Podcast appearances and mentions of Evan Spiegel

Kids these days, you know? They love the '90s, they want everything to be colorful and bold and bouncy, and they really, truly love Snapchat. And the tech world is listening. On this episode, The Verge's Allison Johnson joins to talk about her review of the new Razr Ultra, the new-look Android 16, and why she thinks we're getting ever closer to a true flip phone resurgence. (Also: why we're not quite there yet.) After that, The Verge's Alex Heath explains what's going on with Snapchat, and how it's possible that the app is more popular than ever but still can't figure out how to cash in. It all makes us wonder: is there a business in chat at all? Finally, we answer a question on the Vergecast Hotline (call 866-VERGE11 or email vergecast@theverge.com!) about a possible outcome for Chrome after the Google search trial ends. Further reading: Motorola Razr Ultra (2025) review: looking sharp The best folding phones you can buy Android's youthful new design language just dropped Snapchat scraps ‘simple' redesign as it loses users in North America Zuckerberg offered to buy Snapchat for $6 billion. Evan Spiegel explains why Snap is betting on Spectacles Breaking down the DOJ's plan to end Google's search monopoly Why are companies lining up to buy Chrome? Learn more about your ad choices. Visit podcastchoices.com/adchoices

What started as a design project for Stanford student Evan Spiegel quickly flourished into one of the most-used social media platforms in the world: Snapchat. It only took two years for Mark Zuckerberg to make a multi-billion offer for the company. But Evan turned it down — convinced of Snap's potential to disrupt human communication in an even bigger way. And while Evan's path has been anything but smooth, today Snap is valued at more than $13 billion, with ambitions beyond its hero mobile app.This episode was produced by Alex Cheng with music composed by Ramtin Arablouei. It was edited by John Isabella with research help from Katherine Sypher. Our engineers were Patrick Murray and Gilly Moon.You can follow HIBT on X & Instagram, and email us at hibt@id.wondery.com. Sign up for Guy's free newsletter at guyraz.com or on Substack.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Gaurav Misra is the co-founder and CEO of Captions, an AI-powered video creation company and one of the most successful consumer AI products in the world today. Previously he was a product leader at Snap, where he created the design engineering function and spent years helping develop features used by hundreds of millions of users worldwide. With a background in both engineering and design, Gaurav brings a unique cross-functional perspective to product development.What you'll learn:1. Why the “ship a marketable feature every week” approach helps his team stay focused and the product stay top of mind for users amid constant AI breakthroughs2. How to balance rapid shipping with maintaining quality by cutting scope rather than compromising on timelines3. The “secret roadmap” strategy that helps Captions develop breakthrough features competitors never see coming4. Why taking on strategic technical debt is essential for startups to outpace larger companies5. How Captions accidentally ignored their most successful product for 1.5 years (and why it still grew to 500K users with no updates or support)6. How Snap's unique product development approach—with designers functioning as PMs—enabled their success as the last major social network to break through7. Why AI video will transform marketing before other industries—Brought to you by:• Brex — The banking solution for startups• Paragon—Ship every SaaS integration your customers want• Coda—The all-in-one collaborative workspace—Find the transcript at: https://www.lennysnewsletter.com/p/how-to-win-in-the-ai-era-gaurav-misra—Where to find Gaurav Misra:• X: https://x.com/gmharhar• LinkedIn: https://www.linkedin.com/in/gamisra1/—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) Gaurav's background(04:47) The exciting era of AI and startups(09:30) Staying top of mind(11:26) Tips for staying focused(13:14) Shipping marketable features weekly(19:03) Managing technical debt in startups(25:31) Snap's unique product development approach(32:09) Brainstorming with AI(35:09) What Snap got right(41:06) Scaling with a small, agile team(49:33) The shift toward prototyping in product management(51:47) The product manager role(55:40) Snap's mission and product decisions(01:02:13) The future of AI-generated video(01:10:20) Leveraging AI for marketing(01:14:37) Failure corner(01:20:21) Lightning round and closing thoughts—Referenced:• Snap: https://www.snap.com/• Captions: https://www.captions.ai/• Iron Man on Disney+: https://www.disneyplus.com/movies/iron-man/6aM2a8mZATiu• J.A.R.V.I.S.: https://en.wikipedia.org/wiki/J.A.R.V.I.S.• Cursor: https://www.cursor.com/• Devin: https://devin.ai/• Eye contact: https://www.captions.ai/eye-contact• Nvidia: https://www.nvidia.com• Descript: https://www.descript.com• Evan Spiegel on LinkedIn: https://www.linkedin.com/in/evan-spiegel-8ab74034a/• TikTok: https://www.tiktok.com/• Spotlight: https://www.snapchat.com/spotlight/• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• Patrick Collison on X: https://x.com/patrickc• DeepSeek: https://www.deepseek.com/• ByteDance Goku: New video generation AI model, better than OpenAI Sora: https://medium.com/data-science-in-your-pocket/bytedance-goku-new-video-generation-ai-model-better-than-openai-sora-56c017a320a5• Will Smith eating spaghetti and other weird AI benchmarks that took off in 2024: https://techcrunch.com/2024/12/31/will-smith-eating-spaghetti-and-other-weird-ai-benchmarks-that-took-off-in-2024/• Silo on AppleTV+: https://tv.apple.com/us/show/silo/umc.cmc.3yksgc857px0k0rqe5zd4jice• Severance on AppleTV+: https://tv.apple.com/us/show/severance/umc.cmc.1srk2goyh2q2zdxcx605w8vtx• Linear: https://linear.app/• Superhuman: https://superhuman.com/• Notion: https://www.notion.com• Perplexity: https://www.perplexity.ai/• OmniHuman-1 AI Video Generation Looks Too Real: https://www.youtube.com/watch?v=fY0KB516m-E—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

