed that of the profession itself. He sold out stadiums of tens of thousands. Contrary to popular misconceptions, pro wrestling was not simply the domain of smoky rooms before the era of Hulk Hogan. Jim Londos is proof of that. In fact, it may be fair to say that Jim Londos was Hulk Hogan before Hulk Hogan. And just to drive that point home, one only need look at his match against Kola Kwariani on October 22nd, 1933 in Athens, Greece at the Panathenaic Stadium. The attendance for that event? It's said to be between 65,000 and 100,000. Simply put, Londos was a phenomenon. But, his story is much more than that of a pro wrestler. Londos is the story of an immigrant to the United States overcoming all odds. He is the story of a man who gave hope to the masses in the trying times of The Great Depression. A man who became a symbol of being able to overcome the greatest adversities. He was smaller in stature than many of his wrestling contemporaries. The classic underdog. And the fans loved him for it. He was their hero. He was "The Golden Greek" of professional wrestling. Joining J.G. on this edition of the show is journalist Steven Johnson. Although Johnson has done a lot of journalism related to pro wrestling and its storied history, he's also been a U.S. Senate aide and newspaper editor. Moreover, he has master's and Ph.D. from the University of Virginia. Over more than a decade he worked on a book to finally tell the story of Jim Londos. That book, recently released, is entitled Jim Londos: The Golden Greek of Professional Wrestling. Part of MacFarland's Studies in Strength of Physical Culture series, this book uncovers the life and times of an athletic performer who has been unfairly forgotten due to having wrestled in the pre-television era of the professional wrestling. In this conversation Steven I will discuss how he came around to the story of Jim Londos, the ways in which Londos story differs greatly from the more tragic rise & fall of early television-era wrestling Gorgeous George, the trials and tribulations of Jim Londos as a young immigrant in the United States of America in the early 20th century, the ways in which Londos is comparable to the mythical figure of Jason in the story of Jason and the Argonauts, how the legacy of Londos is carried on today by wrestlers like Bryan Danielson (aka Daniel Bryan), WWE superstar John Bradshaw Layfield's (JBL) foreword to the book, the wrestling double-crosses of the early 20th century that long predated the WWE's infamous "Montreal Screwjob", the colorful wrestling promoters of the Londos era (such as Toots Mondt and the Gold Dust Trio, Jack Pfefer, and Jack Curley), the legendary years long feud between Jim Londos and Ed "The Strangler" Lewis, Londos ability to make a crowd not only "believe" but "care" about his journey as a wrestler, and much, much more.

We dive into Steven Johnson's book 'Wonderland: How Play Made the Modern World,' which shows how play has been a catalyst for invention, the interconnectedness of ideas, and the impact of play on technology and culture. How can we create spaces for play that fosters change? Takeaways Play is essential for human flourishing and creativity. Steven Johnson's 'Wonderland' explores the role of play in invention. Fashion and consumer culture emerged from playful pursuits. Play leads to unforeseen discoveries in various fields. The spice trade significantly influenced global commerce and exploration. Exploration has both positive and negative consequences. Ideas and fields of study are interconnected in surprising ways. We are products of generations of creative thought. Cultivating play can lead to positive change in the world. Play should be valued for its own sake, not just for its utility. Chapters 00:00 The Role of Play in Human Flourishing 05:11 Exploring 'Wonderland' by Steven Johnson 09:15 Play as a Catalyst for Invention 15:24 The Intersection of Play and Commerce 20:51 Exploration and Its Shadow Side 28:30 The Role of Public Spaces in Idea Formation 31:19 Interconnectedness of Ideas and Knowledge 34:38 The Illusion of Self-Made Success 40:52 The Power of Play in Innovation 44:50 Cultivating Virtue Through Play 49:36 Creating Space for Change Through Play CALL TO ACTION: - Subscribe to our newsletter (https://buttondown.email/BoardGameFaith) - Support us on Patreon (https://www.patreon.com/boardgamefaith/) - Interact with us on Instagram (https://www.instagram.com/boardgamefaith/) - Discord us Discord (https://discord.gg/MRqDXEJZ)

As VP of Google Labs, Josh Woodward leads teams exploring the frontiers of AI applications. He shares insights on their rapid development process, why today's written prompts will become outdated and how AI is transforming everything from video generation to computer control. He reveals that 25% of Google's code is now written by AI and explains why coding could see major leaps forward this year. He emphasizes the importance of taste, design and human values in building AI tools that will shape how future generations work and create. Mentioned in this episode: Notebook LM: Personal research product based on Gemini 2 (previously discussed on Training Data.) Veo 2: Google DeepMind's new video generation model. Paul Graham on X replying to Aaron Levie's post that “One approach to take in building in AI is to do something that's too expensive to be reasonably practical right now, and just bet that the costs will drop by 10X or 100X over time. The cost curve is on your side.” Where Good Ideas Come From: Book on the history of innovation by Steven Johnson. Project Mariner: Google DeepMind's research prototype exploring human-agent interaction starting with browser use. Replit Agent: Josh's favorite new AI app The Lego Story: Book on the history of Lego. Hosted by: Ravi Gupta and Sonya Huang, Sequoia Capital 

Hello, wrestling fans! It's time for Episode #158 of Shut Up and Wrestle, with Brian R. Solomon! This week, author and journalist Steven Johnson returns to the show to discuss his new book, Jim Londos: The Golden Greek of Professional Wrestling! Londos was in many ways the greatest star that pro wrestling ever produced, and … Continue reading Episode 158: Steven Johnson Talks Jim Londos → The post Episode 158: Steven Johnson Talks Jim Londos appeared first on Shut Up And Wrestle with Brian Solomon.

Steven Johnson, Kansas Treasurer | 1-31-25See omnystudio.com/listener for privacy information.

Send us a textShantanu Sinha, VP & GM of Google for Education, leads the development of tools like Google Classroom and Read Along, serving over 150 million educators and students globally. Previously, as founding President and COO of Khan Academy, he championed free, personalized learning on a global scale. Shantanu combines deep expertise in computer science, math, and cognitive sciences from MIT with strategic consulting experience from McKinsey.Jennie Magiera, Global Head of Education Impact at Google, is a bestselling author, TEDx speaker, and advocate for equity in education. At Google, she focuses on elevating marginalized voices and creating empowering tools for teachers and learners. A White House Champion for Change and ISTE Impact Award Winner, Jennie brings extensive experience as a teacher, district leader, and digital learning innovator.Steven Johnson, Editorial Director of NotebookLM and Google Labs, is a bestselling author of 14 books on innovation and technology, including Where Good Ideas Come From. An Emmy-winning television host and tech entrepreneur, Steven shapes tools that redefine learning and research while advocating for the power of collaboration in driving transformative ideas.

Chris Benoit known as the Canadian Crippler or the Rabid Wolverine was a WWE star in the 22nd year of a storied career. He was known to be a wrestler's wrestler- one of the most technically proficient athletes among the corps of actors and performers. Chris Jericho once said Chris Benoit was the “most intense and believable performer I've ever been in the ring with. He could see things that were going to happen before they happened.” Chris won many heavyweight and tag team championships, and he'd made a lot of money doing it. He was doing exactly what he'd wanted to do for his entire life- since he was 3-years-old. His friends and colleagues all knew him to be a respectful, reserved and polite family man. So, it came as quite a shock to everybody when he and his family were found dead under suspicious circumstances, in their sprawling Fayetteville, Georgia home. This is the story of a woman, her child, and to some extent, a man, who were failed by the very institution that should have protected them.The question on everyone's mind…could the tragedy have been prevented?Listen to both parts on Patreon now.Today's snacks: Levain Bakery Dark Chocolate Chocolate Chip CookiesSources:https://concussioninc.net/?p=497 Benoit 911 callsBenoit: Wrestling with the Horror that Destroyed a Family and Crippled a Sport - collected essays by Steven Johnson, Heath McCoy, Irvin Muchnick and Creg OliverRingmaster: Vince McMahon and the Unmaking of America, by Abraham Josephine RiesmanChris and Nancy: The True Story of the Benoit Murder-Suicide & Pro Wrestling's Cocktail of Death, by Irvin Muchnickhttps://www.autopsyfiles.org/reports/Celebs/benoit,%20chris_report.pdf Chris' autopsy reporthttps://www.greenwichtime.com/news/article/Sunday-subscriber-advantage-WWE-steroid-385857.php#page-1https://www.biography.com/athletes/andre-the-gianthttps://youtu.be/0b90OweR0n4?si=d8ZIkwEA_FNkz0wWhttps://www.youtube.com/watch?v=V_9hGvpkvws&ab_channel=Scott%27sWrestlingCollectionhttps://ezproxy.bu.edu/login?qurl=https%3A%2F%2Fwww.proquest.com%2Fwire-feeds%2Frepeated-concussions-led-wrestler-chris-benoits%2Fdocview%2F360118700%2Fse-2%3Faccountid%3D9676 (STUFFCO, JERED. "Repeated Concussions Led to Wrestler Chris Benoit's Suicide: CBC Documentary." The Canadian Press, Feb 05 2008, ProQuest. Web. 1 Nov. 2024)https://www.youtube.com/watch?v=BgOdvHHXlr4&ab_channel=MrAdrenaline1982https://archive.ph/20120629093200/http://slam.canoe.ca/SlamWrestlingArchive2000/jan14_ins.htmlhttps://www.fightful.com/wrestling/jay-white-details-life-inside-njpw-dojohttps://www.youtube.com/watch?v=HBXZIr6DP-c&t=47shttps://abcnews.go.com/GMA/story?id=3320736https://www.fightful.com/wrestling/phil-carroll-astin-doctor-chris-benoit-passes-away-age-67https://docs.google.com/document/d/1Nq6UZR8YjNHQb56lZ6kuXqlnxJAoSPclc5hh-qfKa48/edit?tab=t.0

Ben Criddle talks BYU sports every weekday from 2 to 6 pm.Today's Co-Hosts: Ben Criddle (@criddlebenjamin)Subscribe to the Cougar Sports with Ben Criddle podcast:Apple Podcasts: https://itunes.apple.com/us/podcast/cougar-sports-with-ben-criddle/id99676 Stitcherhttps://www.stitcher.com/podcast/espn960sports/cougar-bytes

This week John Poz's TMPT welcomes into the show for the feature episode, author, historian, and award winning journalist, Steven Johnson. The wrestling historian is on to discuss his new book, "Jim Londos: The Golden Greek of Professional Wrestling." Host John Poz and Steven will talk about Jim's breaking into the business, NWA, Ed Strangler Lewis, Lou Thesz, Madison Square Garden, Hulk Hogan, Mount Rushmore, and so much more!Jim Londos: The Golden Greek of Professional Wrestling (Studies in Strength and Physical Culture) - https://www.amazon.com/Jim-Londos-Professional-Wrestling-Strength/dp/147669687XStore - Teepublic.com/stores/TMPTFollow us @TwoManPowerTrip on Twitter and IG

In this episode, Michael chats with Dr. Melissa Sadorf, Executive Director of the Arizona Rural Schools Association; Dr. Steven Johnson, Superintendent of Fort Ransom School District in North Dakota and leader of Rural Educational Associates; and Taylor McCabe-Juhnke, Executive Director of Rural Schools Collaborative. Together, they first offer a warm tribute to Dr. Allen Pratt, who is retiring as Executive Director of the National Rural Education Association. Then, they dive into the most important developments in rural education in 2024 and wrap up with some insights on what could be at the forefront in 2025.

On this episode of Stories with Brisco and Bradshaw, our hall of famers Gerald Brisco and John Bradshaw Layfield welcome author Steven Johnson. Steven discusses his latest project John Londos: The Golden Greek Of Professional Wrestling. The most famous active athlete in the world during the Great Depression was not Babe Ruth, Sonja Henie or Babe Didrikson it was John Londos! Steven tells us all about Londos' impact on the country and professional wrestling.  Learn more about your ad choices. Visit megaphone.fm/adchoices

Today, Dr. Robert Whitfield is joined by Dr. Nasha Winters, a naturopathic physician who emphasizes the importance of personalized care in cancer treatment. Dr. Winters discusses the “hallmarks of cancer” and the need for a holistic approach to treatment that considers diet, environment, and lifestyle. Despite advancements in understanding cancer biology, overall survival rates haven't improved significantly, which points to the necessity of more nuanced care. Her insights bring a fresh perspective on integrative oncology, which is crucial for patient outcomes. Be sure to tune in to hear more! Show Highlights: Challenges in Rural Healthcare (00:04:02) Dr. Whitfield highlights the difficulties of accessing advanced medical care in rural areas. Implant-Related Complications (00:03:36) Dr. Winters shares experiences of patients facing complications from medical implants and the need for support. Chronic Inflammatory Processes (00:17:16) Breast implants as part of a chronic inflammatory process affecting patients Enlightenment from a Cancer Patient (20:11) Dr. Whitfield shares how a cancer patient in 2016 taught him about the complexities of breast implant issues. Addressing Genetic Mutations (30:51) The role of genetics in cancer and the importance of environmental factors in health Hallmarks of Cancer (00:40:05) Overview of the evolving concept of cancer hallmarks and their implications for treatment strategies The Importance of Individualized Care (00:43:31) Emphasizing the uniqueness of each patient and the need for tailored treatment strategies Integrative Oncology Resources (00:56:09) Resources for learning about holistic oncology care and ongoing research efforts Connect with Dr. Whitfield Podcast (https://podcasts.apple.com/gb/podcast/breast-implant-illness/id1678143554) Spotify (https://open.spotify.com/show/1SPDripbluZKYsC0rwrBdb?si=23ea2cd9f6734667) TikTok (https://www.tiktok.com/@drrobertwhitfield?_t=8oQyjO25X5i&_r=1) IG (https://www.instagram.com/breastimplantillnessexpert/) FB (https://www.facebook.com/DrRobertWhitfield) Linkedin (https://www.linkedin.com/in/dr-robert-whitfield-md-50775b10/) X.com (https://x.com/rjwhitfield?lang=en) Read this article (https://www.breastcancer.org/treatment/surgery/breast-reconstruction/types/implant-reconstruction/illness/breast-implant-illness) Shop Dr. Whitfield's Solutions (https://drrobssolutions.com) SHARP (https://www.harp.health) NVISN Labs (https://nvisnlabs.com/) Get access to Dr. Rob's Favorite Products below: Danger Coffee (https://dangercoffee.com/pages/mold-free-coffee?ref=ztvhyjg) - Use our link for mold-free coffee. JASPR Air Purifier (https://jaspr.co/)- Use code DRROB for the Jaspr Air Purifier. Echo Water (https://echowater.com/)- Get high-quality water with our code DRROB10. BallancerPro (https://ballancerpro.com) - Use code DRROBVIP for the world's leader in lymphatic drainage technology. Ultrahuman (https://www.ultrahuman.com/ring/buy/us/?affiliateCode=drwhitfield)- Use code WHITFIELD10 for the most accurate wearable. Connect with Dr. Nasha Winters Dr. Nasha's Website (https://www.drnasha.com/) Dr. Nasha's podcast - Metabolic Matters (https://podcasts.apple.com/us/podcast/metabolic-matters/id1702761393) Books Mentioned Ravenous (https://amzn.to/41sG92H)by Sam Appel The Metabolic Approach to Cancer, (https://amzn.to/4g649gQ) by Dr. Nasha Winters and Jess Higgins Kelley Mistletoe and the Future of Integrative Oncology, (https://amzn.to/3ZOzu1y) by Steven Johnson, DO, Dr. Nasha Winters

NotebookLM is a research assistant powered by Gemini that draws on expertise from storytelling to present information in an engaging way. It allows users to upload their own documents and generate insights, explanations, and—more recently—podcasts. This feature, also known as audio overviews, has captured the imagination of millions of people worldwide, who have created thousands of engaging podcasts ranging from personal narratives to educational explainers using source materials like CVs, personal journals, sales decks, and more.Join Raiza Martin and Steven Johnson from Google Labs, Google's testing ground for products, as they guide host Hannah Fry through the technical advancements that have made NotebookLM possible. In this episode they'll explore what it means to be interesting, the challenges of generating natural-sounding speech, as well as exciting new modalities on the horizon.Further readingTry NotebookLM hereRead about the speech generation technology behind Audio Overveiws: https://deepmind.google/discover/blog/pushing-the-frontiers-of-audio-generation/Thanks to everyone who made this possible, including but not limited to: Presenter: Professor Hannah FrySeries Producer: Dan HardoonEditor: Rami Tzabar, TellTale Studios Commissioner & Producer: Emma YousifMusic composition: Eleni ShawCamera Director and Video Editor: Daniel LazardAudio Engineer: Perry RogantinVideo Studio Production: Nicholas DukeVideo Editor: Alex Baro Cayetano, Daniel Lazard Video Production Design: James BartonVisual Identity and Design: Eleanor TomlinsonCommissioned by Google DeepMind Please subscribe on your preferred podcast platform. Want to share feedback? Why not leave a review? Have a suggestion for a guest that we should have on next? Leave us a comment on YouTube and stay tuned for future episodes.

Cuddly as a cactus and charming as an eel, Whoville's favorite talk show host is back on the mic! The Grinch may hate the holidays, but he loves his new celebrity status as a chart-topping podcaster. With Cindy Lou and Max by his side, join The Grinch each week as he stubbornly refuses the joys of the season, cozies up to his celebrity guests — and investigates a brand-new mystery that puts him right at the center of another dastardly Christmas caper. All the children of Whoville's letters to Santa have gone missing, and Grinch is Suspect No. 1. Follow along at the end of each episode to help Grinch and his crew solve this WHO-dunnit in time for Christmas! Plus, tune into Wondery+ as Cindy Lou and Max take the case into their own hands! Starring SNL's James Austin Johnson as the iconic green grump, and featuring famous faces the whole family will love, 'Tis The Grinch Holiday Podcast might just grow your heart three sizes this winter season.For even more cheer, subscribe to Wondery+ to join Cindy Lou and Max the Dog as they take the case of the missing letters into their own hands!Follow 'Tis The Grinch Holiday Podcast on the Wondery App or wherever you get your podcasts. Unlock Cindy Lou and Max's exclusive Christmas mystery investigation and listen to every episode ad-free by joining Wondery+ in the Wondery App, Spotify, Apple Podcasts or by visiting Wondery.fm/Grinch.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Explore the fascinating world of AI and its potential to transform how we work, learn, and create with NotebookLM. Join guests Steven Johnson, Editorial Director of Notebook LM, and Raiza Martin, Senior Product Manager at Google Labs, leading Notebook LM for a deep dive into the inspiration, development, practical use cases, and more in this People of AI episode. Resources: A.I. Is Mastering Language. Should We Trust What It Says?                                → https://goo.gle/3Cub1Wd  → https://goo.gle/3UZOwPe  →  https://goo.gle/3OflIPc  Adjacent possible newsletter → https://goo.gle/3AGpe21    #TensorFlow #PeopleofAI    

In this thought-provoking episode, we explore the transformation of education in an era of rapid technological change and workplace evolution. Dr. Steven Johnson, founder and CEO of EDSENSE and former senior vice president of innovation at Harvard University, examines how emerging technologies, changing workforce demands, and new learning models are reshaping education's future.Key themes addressed:The convergence of AI, learning science, and personalized educationNew models for lifelong learning and skill developmentThe evolving relationship between education and employmentInnovative approaches to competency-based learning and credentialsTechnology's role in transforming traditional educational paradigmsThe future of hybrid learning environments and personalized education pathsThis dynamic discussion offers unprecedented insight into how educational institutions, employers, and learners can adapt to and thrive in an increasingly complex and rapidly changing landscape. Dr. Johnson makes a compelling case for reimagining education systems to better serve diverse learner needs while maintaining educational quality and accessibility.The Ecosystemic Futures Podcast, presented by NASA Convergent Aeronautics Solutions Project in collaboration with Shoshin Works, a global firm that helps organizations and nations navigate ecosystemic transformation. As our world is increasingly digital and interconnected – ecosystemic models are reshaping society, industry, economy, and policy and reframing how we build for resilient futures. Ecosystemic Futures investigates this expansive and hyper-connected paradigm and explores frameworks to help us achieve more beneficial futures.Guest:Dr. Steven Johnson is the Founder and CEO of EDSENSE, LLC, Host: Marco Annunziata, Co-Founder, Annunziata + Desai PartnersSeries Hosts: Vikram Shyam, Lead Futurist, NASA Glenn Research CenterDyan Finkhousen, Founder & CEO, Shoshin Works

Tech Life created a fake podcast using a new AI tool from Google Labs, and we spoke to the head of the tool, Steven Johnson. Don't worry – this programme is still brought to you by real human beings! We also look into how deepfakes have been used in the US. Plus – have we unveiled the real inventor of Bitcoin? (Spoiler – no.)We love hearing from you. Email us on techlife@bbc.co.uk or send a WhatsApp on +44 330 123 0320.Presenter: Chris Vallance Producer: Imran Rahman-Jones Editor: Monica Soriano(Image: An AI-generated head with letters coming out of its mouth. Credit: Getty Images.)