From turning down $3 billion from Facebook to building a $100 billion empire, Evan Spiegel reveals the blueprint behind Snapchat. Evan Spiegel, co-founder & CEO of Snapchat (now Snap Inc.), founded the app while at Stanford and became the youngest billionaire at 25. In this conversation, Evan and Steven cover how Snapchat almost didn't exist, Evan's ‘T-Shaped' leadership style, getting bullied before founding Snapchat, and the harshest day of his CEO journey. Chapters: 00:00 Intro 02:29 The Dots That Got You Here 03:33 Did You Feel Like You Fitted In? 03:46 When Did Computers First Come In? 05:02 Things Aren't as Complicated as They Seem 05:28 You Got Bullied 06:09 What Were You Like as a Kid 07:33 Why CEOs Don't Do Many Podcasts 08:55 Why Did You Choose Product Design? 10:30 Your Class in Entrepreneurship 11:00 Key Lesson From Entrepreneurship Class 12:02 Big Ambitions 13:26 Entrepreneurship in Europe 16:00 Your First Failure 18:00 How to Know When to Quit 18:50 Why Love & Passion Matter 19:19 Launching Early & Getting Feedback Fast 20:39 How Initial Ideas Can Be Wrong 21:37 How You Started Snapchat 27:03 Customer Feedback to Implement 28:36 Raising Capital 29:46 Investor Feedback 30:17 Building a Social Network Sounds Delusional 31:51 Doubting Snapchat's Success 36:19 Quitting University for Snapchat 37:33 Advice for Young Entrepreneurs 39:27 Are Job Titles Limiting Creativity? 40:34 Hierarchy Issues in Companies 42:22 Innovating at Snapchat 47:59 Importance of Hiring 49:00 Hiring Mistakes to Avoid 51:06 Leadership Traits of a Perfect Hire 52:25 Being Nice vs. Being Kind 53:52 T-Shaped Leadership 56:44 Advice to Younger Evan 59:39 Embedding Company Culture Early 01:01:51 When Company Culture Dilutes 01:03:35 Company Incentives 01:04:25 Worst Early Advice 01:05:47 How Mark Zuckerberg Approached You 01:10:04 Saying No to That Offer 01:13:13 Youngest Billionaire at 25 01:14:19 Managing Romantic Relationships 01:19:23 Ads 01:20:21 Your LinkedIn Bio Joke 01:22:45 Messaging Zuckerberg When They Copied Features 01:26:57 Should Big Tech Monopolies Be Stopped? 01:29:25 Hardest Day When Copied 01:30:30 Leading in Tough Times 01:31:48 Content Moderation Challenges 01:36:28 Why Meta Rolled Back Moderation Policies 01:39:20 Optimism About America 01:40:08 Social Media & Your Kids 01:42:51 Is TikTok's Ban Good for Snapchat? 01:46:07 Snapchat Going Public 01:48:28 Killing Projects You Loved 01:50:15 How Do You Prioritize? 01:52:23 Ray-Ban Spectacles Launch Reaction 01:53:37 Will Kids Learn From AI? 01:56:34 Tradeoffs With AI 01:58:22 Ads 02:00:35 Snapchat in 2025 02:02:14 Importance of Counsels at Work 02:05:34 When to Listen to Your Team 02:06:22 Work-From-Home Policies 02:08:42 Principles of a Successful Entrepreneur 02:10:18 Managing Stress 02:13:10 Worst Days of Snapchat 02:13:50 Do You Have Imposter Syndrome? 02:15:08 Would You Start Another Tech Company? 02:17:23 Hardest Thing You've Overcome 02:18:17 Self-Awareness 02:20:45 Do You Feel Impatient as a Leader? 02:21:35 What Would Your Team Say About You? 02:22:12 What Are You Really Good At? 02:26:55 Biggest Question Entrepreneurs Should Ask Follow Evan: Twitter - https://g2ul0.app.link/hnvyN8X8SRb More about Snap's new glasses - https://g2ul0.app.link/GDzqC6XeTRb Watch on YouTube: https://g2ul0.app.link/DOACEpisodes Get My Book & Cards: 'The 33 Laws Of Business & Life' - https://g2ul0.app.link/DOACBook Conversation Cards: https://g2ul0.app.link/f31dsUttKKb Follow Me: https://g2ul0.app.link/gnGqL4IsKKb Sponsors: LinkedIn Ads - https://www.linkedin.com/DIARY Perfect Ted - https://www.perfectted.com (Code: DIARY40) Learn more about your ad choices. Visit megaphone.fm/adchoices