If you've listened to the podcast for a while, you might have heard our ElevenLabs-powered AI co-host Charlie a few times. Text-to-speech has made amazing progress in the last 18 months, with OpenAI's Advanced Voice Mode (aka “Her”) as a sneak peek of the future of AI interactions (see our “Building AGI in Real Time” recap). Yet, we had yet to see a real killer app for AI voice (not counting music).Today's guests, Raiza Martin and Usama Bin Shafqat, are the lead PM and AI engineer behind the NotebookLM feature flag that gave us the first viral AI voice experience, the “Deep Dive” podcast:The idea behind the “Audio Overviews” feature is simple: take a bunch of documents, websites, YouTube videos, etc, and generate a podcast out of them. This was one of the first demos that people built with voice models + RAG + GPT models, but it was always a glorified speech-to-text. Raiza and Usama took a very different approach:* Make it conversational: when you listen to a NotebookLM audio there are a ton of micro-interjections (Steven Johnson calls them disfluencies) like “Oh really?” or “Totally”, as well as pauses and “uh…”, like you would expect in a real conversation. These are not generated by the LLM in the transcript, but they are built into the the audio model. See ~28:00 in the pod for more details. * Listeners love tension: if two people are always in agreement on everything, it's not super interesting. They tuned the model to generate flowing conversations that mirror the tone and rhythm of human speech. They did not confirm this, but many suspect the 2 year old SoundStorm paper is related to this model.* Generating new insights: because the hosts' goal is not to summarize, but to entertain, it comes up with funny metaphors and comparisons that actually help expand on the content rather than just paraphrasing like most models do. We have had listeners make podcasts out of our podcasts, like this one.This is different than your average SOTA-chasing, MMLU-driven model buildooor. Putting product and AI engineering in the same room, having them build evals together, and understanding what the goal is lets you get these unique results. The 5 rules for AI PMsWe always focus on AI Engineers, but this episode had a ton of AI PM nuggets as well, which we wanted to collect as NotebookLM is one of the most successful products in the AI space:1. Less is more: the first version of the product had 0 customization options. All you could do is give it source documents, and then press a button to generate. Most users don't know what “temperature” or “top-k” are, so you're often taking the magic away by adding more options in the UI. Since recording they added a few, like a system prompt, but those were features that users were “hacking in”, as Simon Willison highlighted in his blog post.2. Use Real-Time Feedback: they built a community of 65,000 users on Discord that is constantly reporting issues and giving feedback; sometimes they noticed server downtime even before the Google internal monitoring did. Getting real time pings > aggregating user data when doing initial iterations. 3. Embrace Non-Determinism: AI outputs variability is a feature, not a bug. Rather than limiting the outputs from the get-go, build toggles that you can turn on/off with feature flags as the feedback starts to roll in.4. Curate with Taste: if you try your product and it sucks, you don't need more data to confirm it. Just scrap that and iterate again. This is even easier for a product like this; if you start listening to one of the podcasts and turn it off after 10 seconds, it's never a good sign. 5. Stay Hands-On: It's hard to build taste if you don't experiment. Trying out all your competitors products as well as unrelated tools really helps you understand what users are seeing in market, and how to improve on it.Chapters00:00 Introductions01:39 From Project Tailwind to NotebookLM09:25 Learning from 65,000 Discord members12:15 How NotebookLM works18:00 Working with Steven Johnson23:00 How to prioritize features25:13 Structuring the data pipelines29:50 How to eval34:34 Steering the podcast outputs37:51 Defining speakers personalities39:04 How do you make audio engaging?45:47 Humor is AGI51:38 Designing for non-determinism53:35 API when?55:05 Multilingual support and dialect considerations57:50 Managing system prompts and feature requests01:00:58 Future of NotebookLM01:04:59 Podcasts for your codebase01:07:16 Plans for real-time chat01:08:27 Wrap upShow Notes* Notebook LM* AI Test Kitchen* Nicholas Carlini* Steven Johnson* Wealth of Nations* Histories of Mysteries by Andrej Karpathy* chicken.pdf Threads* Area 120* Raiza Martin* Usama Bin ShafqatTranscriptNotebookLM [00:00:00]: Hey everyone, we're here today as guests on Latent Space. It's great to be here, I'm a long time listener and fan, they've had some great guests on this show before. Yeah, what an honor to have us, the hosts of another podcast, join as guests. I mean a huge thank you to Swyx and Alessio for the invite, thanks for having us on the show. Yeah really, it seems like they brought us here to talk a little bit about our show, our podcast. Yeah, I mean we've had lots of listeners ourselves, listeners at Deep Dive. Oh yeah, we've made a ton of audio overviews since we launched and we're learning a lot. There's probably a lot we can share around what we're building next, huh? Yeah, we'll share a little bit at least. The short version is we'll keep learning and getting better for you. We're glad you're along for the ride. So yeah, keep listening. Keep listening and stay curious. We promise to keep diving deep and bringing you even better options in the future. Stay curious.Alessio [00:00:52]: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Residence at Decibel Partners. And I'm joined by my co-host, Swyx, founder of Smol.ai.Swyx [00:01:01]: Hey, and today we're back in the studio with our special guest, Raiza Martin. And Raiza, I forgot to get your last name, Shafqat.Raiza [00:01:10]: Yes.Swyx [00:01:10]: Okay, welcome.Raiza [00:01:12]: Hello, thank you for having us.Swyx [00:01:14]: So AI podcasters meet human podcasters, always fun. Congrats on the success of Notebook LM. I mean, how does it feel?Raiza [00:01:22]: It's been a lot of fun. A lot of it, honestly, was unexpected. But my favorite part is really listening to the audio overviews that people have been making.Swyx [00:01:29]: Maybe we should do a little bit of intros and tell the story. You know, what is your path into the sort of Google AI org? Or maybe, actually, I don't even know what org you guys are in.Raiza [00:01:39]: I can start. My name is Raisa. I lead the Notebook LM team inside of Google Labs. So specifically, that's the org that we're in. It's called Google Labs. It's only about two years old. And our whole mandate is really to build AI products. That's it. We work super closely with DeepMind. Our entire thing is just, like, try a bunch of things and see what's landing with users. And the background that I have is, really, I worked in payments before this, and I worked in ads right before, and then startups. I tell people, like, at every time that I changed orgs, I actually almost quit Google. Like, specifically, like, in between ads and payments, I was like, all right, I can't do this. Like, this is, like, super hard. I was like, it's not for me. I'm, like, a very zero-to-one person. But then I was like, okay, I'll try. I'll interview with other teams. And when I interviewed in payments, I was like, oh, these people are really cool. I don't know if I'm, like, a super good fit with this space, but I'll try it because the people are cool. And then I really enjoyed that, and then I worked on, like, zero-to-one features inside of payments, and I had a lot of fun. But then the time came again where I was like, oh, I don't know. It's like, it's time to leave. It's time to start my own thing. But then I interviewed inside of Google Labs, and I was like, oh, darn. Like, there's definitely, like—Alessio [00:02:48]: They got you again.Raiza [00:02:49]: They got me again. And so now I've been here for two years, and I'm happy that I stayed because especially with, you know, the recent success of Notebook LM, I'm like, dang, we did it. I actually got to do it. So that was really cool.Usama [00:03:02]: Kind of similar, honestly. I was at a big team at Google. We do sort of the data center supply chain planning stuff. Google has, like, the largest sort of footprint. Obviously, there's a lot of management stuff to do there. But then there was this thing called Area 120 at Google, which does not exist anymore. But I sort of wanted to do, like, more zero-to-one building and landed a role there. We were trying to build, like, a creator commerce platform called Kaya. It launched briefly a couple years ago. But then Area 120 sort of transitioned and morphed into Labs. And, like, over the last few years, like, the focus just got a lot clearer. Like, we were trying to build new AI products and do it in the wild and sort of co-create and all of that. So, you know, we've just been trying a bunch of different things. And this one really landed, which has felt pretty phenomenal. Really, really landed.Swyx [00:03:53]: Let's talk about the brief history of Notebook LM. You had a tweet, which is very helpful for doing research. May 2023, during Google I.O., you announced Project Tailwind.Raiza [00:04:03]: Yeah.Swyx [00:04:03]: So today is October 2024. So you joined October 2022?Raiza [00:04:09]: Actually, I used to lead AI Test Kitchen. And this was actually, I think, not I.O. 2023. I.O. 2022 is when we launched AI Test Kitchen, or announced it. And I don't know if you remember it.Swyx [00:04:23]: That's how you, like, had the basic prototype for Gemini.Raiza [00:04:26]: Yes, yes, exactly. Lambda.Swyx [00:04:28]: Gave beta access to people.Raiza [00:04:29]: Yeah, yeah, yeah. And I remember, I was like, wow, this is crazy. We're going to launch an LLM into the wild. And that was the first project that I was working on at Google. But at the same time, my manager at the time, Josh, he was like, hey, I want you to really think about, like, what real products would we build that are not just demos of the technology? That was in October of 2022. I was sitting next to an engineer that was working on a project called Talk to Small Corpus. His name was Adam. And the idea of Talk to Small Corpus is basically using LLM to talk to your data. And at the time, I was like, wait, there's some, like, really practical things that you can build here. And just a little bit of background, like, I was an adult learner. Like, I went to college while I was working a full-time job. And the first thing I thought was, like, this would have really helped me with my studying, right? Like, if I could just, like, talk to a textbook, especially, like, when I was tired after work, that would have been huge. We took a lot of, like, the Talk to Small Corpus prototypes, and I showed it to a lot of, like, college students, particularly, like, adult learners. They were like, yes, like, I get it, right? Like, I didn't even have to explain it to them. And we just continued to iterate the prototype from there to the point where we actually got a slot as part of the I.O. demo in 23.Swyx [00:05:42]: And Corpus, was it a textbook? Oh, my gosh.Raiza [00:05:45]: Yeah. It's funny. Actually, when he explained the project to me, he was like, talk to Small Corpus. It was like, talk to a small corpse?Swyx [00:05:51]: Yeah, nobody says Corpus.Raiza [00:06:00]: It was like, a small corpse? This is not AI. Yeah, yeah. And it really was just, like, a way for us to describe the amount of data that we thought, like, it could be good for.Swyx [00:06:02]: Yeah, but even then, you're still, like, doing rag stuff. Because, you know, the context length back then was probably, like, 2K, 4K.Raiza [00:06:08]: Yeah, it was basically rag.Raiza [00:06:09]: That was essentially what it was.Raiza [00:06:10]: And I remember, I was like, we were building the prototypes. And at the same time, I think, like, the rest of the world was. Right? We were seeing all of these, like, chat with PDF stuff come up. And I was like, come on, we gotta go. Like, we have to, like, push this out into the world. I think if there was anything, I wish we would have launched sooner because I wanted to learn faster. But I think, like, we netted out pretty well.Alessio [00:06:30]: Was the initial product just text-to-speech? Or were you also doing kind of, like, synthesizing of the content, refining it? Or were you just helping people read through it?Raiza [00:06:40]: Before we did the I.O. announcement in 23, we'd already done a lot of studies. And one of the first things that I realized was the first thing anybody ever typed was, summarize the thing. Right?Raiza [00:06:53]: Summarize the document.Raiza [00:06:54]: And it was, like, half like a test and half just like, oh, I know the content. I want to see how well it does this. So it was part of the first thing that we launched. It was called Project Tailwind back then. It was just Q&A, so you could chat with the doc just through text, and it would automatically generate a summary as well. I'm not sure if we had it back then.Raiza [00:07:12]: I think we did.Raiza [00:07:12]: It would also generate the key topics in your document, and it could support up to, like, 10 documents. So it wasn't just, like, a single doc.Alessio [00:07:20]: And then the I.O. demo went well, I guess. And then what was the discussion from there to where we are today? Is there any, maybe, intermediate step of the product that people missed between this was launch or?Raiza [00:07:33]: It was interesting because every step of the way, I think we hit, like, some pretty critical milestones. So I think from the initial demo, I think there was so much excitement of, like, wow, what is this thing that Google is launching? And so we capitalized on that. We built the wait list. That's actually when we also launched the Discord server, which has been huge for us because for us in particular, one of the things that I really wanted to do was to be able to launch features and get feedback ASAP. Like, the moment somebody tries it, like, I want to hear what they think right now, and I want to ask follow-up questions. And the Discord has just been so great for that. But then we basically took the feedback from I.O., we continued to refine the product.Raiza [00:08:12]: So we added more features.Raiza [00:08:13]: We added sort of, like, the ability to save notes, write notes. We generate follow-up questions. So there's a bunch of stuff in the product that shows, like, a lot of that research. But it was really the rolling out of things. Like, we removed the wait list, so rolled out to all of the United States. We rolled out to over 200 countries and territories. We started supporting more languages, both in the UI and, like, the actual source stuff. We experienced, like, in terms of milestones, there was, like, an explosion of, like, users in Japan. This was super interesting in terms of just, like, unexpected. Like, people would write to us and they would be like, this is amazing. I have to read all of these rules in English, but I can chat in Japanese. It's like, oh, wow. That's true, right? Like, with LLMs, you kind of get this natural, it translates the content for you. And you can ask in your sort of preferred mode. And I think that's not just, like, a language thing, too. I think there's, like, I do this test with Wealth of Nations all the time because it's, like, a pretty complicated text to read. The Evan Smith classic.Swyx [00:09:11]: It's, like, 400 pages or something.Raiza [00:09:12]: Yeah. But I like this test because I'm, like, asking, like, Normie, you know, plain speak. And then it summarizes really well for me. It sort of adapts to my tone.Swyx [00:09:22]: Very capitalist.Raiza [00:09:25]: Very on brand.Swyx [00:09:25]: I just checked in on a Notebook LM Discord. 65,000 people. Yeah.Raiza [00:09:29]: Crazy.Swyx [00:09:29]: Just, like, for one project within Google. It's not, like, it's not labs. It's just Notebook LM.Raiza [00:09:35]: Just Notebook LM.Swyx [00:09:36]: What do you learn from the community?Raiza [00:09:39]: I think that the Discord is really great for hearing about a couple of things.Raiza [00:09:43]: One, when things are going wrong. I think, honestly, like, our fastest way that we've been able to find out if, like, the servers are down or there's just an influx of people being, like, it saysRaiza [00:09:53]: system unable to answer.Raiza [00:09:54]: Anybody else getting this?Raiza [00:09:56]: And I'm, like, all right, let's go.Raiza [00:09:58]: And it actually catches it a lot faster than, like, our own monitoring does.Raiza [00:10:01]: It's, like, that's been really cool. So, thank you.Swyx [00:10:03]: Canceled eat a dog.Raiza [00:10:05]: So, thank you to everybody. Please keep reporting it. I think the second thing is really the use cases.Raiza [00:10:10]: I think when we put it out there, I was, like, hey, I have a hunch of how people will use it, but, like, to actually hear about, you know, not just the context of, like, the use of Notebook LM, but, like, what is this person's life like? Why do they care about using this tool?Raiza [00:10:23]: Especially people who actually have trouble using it, but they keep pushing.Raiza [00:10:27]: Like, that's just so critical to understand what was so motivating, right?Raiza [00:10:31]: Like, what was your problem that was, like, so worth solving? So, that's, like, a second thing.Raiza [00:10:34]: The third thing is also just hearing sort of, like, when we have wins and when we don't have wins because there's actually a lot of functionality where I'm, like, hmm, IRaiza [00:10:42]: don't know if that landed super well or if that was actually super critical.Raiza [00:10:45]: As part of having this sort of small project, right, I want to be able to unlaunch things, too. So, it's not just about just, like, rolling things out and testing it and being, like, wow, now we have, like, 99 features. Like, hopefully we get to a place where it's, like, there's just a really strong core feature set and the things that aren't as great, we can just unlaunch.Swyx [00:11:02]: What have you unlaunched? I have to ask.Raiza [00:11:04]: I'm in the process of unlaunching some stuff, but, for example, we had this idea that you could highlight the text in your source passage and then you could transform it. And nobody was really using it and it was, like, a very complicated piece of our architecture and it's very hard to continue supporting it in the context of new features. So, we were, like, okay, let's do a 50-50 sunset of this thing and see if anybody complains.Raiza [00:11:28]: And so far, nobody has.Swyx [00:11:29]: Is there, like, a feature flagging paradigm inside of your architecture that lets you feature flag these things easily?Raiza [00:11:36]: Yes, and actually...Raiza [00:11:37]: What is it called?Swyx [00:11:38]: Like, I love feature flagging.Raiza [00:11:40]: You mean, like, in terms of just, like, being able to expose things to users?Swyx [00:11:42]: Yeah, as a PM. Like, this is your number one tool, right?Raiza [00:11:44]: Yeah, yeah.Swyx [00:11:45]: Let's try this out. All right, if it works, roll it out. If it doesn't, roll it back, you know?Raiza [00:11:49]: Yeah, I mean, we just run Mendel experiments for the most part. And, actually, I don't know if you saw it, but on Twitter, somebody was able to get around our flags and they enabled all the experiments.Raiza [00:11:58]: They were, like, check out what the Notebook LM team is cooking.Raiza [00:12:02]: I was, like, oh!Raiza [00:12:03]: And I was at lunch with the rest of the team and I was, like, I was eating. I was, like, guys, guys, Magic Draft League!Raiza [00:12:10]: They were, like, oh, no!Raiza [00:12:12]: I was, like, okay, just finish eating and then let's go figure out what to do.Raiza [00:12:15]: Yeah.Alessio [00:12:15]: I think a post-mortem would be fun, but I don't think we need to do it on the podcast now. Can we just talk about what's behind the magic? So, I think everybody has questions, hypotheses about what models power it. I know you might not be able to share everything, but can you just get people very basic? How do you take the data and put it in the model? What text model you use? What's the text-to-speech kind of, like, jump between the two? Sure.Raiza [00:12:42]: Yeah.Raiza [00:12:42]: I was going to say, SRaiza, he manually does all the podcasts.Raiza [00:12:46]: Oh, thank you.Usama [00:12:46]: Really fast. You're very fast, yeah.Raiza [00:12:48]: Both of the voices at once.Usama [00:12:51]: Voice actor.Raiza [00:12:52]: Good, good.Usama [00:12:52]: Yeah, so, for a bit of background, we were building this thing sort of outside Notebook LM to begin with. Like, just the idea is, like, content transformation, right? Like, we can do different modalities. Like, everyone knows that. Everyone's been poking at it. But, like, how do you make it really useful? And, like, one of the ways we thought was, like, okay, like, you maybe, like, you know, people learn better when they're hearing things. But TTS exists, and you can, like, narrate whatever's on screen. But you want to absorb it the same way. So, like, that's where we sort of started out into the realm of, like, maybe we try, like, you know, two people are having a conversation kind of format. We didn't actually start out thinking this would live in Notebook, right? Like, Notebook was sort of, we built this demo out independently, tried out, like, a few different sort of sources. The main idea was, like, go from some sort of sources and transform it into a listenable, engaging audio format. And then through that process, we, like, unlocked a bunch more sort of learnings. Like, for example, in a sense, like, you're not prompting the model as much because, like, the information density is getting unrolled by the model prompting itself, in a sense. Because there's two speakers, and they're both technically, like, AI personas, right? That have different angles of looking at things. And, like, they'll have a discussion about it. And that sort of, we realized that's kind of what was making it riveting, in a sense. Like, you care about what comes next, even if you've read the material already. Because, like, people say they get new insights on their own journals or books or whatever. Like, anything that they've written themselves. So, yeah, from a modeling perspective, like, it's, like Reiza said earlier, like, we work with the DeepMind audio folks pretty closely. So, they're always cooking up new techniques to, like, get better, more human-like audio. And then Gemini 1.5 is really, really good at absorbing long context. So, we sort of, like, generally put those things together in a way that we could reliably produce the audio.Raiza [00:14:52]: I would add, like, there's something really nuanced, I think, about sort of the evolution of, like, the utility of text-to-speech. Where, if it's just reading an actual text response, and I've done this several times. I do it all the time with, like, reading my text messages. Or, like, sometimes I'm trying to read, like, a really dense paper, but I'm trying to do actual work. I'll have it, like, read out the screen. There is something really robotic about it that is not engaging. And it's really hard to consume content in that way. And it's never been really effective. Like, particularly for me, where I'm, like, hey, it's actually just, like, it's fine for, like, short stuff. Like, texting, but even that, it's, like, not that great. So, I think the frontier of experimentation here was really thinking about there is a transform that needs to happen in between whatever.Raiza [00:15:38]: Here's, like, my resume, right?Raiza [00:15:39]: Or here's, like, a 100-page slide deck or something. There is a transform that needs to happen that is inherently editorial. And I think this is where, like, that two-person persona, right, dialogue model, they have takes on the material that you've presented. That's where it really sort of, like, brings the content to life in a way that's, like, not robotic. And I think that's, like, where the magic is, is, like, you don't actually know what's going to happen when you press generate.Raiza [00:16:08]: You know, for better or for worse.Raiza [00:16:09]: Like, to the extent that, like, people are, like, no, I actually want it to be more predictable now. Like, I want to be able to tell them. But I think that initial, like, wow was because you didn't know, right? When you upload your resume, what's it about to say about you? And I think I've seen enough of these where I'm, like, oh, it gave you good vibes, right? Like, you knew it was going to say, like, something really cool. As we start to shape this product, I think we want to try to preserve as much of that wow as much as we can. Because I do think, like, exposing, like, all the knobs and, like, the dials, like, we've been thinking about this a lot. It's like, hey, is that, like, the actual thing?Raiza [00:16:43]: Is that the thing that people really want?Alessio [00:16:45]: Have you found differences in having one model just generate the conversation and then using text-to-speech to kind of fake two people? Or, like, are you actually using two different kind of system prompts to, like, have a conversation step-by-step? I'm always curious, like, if persona system prompts make a big difference? Or, like, you just put in one prompt and then you just let it run?Usama [00:17:05]: I guess, like, generally we use a lot of inference, as you can tell with, like, the spinning thing takes a while. So, yeah, there's definitely, like, a bunch of different things happening under the hood. We've tried both approaches and they have their, sort of, drawbacks and benefits. I think that that idea of, like, questioning, like, the two different personas, like, persists throughout, like, whatever approach we try. It's like, there's a bit of, like, imperfection in there. Like, we had to really lean into the fact that, like, to build something that's engaging, like, it needs to be somewhat human and it needs to be just not a chatbot. Like, that was sort of, like, what we need to diverge from. It's like, you know, most chatbots will just narrate the same kind of answer, like, given the same sources, for the most part, which is ridiculous. So, yeah, there's, like, experimentation there under the hood, like, with the model to, like, make sure that it's spitting out, like, different takes and different personas and different, sort of, prompting each other is, like, a good analogy, I guess.Swyx [00:18:00]: Yeah, I think Steven Johnson, I think he's on your team. I don't know what his role is. He seems like chief dreamer, writer.Raiza [00:18:08]: Yeah, I mean, I can comment on Steven. So, Steven joined, actually, in the very early days, I think before it was even a fully funded project. And I remember when he joined, I was like, Steven Johnson's going to be on my team? You know, and for folks who don't know him, Steven is a New York Times bestselling author of, like, 14 books. He has a PBS show. He's, like, incredibly smart, just, like, a true, sort of, celebrity by himself. And then he joined Google, and he was like, I want to come here, and I want to build the thing that I've always dreamed of, which is a tool to help me think. I was like, a what? Like, a tool to help you think? I was like, what do you need help with? Like, you seem to be doing great on your own. And, you know, he would describe this to me, and I would watch his flow. And aside from, like, providing a lot of inspiration, to be honest, like, when I watched Steven work, I was like, oh, nobody works like this, right? Like, this is what makes him special. Like, he is such a dedicated, like, researcher and journalist, and he's so thorough, he's so smart. And then I had this realization of, like, maybe Steven is the product. Maybe the work is to take Steven's expertise and bring it to, like, everyday people that could really benefit from this. Like, just watching him work, I was like, oh, I could definitely use, like, a mini-Steven, like, doing work for me. Like, that would make me a better PM. And then I thought very quickly about, like, the adjacent roles that could use sort of this, like, research and analysis tool. And so, aside from being, you know, chief dreamer, Steven also represents, like, a super workflow that I think all of us, like, if we had access to a tool like it, would just inherently, like, make us better.Swyx [00:19:46]: Did you make him express his thoughts while he worked, or you just silently watched him, or how does this work?Raiza [00:19:52]: Oh, now you're making me admit it. But yes, I did just silently watch him.Swyx [00:19:57]: This is a part of the PM toolkit, right? They give user interviews and all that.Raiza [00:20:00]: Yeah, I mean, I did interview him, but I noticed, like, if I interviewed him, it was different than if I just watched him. And I did the same thing with students all the time. Like, I followed a lot of students around. I watched them study. I would ask them, like, oh, how do you feel now, right?Raiza [00:20:15]: Or why did you do that? Like, what made you do that, actually?Raiza [00:20:18]: Or why are you upset about, like, this particular thing? Why are you cranky about this particular topic? And it was very similar, I think, for Steven, especially because he was describing, he was in the middle of writing a book. And he would describe, like, oh, you know, here's how I research things, and here's how I keep my notes. Oh, and here's how I do it. And it was really, he was doing this sort of, like, self-questioning, right? Like, now we talk about, like, chain of, you know, reasoning or thought, reflection.Raiza [00:20:44]: And I was like, oh, he's the OG.Raiza [00:20:46]: Like, I watched him do it in real time. I was like, that's, like, L-O-M right there. And to be able to bring sort of that expertise in a way that was, like, you know, maybe, like, costly inference-wise, but really have, like, that ability inside of a tool that was, like, for starters, free inside of NotebookLM, it was good to learn whether or not people really did find use out of it.Swyx [00:21:05]: So did he just commit to using NotebookLM for everything, or did you just model his existing workflow?Raiza [00:21:12]: Both, right?Raiza [00:21:12]: Like, in the beginning, there was no product for him to use. And so he just kept describing the thing that he wanted. And then eventually, like, we started building the thing. And then I would start watching him use it. One of the things that I love about Steven is he uses the product in ways where it kind of does it, but doesn't quite. Like, he's always using it at, like, the absolute max limit of this thing. But the way that he describes it is so full of promise, where he's like, I can see it going here. And all I have to do is sort of, like, meet him there and sort of pressure test whether or not, you know, everyday people want it. And we just have to build it.Swyx [00:21:47]: I would say OpenAI has a pretty similar person, Andrew Mason, I think his name is. It's very similar, like, just from the writing world and using it as a tool for thought to shape Chachabitty. I don't think that people who use AI tools to their limit are common. I'm looking at my NotebookLM now. I've got two sources. You have a little, like, source limit thing. And my bar is over here, you know, and it stretches across the whole thing. I'm like, did he fill it up?Raiza [00:22:09]: Yes, and he has, like, a higher limit than others, I think. He fills it up.Raiza [00:22:14]: Oh, yeah.Raiza [00:22:14]: Like, I don't think Steven even has a limit, actually.Swyx [00:22:17]: And he has Notes, Google Drive stuff, PDFs, MP3, whatever.Raiza [00:22:22]: Yes, and one of my favorite demos, he just did this recently, is he has actually PDFs of, like, handwritten Marie Curie notes. I see.Swyx [00:22:29]: So you're doing image recognition as well. Yeah, it does support it today.Raiza [00:22:32]: So if you have a PDF that's purely images, it will recognize it.Raiza [00:22:36]: But his demo is just, like, super powerful.Raiza [00:22:37]: He's like, okay, here's Marie Curie's notes. And it's like, here's how I'm using it to analyze it. And I'm using it for, like, this thing that I'm writing.Raiza [00:22:44]: And that's really compelling.Raiza [00:22:45]: It's