From a successful career as one of Australia’s most in-demand models to mother of four boys and founder and CEO of Kora Organics (or, as she also calls it, “my baby girl”), Miranda Kerr has charted a fascinating path for herself. On this episode of Something To Talk About, Miranda joins Sarrah for a revealing conversation about her approach to motherhood – and co-parenting with Orlando Bloom and Katy Perry, life at home with her husband, Snap Inc founder Evan Spiegel, their surprising attitude toward screen time for the four young boys they’re raising, and the big move she is contemplating for her skincare empire. Plus, Miranda explains why walking down runways in her underwear is now off-limits: “I’m not in that headspace. I’ll just keep that for my husband.” You can find out more details about Kora Organics new Active Algae Balancing Probiotic Mask here. Miranda Kerr is also the ambassador for Michael Hill. Watch the full episode with Miranda here. Something To Talk About is a podcast by Stellar, hosted by Sarrah Le Marquand Find more from Stellar via Instagram @stellarmag or stellarmag.com.auSee omnystudio.com/listener for privacy information.

In this rare, in-depth conversation, supermodel, Kora Organics founder, and mother of four Miranda Kerr welcomes Sigourney into her LA home to share the personal rituals, love story, and life lessons that have shaped her.Key Moments: • The Love Story: On their very first date, Evan Spiegel fell asleep on Miranda's lap—and somehow, that moment sealed their bond. Today, therapy helps them grow together, not apart. • Faith & Spirituality: How Kundalini yoga, prayer, and daily gratitude keep her grounded amidst the chaos of life. • Loss & Resilience: From losing her first boyfriend at 15 to her grandparents' lifelong love story, Miranda reflects on how grief, love, and deep family connections have shaped her perspective. • Motherhood & Balance: Raising four boys, running a global business, and making space for self-care. • Building Kora Organics: Her mission to create clean, high-performance skincare, inspired by nature and backed by science.Follow Sigourney on ⁠⁠⁠Instagram:https://www.instagram.com/sigourneycanteloTikTok: https://www.tiktok.com/@sigourneycanteloFollow Beauticate on ⁠⁠⁠Instagram⁠⁠⁠ and ⁠Facebook⁠.https://www.instagram.com/beauticate/https://www.facebook.com/beauticate/

On this episode of The Colin and Samir Show, we sit down with Snapchat founder and CEO, Evan Spiegel, for a deep dive into the evolution of social media, the future of technology, and the role of Snapchat in the creator economy. Evan shares his insights on the future of wearables like Spectacles, the TikTok ban, how social media shapes culture and politics, what it takes to build a product that connects people, and more. Learn more about your ad choices. Visit megaphone.fm/adchoices

Evan Spiegel is an American entrepreneur and co-founder of Snap Inc., the parent company of the popular multimedia messaging app Snapchat. The app, launched in 2011, revolutionized social media by introducing disappearing messages and creative visual tools like filters and lenses. Under Spiegel's leadership as CEO, Snap Inc. has grown into a global company with innovative products such as Spectacles and augmented reality technologies. Recognized for his forward-thinking approach, Evan has become one of the youngest billionaires in the world, known for reshaping how people communicate digitally.On this episode, Evan and Mo discussed Snapchat's unique popularity in Saudi Arabia, Augmented Reality, Snapchat's inaugurating their new office in Riyadh and Evan's admiration for the late great Kobe Bryant.