like the everyday person doesn't think of these applications. And I think even, like, when I listen to Steven's demo, I see the gap. I see how Steven got there, but I don't see how I could without him. And so there's a lot of work still for us to build of, like, hey, how do I bring that magic down to, like, zero work? Because I look at all the steps that he had to take in order to do it, and I'm like, okay, that's product work for us, right? Like, that's just onboarding.Alessio [00:23:09]: And so from an engineering perspective, people come to you and it's like, hey, I need to use this handwritten notes from Marie Curie from hundreds of years ago. How do you think about adding support for, like, data sources and then maybe any fun stories and, like, supporting more esoteric types of inputs?Raiza [00:23:25]: So I think about the product in three ways, right? So there's the sources, the source input. There's, like, the capabilities of, like, what you could do with those sources. And then there's the third space, which is how do you output it into the world? Like, how do you put it back out there? There's a lot of really basic sources that we don't support still, right? I think there's sort of, like, the handwritten notes stuff is one, but even basic things like DocX or, like, PowerPoint, right? Like, these are the things that people, everyday people are like, hey, my professor actually gave me everything in DocX. Can you support that? And then just, like, basic stuff, like images and PDFs combined with text. Like, there's just a really long roadmap for sources that I think we just have to work on.Raiza [00:24:04]: So that's, like, a big piece of it.Raiza [00:24:05]: On the output side, and I think this is, like, one of the most interesting things that we learned really early on, is, sure, there's, like, the Q&A analysis stuff, which is like, hey, when did this thing launch? Okay, you found it in the slide deck. Here's the answer. But most of the time, the reason why people ask those questions is because they're trying to make something new. And so when, actually, when some of those early features leaked, like, a lot of the features we're experimenting with are the output types. And so you can imagine that people care a lot about the resources that they're putting into NotebookLM because they're trying to create something new. So I think equally as important as, like, the source inputs are the outputs that we're helping people to create. And really, like, you know, shortly on the roadmap, we're thinking about how do we help people use NotebookLM to distribute knowledge? And that's, like, one of the most compelling use cases is, like, shared notebooks. It's, like, a way to share knowledge. How do we help people take sources and, like, one-click new documents out of it, right? And I think that's something that people think is, like, oh, yeah, of course, right? Like, one push a document. But what does it mean to do it right? Like, to do it in your style, in your brand, right?Raiza [00:25:08]: To follow your guidelines, stuff like that.Raiza [00:25:09]: So I think there's a lot of work, like, on both sides of that equation.Raiza [00:25:13]: Interesting.Swyx [00:25:13]: Any comments on the engineering side of things?Usama [00:25:16]: So, yeah, like I said, I was mostly working on building the text to audio, which kind of lives as a separate engineering pipeline, almost, that we then put into NotebookLM. But I think there's probably tons of NotebookLM engineering war stories on dealing with sources. And so I don't work too closely with engineers directly. But I think a lot of it does come down to, like, Gemini's native understanding of images really well with the latest generation.Raiza [00:25:39]: Yeah, I think on the engineering and modeling side, I think we are a really good example of a team that's put a product out there, and we're getting a lot of feedback from the users, and we return the data to the modeling team, right? To the extent that we say, hey, actually, you know what people are uploading, but we can't really support super well?Raiza [00:25:56]: Text plus image, right?Raiza [00:25:57]: Especially to the extent that, like, NotebookLM can handle up to 50 sources, 500,000 words each. Like, you're not going to be able to jam all of that into, like, the context window. So how do we do multimodal embeddings with that? There's really, like, a lot of things that we have to solve that are almost there, but not quite there yet.Alessio [00:26:16]: On then turning it into audio, I think one of the best things is it has so many of the human... Does that happen in the text generation that then becomes audio? Or is that a part of, like, the audio model that transforms the text?Usama [00:26:27]: It's a bit of both, I would say. The audio model is definitely trying to mimic, like, certain human intonations and, like, sort of natural, like, breathing and pauses and, like, laughter and things like that. But yeah, in generating, like, the text, we also have to sort of give signals on, like, where those things maybe would make sense.Alessio [00:26:45]: And on the input side, instead of having a transcript versus having the audio, like, can you take some of the emotions out of it, too? If I'm giving, like, for example, when we did the recaps of our podcast, we can either give audio of the pod or we can give a diarized transcription of it. But, like, the transcription doesn't have some of the, you know, voice kind of, like, things.Raiza [00:27:05]: Yeah, yeah.Alessio [00:27:05]: Do you reconstruct that when people upload audio or how does that work?Raiza [00:27:09]: So when you upload audio today, we just transcribe it. So it is quite lossy in the sense that, like, we don't transcribe, like, the emotion from that as a source. But when you do upload a text file and it has a lot of, like, that annotation, I think that there is some ability for it to be reused in, like, the audio output, right? But I think it will still contextualize it in the deep dive format. So I think that's something that's, like, particularly important is, like, hey, today we only have one format.Raiza [00:27:37]: It's deep dive.Raiza [00:27:38]: It's meant to be a pretty general overview and it is pretty peppy.Raiza [00:27:42]: It's just very upbeat.Raiza [00:27:43]: It's very enthusiastic, yeah.Raiza [00:27:45]: Yeah, yeah.Raiza [00:27:45]: Even if you had, like, a sad topic, I think they would find a way to be, like, silver lining, though.Raiza [00:27:50]: Really?Raiza [00:27:51]: Yeah.Raiza [00:27:51]: We're having a good chat.Raiza [00:27:54]: Yeah, that's awesome.Swyx [00:27:54]: One of the ways, many, many, many ways that deep dive went viral is people saying, like, if you want to feel good about yourself, just drop in your LinkedIn. Any other, like, favorite use cases that you saw from people discovering things in social media?Raiza [00:28:08]: I mean, there's so many funny ones and I love the funny ones.Raiza [00:28:11]: I think because I'm always relieved when I watch them. I'm like, haha, that was funny and not scary. It's great.Raiza [00:28:17]: There was another one that was interesting, which was a startup founder putting their landing page and being like, all right, let's test whether or not, like, the value prop is coming through. And I was like, wow, that's right.Raiza [00:28:26]: That's smart.Usama [00:28:27]: Yeah.Raiza [00:28:28]: And then I saw a couple of other people following up on that, too.Raiza [00:28:32]: Yeah.Swyx [00:28:32]: I put my about page in there and, like, yeah, if there are things that I'm not comfortable with, I should remove it. You know, so that it can pick it up. Right.Usama [00:28:39]: I think that the personal hype machine was, like, a pretty viral one. I think, like, people uploaded their dreams and, like, some people, like, keep sort of dream journals and it, like, would sort of comment on those and, like, it was therapeutic. I didn't see those.Raiza [00:28:54]: Those are good. I hear from Googlers all the time, especially because we launched it internally first. And I think we launched it during the, you know, the Q3 sort of, like, check-in cycle. So all Googlers have to write notes about, like, hey, you know, what'd you do in Q3? And what Googlers were doing is they would write, you know, whatever they accomplished in Q3 and then they would create an audio overview. And these people they didn't know would just ping me and be like, wow, I feel really good, like, going into a meeting with my manager.Raiza [00:29:25]: And I was like, good, good, good, good. You really did that, right?Usama [00:29:29]: I think another cool one is just, like, any Wikipedia article. Yeah. Like, you drop it in and it's just, like, suddenly, like, the best sort of summary overview.Raiza [00:29:38]: I think that's what Karpathy did, right? Like, he has now a Spotify channel called Histories of Mysteries, which is basically, like, he just took, like, interesting stuff from Wikipedia and made audio overviews out of it.Swyx [00:29:50]: Yeah, he became a podcaster overnight.Raiza [00:29:52]: Yeah.Raiza [00:29:53]: I'm here for it. I fully support him.Raiza [00:29:55]: I'm racking up the listens for him.Swyx [00:29:58]: Honestly, it's useful even without the audio. You know, I feel like the audio does add an element to it, but I always want, you know, paired audio and text. And it's just amazing to see what people are organically discovering. I feel like it's because you laid the groundwork with NotebookLM and then you came in and added the sort of TTS portion and made it so good, so human, which is weird. Like, it's this engineering process of humans. Oh, one thing I wanted to ask. Do you have evals?Raiza [00:30:23]: Yeah.Swyx [00:30:23]: Yes.Raiza [00:30:24]: What? Potatoes for chefs.Swyx [00:30:27]: What is that? What do you mean, potatoes?Raiza [00:30:29]: Oh, sorry.Raiza [00:30:29]: Sorry. We were joking with this, like, a couple of weeks ago. We were doing, like, side-by-sides. But, like, Raiza sent me the file and it was literally called Potatoes for Chefs. And I was like, you know, my job is really serious, but you have to laugh a little bit. Like, the title of the file is, like, Potatoes for Chefs.Swyx [00:30:47]: Is it like a training document for chefs?Usama [00:30:50]: It's just a side-by-side for, like, two different kind of audio transcripts.Swyx [00:30:54]: The question is really, like, as you iterate, the typical engineering advice is you establish some kind of test or benchmark. You're at, like, 30 percent. You want to get it up to 90, right?Raiza [00:31:05]: Yeah.Swyx [00:31:05]: What does that look like for making something sound human and interesting and voice?Usama [00:31:11]: We have the sort of formal eval process as well. But I think, like, for this particular project, we maybe took a slightly different route to begin with. Like, there was a lot of just within the team listening sessions. A lot of, like, sort of, like... Dogfooding.Raiza [00:31:23]: Yeah.Usama [00:31:23]: Like, I think the bar that we tried to get to before even starting formal evals with raters and everything was much higher than I think other projects would. Like, because that's, as you said, like, the traditional advice, right? Like, get that ASAP. Like, what are you looking to improve on? Whatever benchmark it is. So there was a lot of just, like, critical listening. And I think a lot of making sure that those improvements actually could go into the model. And, like, we're happy with that human element of it. And then eventually we had to obviously distill those down into an eval set. But, like, still there's, like, the team is just, like, a very, very, like, avid user of the product at all stages.Raiza [00:32:02]: I think you just have to be really opinionated.Raiza [00:32:05]: I think that sometimes, if you are, your intuition is just sharper and you can move a lot faster on the product.Raiza [00:32:12]: Because it's like, if you hold that bar high, right?Raiza [00:32:15]: Like, if you think about, like, the iterative cycle, it's like, hey, we could take, like, six months to ship this thing. To get it to, like, mid where we were. Or we could just, like, listen to this and be like, yeah, that's not it, right? And I don't need a rater to tell me that. That's my preference, right? And collectively, like, if I have two other people listen to it, they'll probably agree. And it's just kind of this step of, like, just keep improving it to the point where you're like, okay, now I think this is really impressive. And then, like, do evals, right? And then validate that.Swyx [00:32:43]: Was the sound model done and frozen before you started doing all this? Or are you also saying, hey, we need to improve the sound model as well? Both.Usama [00:32:51]: Yeah, we were making improvements on the audio and just, like, generating the transcript as well. I think another weird thing here was, like, we needed to be entertaining. And that's much harder to quantify than some of the other benchmarks that you can make for, like, you know, Sweebench or get better at this math.Swyx [00:33:10]: Do you just have people rate one to five or, you know, or just thumbs up and down?Usama [00:33:14]: For the formal rater evals, we have sort of like a Likert scale and, like, a bunch of different dimensions there. But we had to sort of break down what makes it entertaining into, like, a bunch of different factors. But I think the team stage of that was more critical. It was like, we need to make sure that, like, what is making it fun and engaging? Like, we dialed that as far as it goes. And while we're making other changes that are necessary, like, obviously, they shouldn't make stuff up or, you know, be insensitive.Raiza [00:33:41]: Hallucinations. Safety.Swyx [00:33:42]: Other safety things.Raiza [00:33:43]: Right.Swyx [00:33:43]: Like a bunch of safety stuff.Raiza [00:33:45]: Yeah, exactly.Usama [00:33:45]: So, like, with all of that and, like, also just, you know, following sort of a coherent narrative and structure is really important. But, like, with all of this, we really had to make sure that that central tenet of being entertaining and engaging and something you actually want to listen to. It just doesn't go away, which takes, like, a lot of just active listening time because you're closest to the prompts, the model and everything.Swyx [00:34:07]: I think sometimes the difficulty is because we're dealing with non-deterministic models, sometimes you just got a bad roll of the dice and it's always on the distribution that you could get something bad. Basically, how many do you, like, do ten runs at a time? And then how do you get rid of the non-determinism?Raiza [00:34:23]: Right.Usama [00:34:23]: Yeah, that's bad luck.Raiza [00:34:25]: Yeah.Swyx [00:34:25]: Yeah.Usama [00:34:26]: I mean, there still will be, like, bad audio overviews. There's, like, a bunch of them that happens. Do you mean for, like, the raider? For raiders, right?Swyx [00:34:34]: Like, what if that one person just got, like, a really bad rating? You actually had a great prompt, you actually had a great model, great weights, whatever. And you just, you had a bad output.Usama [00:34:42]: Like, and that's okay, right?Raiza [00:34:44]: I actually think, like, the way that these are constructed, if you think about, like, the different types of controls that the user has, right? Like, what can the user do today to affect it?Usama [00:34:54]: We push a button.Raiza [00:34:55]: You just push a button.Swyx [00:34:56]: I have tried to prompt engineer by changing the title. Yeah, yeah, yeah.Raiza [00:34:59]: Changing the title, people have found out.Raiza [00:35:02]: Yeah.Raiza [00:35:02]: The title of the notebook, people have found out. You can add show notes, right? You can get them to think, like, the show has changed. Someone changed the language of the output. Changing the language of the output. Like, those are less well-tested because we focused on, like, this one aspect. So it did change the way that we sort of think about quality as well, right? So it's like, quality is on the dimensions of entertainment, of course, like, consistency, groundedness. But in general, does it follow the structure of the deep dive? And I think when we talk