Snap shares moving higher on the back of strong results, CEO Evan Spiegel walks us through the quarter and how it plans to compete in the AI space. Plus, while tech has stolen the headlines, utilities area having a standout year... We'll speak with one of the key players in the areas. And, one portfolio manager makes the case for small caps even in a recession.

Today on the podcast we have Michael Lynton, one of America's leading CEOs. Michael led Sony Entertainment as CEO, overseeing Sony's global entertainment businesses during a period of great success. But it also had its challenges - notably when North Korean hackers released private emails and unreleased films. Michael had previously worked for Time Warner as CEO of AOL Europe, and was  Chairman and CEO of Pearson PLC's Penguin Group.But today our focus is on Michael's role as a mentor. He has been arguably one of the most successful startup mentors of all time, discovering and nurturing a young Evan Spiegel - the founder of Snapchat, now Snap. Michael spotted Evan after Michael's wife contacted Snapchat customer support in a moment of serendipity. From that chance encounter, Michael went on to become chairman of Snap, now one of the world's largest social media platforms. On this episode, you find out from Michael what truly great mentorship looks like, what you should look for in a mentor and how this changes as you scale, and what matters most when becoming a great leader.

Snap AR Platform Lead Sophia Dominguez interviewed Snap co-founders Evan Spiegel and Bobby Murphy at the Snap Lens Fest about AR and the Snap Spectacles, and there was an audience Q&A at the end as well. See more context in the rough transcript below. This is a listener-supported podcast through the Voices of VR Patreon. Music: Fatality

 This bonus episode of Squawk Pod, from our partners at “The Keynote” features a mogul at the forefront of innovation in social media and tech. CEO of Snap Evan Spiegel spoke with Andrew Ross Sorkin at the Game Plan sports business summit hosted by CNBC and Boardroom on September 10th 2024. They discuss social media's integration with sports, the future of augmented reality and what he wishes other social media companies would copy about Snapchat. To listen to other interviews from events check out “The Keynote by CNBC Events” here: https://podcasts.apple.com/us/podcast/the-keynote-by-cnbc-events/id1493248246 For information on upcoming events visit: CNBCevents.com In this episode: Evan Spiegel, @evanspiegel Andrew Ross Sorkin, @andrewrsorkin Katie Kramer, @Kramer_Katie 

Subscribe to Mamamia Instagram is finally doing something about teenagers on its app. But others think this is just parental cop-out. We unpack. Plus, are you terrified of breaking a streak? When does a self-improvement habit become an addiction, and what are ours? We have thoughts.   And, a very famous Australian man is in complete public free-fall. Is it time to look away? We discuss.   What To Listen To Next:  Listen to our latest episode: Emmys, Controversy & Stuck Style Listen: What Elle Macpherson Did Next Listen: Tampons, Tarot & The Rise Of Magical Thinking Connect your subscription to Apple Podcasts  Sign up to the Mamamia Out Loud Newsletter for all our recommendations and behind-the-scenes content in one place.  Want to try our new exercise app? Click here to start a seven-day free trial of MOVE by Mamamia  What to Read:  Read: Ben Affleck's cousin is the worst part of The Secret Lives of Mormon Wives. GET IN TOUCH: Feedback? We're listening. Send us an email at outloud@mamamia.com.au Share your story, feedback, or dilemma! Send us a voice message Join our Facebook group Mamamia Outlouders to talk about the show. Follow us on Instagram @mamamiaoutloud CREDITS: Hosts: Holly Wainwright, Mia Freedman & Jessie Stephens Executive Producer: Ruth Devine Senior Producer: Emeline Gazilas Audio Production: Leah Porges Mamamia acknowledges the Traditional Owners of the Land we have recorded this podcast on, the Gadigal people of the Eora Nation. We pay our respects to their Elders past and present, and extend that respect to all Aboriginal and Torres Strait Islander cultures.Become a Mamamia subscriber: https://www.mamamia.com.au/subscribeSee omnystudio.com/listener for privacy information.