about, like, non-determinism, it's like, well, as long as it follows, like, the structure of the deep dive, right? It sort of inherently meets all those other qualities. And so it makes it a little bit easier for us to ship something with confidence to the extent that it's like, I know it's going to make a deep dive. It's going to make a good deep dive. Whether or not the person likes it, I don't know. But as we expand to new formats, as we open up controls, I think that's where it gets really much harder. Even with the show notes, right? Like, people don't know what they're going to get when they do that. And we see that already where it's like, this is going to be a lot harder to validate in terms of quality, where now we'll get a greater distribution. Whereas I don't think we really got, like, varied distribution because of, like, that pre-process that Raiza was talking about. And also because of the way that we'd constrain, like, what were we measuring for? Literally, just like, is it a deep dive?Swyx [00:36:18]: And you determine what a deep dive is. Yeah. Everything needs a PM. Yeah, I have, this is very similar to something I've been thinking about for AI products in general. There's always like a chief tastemaker. And for Notebook LM, it seems like it's a combination of you and Steven.Raiza [00:36:31]: Well, okay.Raiza [00:36:32]: I want to take a step back.Swyx [00:36:33]: And Raiza, I mean, presumably for the voice stuff.Raiza [00:36:35]: Raiza's like the head chef, right? Of, like, deep dive, I think. Potatoes.Raiza [00:36:40]: Of potatoes.Raiza [00:36:41]: And I say this because I think even though we are already a very opinionated team, and Steven, for sure, very opinionated, I think of the audio generations, like, Raiza was the most opinionated, right? And we all, like, would say, like, hey, I remember, like, one of the first ones he sent me.Raiza [00:36:57]: I was like, oh, I feel like they should introduce themselves. I feel like they should say a title. But then, like, we would catch things, like, maybe they shouldn't say their names.Raiza [00:37:04]: Yeah, they don't say their names.Usama [00:37:05]: That was a Steven catch, like, not give them names.Raiza [00:37:08]: So stuff like that is, like, we all injected, like, a little bit of just, like, hey, here's, like, my take on, like, how a podcast should be, right? And I think, like, if you're a person who, like, regularly listens to podcasts, there's probably some collective preference there that's generic enough that you can standardize into, like, the deep dive format. But, yeah, it's the new formats where I think, like, oh, that's the next test. Yeah.Swyx [00:37:30]: I've tried to make a clone, by the way. Of course, everyone did. Yeah. Everyone in AI was like, oh, no, this is so easy. I'll just take a TTS model. Obviously, our models are not as good as yours, but I tried to inject a consistent character backstory, like, age, identity, where they work, where they went to school, what their hobbies are. Then it just, the models try to bring it in too much.Raiza [00:37:49]: Yeah.Swyx [00:37:49]: I don't know if you tried this.Raiza [00:37:51]: Yeah.Swyx [00:37:51]: So then I'm like, okay, like, how do I define a personality? But it doesn't keep coming up every single time. Yeah.Raiza [00:37:58]: I mean, we have, like, a really, really good, like, character designer on our team.Raiza [00:38:02]: What?Swyx [00:38:03]: Like a D&D person?Raiza [00:38:05]: Just to say, like, we, just like we had to be opinionated about the format, we had to be opinionated about who are those two people talking.Raiza [00:38:11]: Okay.Raiza [00:38:12]: Right.Raiza [00:38:12]: And then to the extent that, like, you can design the format, you should be able to design the people as well.Raiza [00:38:18]: Yeah.Swyx [00:38:18]: I would love, like, a, you know, like when you play Baldur's Gate, like, you roll, you roll like 17 on Charisma and like, it's like what race they are. I don't know.Raiza [00:38:27]: I recently, actually, I was just talking about character select screens.Raiza [00:38:30]: Yeah. I was like, I love that, right.Raiza [00:38:32]: And I was like, maybe there's something to be learned there because, like, people have fallen in love with the deep dive as a, as a format, as a technology, but also as just like those two personas.Raiza [00:38:44]: Now, when you hear a deep dive and you've heard them, you're like, I know those two.Raiza [00:38:48]: Right.Raiza [00:38:48]: And people, it's so funny when I, when people are trying to find out their names, like, it's a, it's a worthy task.Raiza [00:38:54]: It's a worthy goal.Raiza [00:38:55]: I know what you're doing. But the next step here is to sort of introduce, like, is this like what people want?Raiza [00:39:00]: People want to sort of edit the personas or do they just want more of them?Swyx [00:39:04]: I'm sure you're getting a lot of opinions and they all, they all conflict with each other. Before we move on, I have to ask, because we're kind of on this topic. How do you make audio engaging? Because it's useful, not just for deep dive, but also for us as podcasters. What is, what does engaging mean? If you could break it down for us, that'd be great.Usama [00:39:22]: I mean, I can try. Like, don't, don't claim to be an expert at all.Swyx [00:39:26]: So I'll give you some, like variation in tone and speed. You know, there's this sort of writing advice where, you know, this sentence is five words. This sentence is three, that kind of advice where you, where you vary things, you have excitement, you have laughter, all that stuff. But I'd be curious how else you break down.Usama [00:39:42]: So there's the basics, like obviously structure that can't be meandering, right? Like there needs to be sort of a, an ultimate goal that the voices are trying to get to, human or artificial. I think one thing we find often is if there's just too much agreement between people, like that's not fun to listen to. So there needs to be some sort of tension and build up, you know, withholding information. For example, like as you listen to a story unfold, like you're going to learn more and more about it. And audio that maybe becomes even more important because like you actually don't have the ability to just like skim to the end of something. You're driving or something like you're going to be hooked because like there's, and that's how like, that's how a lot of podcasts work. Like maybe not interviews necessarily, but a lot of true crime, a lot of entertainment in general. There's just like a gradual unrolling of information. And that also like sort of goes back to the content transformation aspect of it. Like maybe you are going from, let's say the Wikipedia article of like one of the History of Mysteries, maybe episodes. Like the Wikipedia article is going to state out the information very differently. It's like, here's what happened would probably be in the very first paragraph. And one approach we could have done is like maybe a person's just narrating that thing. And maybe that would work for like a certain audience. Or I guess that's how I would picture like a standard history lesson to unfold. But like, because we're trying to put it in this two-person dialogue format, like there, we inject like the fact that, you know, there's, you don't give everything at first. And then you set up like differing opinions of the same topic or the same, like maybe you seize on a topic and go deeper into it and then try to bring yourself back out of it and go back to the main narrative. So that's, that's mostly from like the setting up the script perspective. And then the audio, I was saying earlier, it's trying to be as close to just human speech as possible. I think was the, what we found success with so far.Raiza [00:41:40]: Yeah. Like with interjections, right?Raiza [00:41:41]: Like I think like when you listen to two people talk, there's a lot of like, yeah, yeah, right. And then there's like a lot of like that questioning, like, oh yeah, really?Raiza [00:41:49]: What did you think?Swyx [00:41:50]: I noticed that. That's great.Raiza [00:41:52]: Totally.Usama [00:41:54]: Exactly.Swyx [00:41:55]: My question is, do you pull in speech experts to do this? Or did you just come up with it yourselves? You can be like, okay, talk to a whole bunch of fiction writers to, to make things engaging or comedy writers or whatever, stand up comedy, right? They have to make audio engaging, but audio as well. Like there's professional fields of studying where people do this for a living, but us as AI engineers are just making this up as we go.Raiza [00:42:19]: I mean, it's a great idea, but you definitely didn't.Raiza [00:42:22]: Yeah.Swyx [00:42:24]: My guess is you didn't.Raiza [00:42:25]: Yeah.Swyx [00:42:26]: There's a, there's a certain field of authority that people have. They're like, oh, like you can't do this because you don't have any experience like making engaging audio. But that's what you literally did.Raiza [00:42:35]: Right.Usama [00:42:35]: I mean, I was literally chatting with someone at Google earlier today about how some people think that like you need a linguistics person in the room for like making a good chatbot. But that's not actually true because like this person went to school for linguistics. And according to him, he's an engineer now. According to him, like most of his classmates were not actually good at language. Like they knew how to analyze language and like sort of the mathematical patterns and rhythms and language. But that doesn't necessarily mean they were going to be eloquent at like while speaking or writing. So I think, yeah, a lot of we haven't invested in specialists in audio format yet, but maybe that would.Raiza [00:43:13]: I think it's like super interesting because I think there is like a very human question of like what makes something interesting. And there's like a very deep question of like what is it, right? Like what is the quality that we are all looking for? Is it does somebody have to be funny? Does something have to be entertaining? Does something have to be straight to the point? And I think when you try to distill that, this is the interesting thing I think about our experiment, about this particular launch is first, we only launched one format. And so we sort of had to squeeze everything we believed about what an interesting thing is into one package. And as a result of it, I think we learned it's like, hey, interacting with a chatbot is sort of novel at first, but it's not interesting, right? It's like humans are what makes interacting with chatbots interesting.Raiza [00:43:59]: It's like, ha ha ha, I'm going to try to trick it. It's like, that's interesting.Raiza [00:44:02]: Spell strawberry, right?Raiza [00:44:04]: This is like the fun that like people have with it. But like that's not the LLM being interesting.Raiza [00:44:08]: That's you just like kind of giving it your own flavor. But it's like, what does it mean to sort of flip it on its head and say, no, you be interesting now, right? Like you give the chatbot the opportunity to do it. And this is not a chatbot per se. It is like just the audio. And it's like the texture, I think, that really brings it to life. And it's like the things that we've described here, which is like, okay, now I have to like lead you down a path of information about like this commercialization deck.Raiza [00:44:36]: It's like, how do you do that?Raiza [00:44:38]: To be able to successfully do it, I do think that you need experts. I think we'll engage with experts like down the road, but I think it will have to be in the context of, well, what's the next thing we're building, right? It's like, what am I trying to change here? What do I fundamentally believe needs to be improved? And I think there's still like a lot more studying that we have to do in terms of like, well, what are people actually using this for? And we're just in such early days. Like it hasn't even been a month. Two, three weeks.Usama [00:45:05]: Three weeks.Raiza [00:45:06]: Yeah, yeah.Usama [00:45:07]: I think one other element to that is the fact that you're bringing your own sources to it. Like it's your stuff. Like, you know this somewhat well, or you care to know about this. So like that, I think, changed the equation on its head as well. It's like your sources and someone's telling you about it. So like you care about how that dynamic is, but you just care for it to be good enough to be entertaining. Because ultimately they're talking about your mortgage deed or whatever.Swyx [00:45:33]: So it's interesting just from the topic itself. Even taking out all the agreements and the hiding of the slow reveal. I mean, there's a baseline, maybe.Usama [00:45:42]: Like if it was like too drab. Like if someone was reading it off, like, you know, that's like the absolute worst.Raiza [00:45:46]: But like...Swyx [00:45:47]: Do you prompt for humor? That's a tough one, right?Raiza [00:45:51]: I think it's more of a generic way to bring humor out if possible. I think humor is actually one of the hardest things. Yeah.Raiza [00:46:00]: But I don't know if you saw...Raiza [00:46:00]: That is AGI.Swyx [00:46:01]: Humor is AGI.Raiza [00:46:02]: Yeah, but did you see the chicken one?Raiza [00:46:03]: No.Raiza [00:46:04]: Okay. If you haven't heard it... We'll splice it in here.Swyx [00:46:06]: Okay.Raiza [00:46:07]: Yeah.Raiza [00:46:07]: There is a video on Threads. I think it was by Martino Wong. And it's a PDF.Raiza [00:46:16]: Welcome to your deep dive for today. Oh, yeah. Get ready for a fun one. Buckle up. Because we are diving into... Chicken, chicken, chicken. Chicken, chicken. You got that right. By Doug Zonker. Now. And yes, you heard that title correctly. Titles. Our listener today submitted this paper. Yeah, they're going to need our help. And I can totally see why. Absolutely. It's dense. It's baffling. It's a lot. And it's packed with more chicken than a KFC buffet. What? That's hilarious.Raiza [00:46:48]: That's so funny. So it's like stuff like that, that's like truly delightful, truly surprising.Raiza [00:46:53]: But it's like we didn't tell it to be funny.Usama [00:46:55]: Humor is contextual also. Like super contextual is what we're realizing. So we're not prompting for humor, but we're prompting for maybe a lot of other things that are bringing out that humor.Alessio [00:47:04]: I think the thing about ad-generated content, if we look at YouTube, like we do videos on YouTube and it's like, you know, a lot of people like screaming in the thumbnails to get clicks. There's like everybody, there's kind of like a meta of like what you need to do to get clicks. But I think in your product, there's no actual creator on the other side investing the time. So you can actually generate a type of content that is maybe not universally appealing, you know, at a much, yeah, exactly. I think that's the most interesting thing. It's like, well, is there a way for like, take Mr.Raiza [00:47:36]: Beast, right?Alessio [00:47:36]: It's like Mr. Beast optimizes videos to reach the biggest audience and like the most clicks. But what if every video could be kind of like regenerated to be closer to your taste, you know, when you watch it?Raiza [00:47:48]: I think that's kind of the promise of AI that I think we are just like touching on, which is, I think every time I've gotten information from somebody, they have delivered it to me in their preferred method, right?Raiza [00:47:59]: Like if somebody gives me a PDF, it's a PDF.Raiza [00:48:01]: Somebody gives me a hundred slide deck, that is the format in which I'm going to read it. But I think we are now living in the era where transformations are really possible, which is, look, like I don't want to read your hundred slide deck, but I'll listen to a 16 minute audio overview on the drive home. And that, that I think is, is really novel. And that is, is paving the way in a way that like maybe we wanted, but didn'tRaiza [00:48:24]: expect.Raiza [00:48:25]: Where I also think you're listening to a lot of content that normally wouldn't have had content made about it. Like I watched this TikTok where this woman uploaded her diary from 2004.Raiza [00:48:36]: For sure, right?Raiza [00:48:36]: Like nobody was goin

Hour one of DJ & PK for October 18, 2024: Pablo Mastroenu, Real Salt Lake Berry Tramel, Tulsa World Steven Johnson, Fort Worth Star-Telegram

The entirety of DJ & PK for October 18, 2024: HOUR ONE Pablo Mastroenu, Real Salt Lake Berry Tramel, Tulsa World Steven Johnson, Fort Worth Star-Telegram HOUR TWO What is Trending BYU Cougars vs. Oklahoma State Cowboys Will the Utah Utes snap their slide? HOUR THREE David Locke, Utah Jazz Radio Hot Takes or Toast Will the Utah Utes beat TCU? HOUR FOUR Kevin Graham on the NFL Slacker Radio Headlines Feedback of the Day

Fort Worth Star-Telegram TCU beat writer Steven Johnson joined DJ & PK to talk about the TCU Horned Frogs as they prepare to take on the Utah Utes Saturday night.

Hour four of DJ & PK for October 17, 2024: Steven Johnson, Fort Worth Star-Telegram Slacker Radio Headlines Feedback of the Day

The entirety of DJ & PK for October 17, 2024: HOUR ONE Karene Reid, Utah Utes Lineback Riley Jensen, College Football Expert Matt Brown, Extra Points HOUR TWO What is Trending Hot Takes or Toast Will the BYU Cougars keep the run going? HOUR THREE Berry Tramel, Tulsa World Pablo Mastroeni, Real Salt Lake When will BYU pick up its first loss? HOUR FOUR Steven Johnson, Fort Worth Star-Telegram Slacker Radio Headlines Feedback of the Day

In our second installment in this new series, hosts Michael Tamblyn and Nathan Maharaj sat down to go over some of the latest goings-on since summer in the business of books. Topics covered in this episode: Is AI a no-go for NaNoWriMo? Audible announces AI narration—as a side hustle for human narrators B&N needs more shovels (to deal with AI) Bestselling nonfiction author Steven Johnson on employing AI as research assistant on steriods - The Verge Odds on an AI writing a bestselling book Fewer booksellers at Apple Books A leaner, meaner penguin* in the Penguin Random House logo (or, the slimming power of a strong vertical line)? Gen Z's eReader moment Books mentioned: By Stephen Johnson: The Ghost Map, Where Good Ideas Come From Naked Came the Stranger by Penelope Ashe (aka. Mike McGrady "and two dozen of his colleagues") *This conversation contains a brief digression into off-label use of Ozempic. Please listen with care.

Raiza Martin is a senior product manager for AI at Google Labs, where she leads the team behind NotebookLM, an AI-powered research tool that includes a delightful podcast-on-demand feature called “Audio Overviews.” NotebookLM started as a 20% project and has grown into a product that's spreading across social media and has a Discord server with over 60,000 users. Raiza previously worked on AI Test Kitchen and has a background in startups, payments, and ads. In our conversation, we discuss:• The origin story of NotebookLM• The future road map for NotebookLM• How Google Labs operates differently from the rest of Google• The development of the “Audio Overviews” feature• Key metrics and growth of NotebookLM• Stories about collaborating with author Steven Johnson• Navigating potential misuse of AI technology—Brought to you by:• Explo — Embed customer-facing analytics in your product• Sprig⁠⁠ — Build products for people, not data points• Sidebar — Accelerate your career by surrounding yourself with extraordinary peers—Find the transcript and show notes at: https://www.lennysnewsletter.com/p/googles-notebooklm-raiza-martin—Where to find Raiza Martin:• X: https://x.com/raiza_abubakar• LinkedIn: https://www.linkedin.com/in/whatsaraiza/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to NotebookLM(05:43) The genesis of NotebookLM(08:08) Innovative features and use cases(18:52) Building a startup culture within Google(24:28) Expanding user demographics(27:30) The product roadmap(32:18) Other use cases(36:11) Collaborating with Steven Johnson(42:49) Ensuring ethical AI(46:06) Future directions and user engagement—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

This week, Casey reports back from a wild day at Meta Connect, discussing what's new with Meta's efforts in artificial intelligence, virtual reality headsets and the Holy Grail — augmented reality glasses. Then, Steven Johnson, a writer and editorial director at Google Labs, stops by to talk about the company's new hit NotebookLM, which uses A.I. to turn even boring PDFs, such as user manuals and Kevin's bank records, into chatty, disturbingly good podcasts. Finally, so much happened in tech news this week that we reached for the bucket hat in the latest installment of HatGPT! Guest:Steven Johnson, author and editorial director, NotebookLM Additional Reading: Meta Unveils New Smart Glasses and Headsets in Pursuit of the MetaverseA.I. Is Mastering Language. Should We Trust What It Says?OpenAI Executives Exit as C.E.O. Works to Make the Company For-Profit We want to hear from you. Email us at hardfork@nytimes.com. Find “Hard Fork” on YouTube and TikTok.

For the first episode in our new miniseries about the impact of AI in our everyday lives, we chat with Steven Johnson, a longtime author who has spent the last couple of years at Google working on an AI research and note-taking tool called NotebookLM. We talk about whether AI can really help us learn better, how Google has tried to make NotebookLM more accurate and helpful, and whether AI-generated podcasts are the future of learning.  Further reading: NotebookLM Steven Johnson's website / newsletter From Steven Johnson: Listening To The Algorithm Google teases Project Tailwind — a prototype AI notebook that learns from your documents Google's AI-powered note-taking app is the messy beginning of something great Google is using AI to make fake podcasts from your notes Email us at vergecast@theverge.com or call us at 866-VERGE11, we love hearing from you. Learn more about your ad choices. Visit podcastchoices.com/adchoices

At a time when we're debating where policing is going, we're going to tell you where the police came from. Guided by Peabody award-winning host Chenjerai Kumanyika, Empire City will provide the first accessible narrative history of the American police and its place in popular culture. Who are the police? And why were police departments created in the first place? To find answers, we're going to tell the origin story of the largest police force in the world: The NYPD. We begin in the late 1800's at a moment when the entire police force was on trial. It's the biggest corruption scandal in the history of the NYPD, and it all plays out like a high stakes courtroom drama. What follows is the action-packed account of how the NYPD got to this point and what happened next. It involves Black abolitionists fighting slave patrols in the courts of Gotham; two rival police forces duking it out for power at City Hall; the origins of the true crime genre; and how the NYPD spread their tactics worldwide.Listen to Empire City wherever you get your podcasts: Wondery.fm/Empire_City.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Today we bring you a case where bodies began popping up in the radius of 1 mile around the area of Asylum Hills in Hartford, Connecticut starting in 1999. It is a horrifying case where a man with so much hostility takes out his anger on vulnerable women. Listen to today's episode to hear about the brutal beatings 11 women endured at the hands of Matthew Steven Johnson. Sources; https://www.oxygen.com/mark-of-a-serial-killer/crime-news/serial-killer-matthew-steven-johnson-crushed-victims-skulls Hartford Courant Edition January 16 2002; January 28 2004 Matthew Steven Johnson - Wikipedia STATE v. JOHNSON (2008) | FindLaw State v. Johnson, 2009 Ct. Sup. 7373 | Casetext Search + Citator --- Support this podcast: https://podcasters.spotify.com/pod/show/homicidehobbies/support

Summary Dr. Steven Johnson, a father, radiologist, non-profit founder, and Ironman athlete, shares his journey of founding a non-profit organization called Race Against Blindness after his son was diagnosed with retinitis pigmentosa, a rare genetic condition that causes vision loss. He discusses the challenges of balancing his full-time job, running the non-profit, and being present for his family. Johnson emphasizes the importance of finding purpose and being of service to others as a way to overcome challenges and make a difference in the world. Steve Johnston discusses the importance of taking action and making a positive impact on others. He emphasizes the power of service to others and the potential for the butterfly effect to create significant change. Steve also shares his involvement with the nonprofit organization Race Against Blindness, which funds research to cure childhood blindness. He highlights the tangible impact that donations can have and encourages listeners to spread awareness about the cause. In the context of fatherhood, Steve emphasizes the importance of living life to the fullest and not waiting for tomorrow. He encourages fathers to be present for their families and lead by example. Takeaways Dr. Steven Johnson founded the non-profit organization Race Against Blindness after his son was diagnosed with retinitis pigmentosa. Balancing a full-time job, running a non-profit, and being present for family can be challenging, but it is important to prioritize and manage time effectively. Finding purpose and being of service to others can help overcome challenges and make a positive impact. Volunteering and getting involved in the community can lead to personal growth and fulfillment. Being a leader in your home and community can create positive change and inspire others. Taking action and making a positive impact on others can inspire and motivate them to overcome challenges. Service to others and servant leadership can create a butterfly effect, leading to significant change. Donations to nonprofit organizations can have a tangible and immediate impact on important causes. Spreading awareness about a cause is a crucial first step in making a difference. Fatherhood means putting family first, being a rock for your family, and leading by example. Living life to the fullest and not waiting for tomorrow is essential for personal growth and fulfillment. Chapters 00:00 Introduction and Guest Introduction 03:20 Discovering the Rare Genetic Condition 09:17 The Emotional Impact and Taking Action 14:12 Balancing Work, Nonprofit, and Family Life 18:44 Finding Purpose and Being of Service 22:43 The Power of Making a Positive Impact 25:26 The Butterfly Effect: Small Actions, Big Changes 27:28 Race Against Blindness: Funding Research to Cure Childhood Blindness 29:21 Race Against Blindness: Racing Against Time and Blindness 31:09 From Ironman Athlete to Inspiring Father: Overcoming Challenges 35:49 Join the Race: Spreading Awareness and Making an Impact 38:35 Live Life to the Fullest: Don't Wait, Take Action 41:43 Fatherhood: Giving It All Without Regrets 46:03 Inspiring Others: Be Motivated, Not Comparing 48:48 Supporting Race Against Blindness: Donate, Share, and Spread the Word 49:22 New Chapter A Race Against Blindness - Nonprofit funding sight-saving research www.4fitfatherhood.carrd.co You have a limited offer you can use now, that gets you up to 48% off your first subscription or 20% off one time purchases with code 4FIT20 at checkout You can claim it at: https://magicmind.com/4fit20 --- Support this podcast: https://podcasters.spotify.com/pod/show/4fitfatherhood/support

This episode is brought to you by BetterHelp. Give online therapy a try at betterhelp.com/365 and get on your way to being your best self. Learn more about your ad choices. Visit megaphone.fm/adchoices

(0:40:00) Colt Barber, SicEm365.com (1:00:00) Dave Wilson, ESPN.com (1:25:00) Jed Drenning, West Virginia Sideline Reporter (1:45:00) Hans Olsen, BYU Color Analyst (2:10:00) Steven Johnson, Fort Worth Star-Telegram (2:30:00) Chris Karpman, SunDevilSource.com (2:48:00) Paul Catalina's Top  Learn more about your ad choices. Visit megaphone.fm/adchoices

Steven Johnson returns! He's with us today to talk about his new book, "The Infernal Machine: A True Story of Dynamite, Terror, and the Rise of the Modern Detective," and his new day job helping Google develop AI tools for writers.

A very special episode this week with actor Steven Johnson who has been touring the country with the Broadway production of To Kill a Mockingbird. He's been to over 70 cities across 40 states, and he's got some incredible stories to share. From bustling food trucks to Michelin-worthy hidden gems, Steven's journey has not only expanded his palate but also challenged his preconceptions about various regions. He'll be dishing out his favorite places to eat, what makes each spot special, and the surprising culinary treasures he's found in cities you might not expect. Join us as we explore the rich and diverse food landscape of the United States, learn about the regional nuances, and hear firsthand how travel has broadened Steven's perspectives on food and culture. You won't want to miss his recommendations and the unique experiences he's gathered along the way. Check if To Kill a Mockingbird is coming to a theater near you TAKE THE QUIZ TO SEE IF YOU'VE BEEN PLANNING YOUR TRAVEL ALL WRONG!    ***Looking to experience the flavors we've explored firsthand?  Skip the stress of travel planning and work with a trusted professional to take care of all of that for you!   Travel Trails specializes in crafting unforgettable travel experiences tailored to your taste for adventure.  Don't miss out on tasting these delicious dishes because you don't have the time to plan.  Visit https://travel-trails.com/ to learn more and follow  @TastyTrailsTravelPod and @Travel.Trails___ on Instagram to stay up to date on episodes and all things food & travel 

In this episode of The Observatory, Scott and LaRae discuss the profound concept of healing, exploring what it truly means, emphasizing why we crucially need healing, and guiding us through the transformative journey to achieve inner healing. Hear why the healing journey is so personal, how your belief system impacts it, and the things in your life that can ignite it. They also share the steps to take in your healing journey and why it's important to let go of the need always to be right. Timestamps[03:44] What is a healing journey?[10:58] Why the healing journey is so personal[13:04] God is a mirror[18:03] How your belief system impacts your healing journey [21:02] The book: Wonderland by Steven Johnson[27:33] The evolution of taste, music, and fashion [34:00] How the mind works [43:03] The moments in your life that can ignite your healing journey [50:34] The steps to take in your healing journey[53:34] The importance of letting go of the need to be right Notable quotes:“A healing journey starts from the desire to become more aware of yourself.” - LaRae Wright [05:12]“Everyone is a mirror, and we get to see different perspectives of other people's lives.” - Scott [13:08]“Your belief system is going to limit your ability to see other things differently.” - Scott [18:05]“Just because we think differently doesn't mean we can't be friends.” - LaRae Wright [29:37]Relevant links:LaRae Instagram: @larae_wrightScott Instagram: @scott_david_wrightThe book: Wonderland by Steven JohnsonSubscribe to the podcast: Apple Podcast

Let's blow it up! Author Steven Johnson joins me to talk his new (and incredible) book The Infernal Machine: A True Story of Dynamite, Terror, and the Rise of the Modern Detective. It's a book of the year according to me so come listen!Buy The Infernal MachineCheck out Steven's websiteSupport the Show.

Yesterday's action by the ICC action targeting both Israeli and Hamas leaders for war crimes and crimes against humanity has prompted furious condemnation from Israel and the United States, but France and Belgium have broken with these allies by supporting the court. Bestselling Israeli author and historian Yuval Noah Harari has been thinking deeply on his homeland and the possibility of peace between Israelis and Palestinians even now, asking in a Financial Times op-ed "Is there a way out of the Israeli-Palestinian trap?." He joins the show in London.   Also on today's show: Chef Fadi Kattan, Author, "Bethlehem: A Celebration of Palestinian Food"; Steven Johnson, Author, "The Infernal Machine"  Learn more about your ad choices. Visit podcastchoices.com/adchoices

Steven Johnson returns to share some key insights from his new book "The Infernal Machine: A True Story of Dynamite, Terror, and the Rise of the Modern Detective."

The Wing was supposed to be a model for feminist social clubs, built on activism, inclusion, and self-care. But instead, The Wing became a glaring example of toxic girlboss culture and workplace discrimination. On each episode of Wondery's podcast The Big Flop, comedians join host Misha Brown to chronicle one of the biggest pop-culture fails of all time and try to answer the age-old question: who thought THIS was a good idea?This is just a preview of The Big Flop. Listen to the full episode wherever you get your podcasts, or at wondery.fm/the-big-flop.For more deep dive and daily business content listen to Wondery – the destination for business podcasts. With shows like How I Built This, Business Wars, The Best One Yet, Business Movers and many more, Wondery Means Business.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

For real life royals, the crown jewels can be more like shiny handcuffs. There are expectations and rules – and if you break them, the consequences are big, and very public. And no, we're not just talking about Harry and Meghan. There are royal families and wild royal tales from around the world and throughout history that you have never heard before. From Wondery comes the latest from Even the Rich co-hosts Brooke Siffrinn and Aricia Skidmore-Williams. Even the Royals takes us inside the cloistered world of royal families, past and present, where wealth and status often come at the expense of your freedom – and maybe even your life. In these stories, very human emotions, like jealousy, love, disgust, have the power to reshape the world. This is just a preview of Even the Royals. Listen to the full episode wherever you get your podcasts, or at wondery.fm/eventheroyals.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Cuddly as a cactus and charming as an eel, he's your new favorite snarky talk show host. Join The Grinch (and his faithful dog Max) each week as he rants against Christmas cheer and roasts celebrity guests like chestnuts on an open fire. Starring Saturday Night Live's James Austin Johnson as the notorious curmudgeon and broadcasting straight from Who-Ville, will The Grinch send these famous folks back down Mt. Crumpit, or will they soften his stance against Christmas and grow his heart three sizes? Grab your hot cocoa and cozy slippers and listen along to find out!Follow 'Tis The Grinch Holiday Talk Show on the Wondery App or wherever you get your podcasts. You can listen to episodes of 'Tis The Grinch Holiday Talk Show early and ad-free right now by joining Wondery Plus. Listen now: Wondery.fm/GrinchSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Follow MrBallen's Medical Mysteries wherever you get your podcasts. You can binge the first 8 episodes, early and ad-free on Amazon Music. Download the Amazon Music app today.The human body is a miracle. But when it's not working, it can be the stuff of nightmares. On this new series from master storyteller MrBallen, we're sharing medical horror stories and diagnostic mysteries that are surgically calibrated to make your blood run cold. From bizarre, unheard-of diseases and miraculous recoveries to strange medical mishaps and unexplainable deaths — you'll never hear the phrase “heart-stopping” in the same way again. MrBallen's Medical Mysteries is a first-of-its-kind collaboration between MrBallen and Wondery, the award-winning company behind Dr. Death.Listen Now: Wondery.fm/MBMM See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.