Today, Equalman sits down with 2015's youngest billionaire in the world, Evan Spiegel. Spiegel is the co-founder and CEO of Snap Inc, a technology company that developes and maintains products and services, namely Snapchat and Bitmoji. They discuss communicating responsibly, the essence of Snapchat, fear in technology, and corporate team structure.   5x #1 Bestselling Author and Motivational Speaker Erik Qualman has performed in over 55 countries and reached over 50 million people this past decade. He was voted the 2nd Most Likable Author in the World behind Harry Potter's J.K. Rowling.   Have Erik speak at your conference: eq@equalman.com   Motivational Speaker | Erik Qualman has inspired audiences at FedEx, Chase, ADP, Huawei, Starbucks, Godiva, FBI, Google, and many more on Focus and Digital Leadership.   Learn more at https://equalman.com

The Big Tech Gut Check is a super quick, weekly update on all things social media and Big Tech. Social Media & Big Tech highlights for this week: Why Phones Don't Belong in School (podcast episode here) Meta Advertising Nudify Apps on Facebook and Instagram (update here) Social Media's Role in Crimes Against Kids (with John Pizzuro) Harrison Haynes Was Groomed And Is Speaking out (more here) Evan Spiegel's Recent Announcements (here) Snapchat Sued by New Mexico for Facilitating Child Exploitation (more here) Snapchat Will Send Ads in Private Messages (more here) Check back on Fridays for everything that parents need to know about the platforms our children are spending hours on every day. This episode is sponsored by Bark Technologies. Check out the Bark Phone Check out the Bark Parental Monitoring App for iPhones and Androids (use code SCROLLING2DEATH for 10% off) --- Support this podcast: https://podcasters.spotify.com/pod/show/scrolling2death/support

From the archive: This episode was originally recorded and published in 2021. Our interviews on Entrepreneurs On Fire are meant to be evergreen, and we do our best to confirm that all offers and URL's in these archive episodes are still relevant. Anthony Sarandrea is recognized as one of the top customer generators in the world, specializing in the financial services space and running a team that drove over one million customers in 2020. Today, he runs a profitable portfolio of websites ranging from commerce to content blogs that combined reach millions of buyers every month and drive 4k inbound calls per day off of internal websites as an affiliate. He is consistently featured as one of the top Under 30 entrepreneurs and was recently featured alongside Snapchat's founder Evan Spiegel as one of the Entrepreneurs Changing the World. Top 3 Value Bombs 1. You need to have a sickening, delusional attitude to run at things that are uncomfortable to those around you. 2. Someone is exponentially learning where they can improve and consistently seeking those things out both professionally and personally. If they take action on it, they're going to reach higher heights than you ever will. 3. The idea of failing fast over and over is so necessary with how fast the world moves today. You have to run to stand still nowadays. Follow Anthony on Instagram - Anthony's Instagram Sponsor HubSpot Grow better, faster with HubSpot's all-in-one intuitive customer platform. Visit HubSpot.com to learn more

From the archive: This episode was originally recorded and published in 2021. Our interviews on Entrepreneurs On Fire are meant to be evergreen, and we do our best to confirm that all offers and URL's in these archive episodes are still relevant. Anthony Sarandrea is recognized as one of the top customer generators in the world, specializing in the financial services space and running a team that drove over one million customers in 2020. Today, he runs a profitable portfolio of websites ranging from commerce to content blogs that combined reach millions of buyers every month and drive 4k inbound calls per day off of internal websites as an affiliate. He is consistently featured as one of the top Under 30 entrepreneurs and was recently featured alongside Snapchat's founder Evan Spiegel as one of the Entrepreneurs Changing the World. Top 3 Value Bombs 1. You need to have a sickening, delusional attitude to run at things that are uncomfortable to those around you. 2. Someone is exponentially learning where they can improve and consistently seeking those things out both professionally and personally. If they take action on it, they're going to reach higher heights than you ever will. 3. The idea of failing fast over and over is so necessary with how fast the world moves today. You have to run to stand still nowadays. Follow Anthony on Instagram - Anthony's Instagram Sponsor HubSpot Grow better, faster with HubSpot's all-in-one intuitive customer platform. Visit HubSpot.com to learn more

Imran Khan is the OG of IPOs having taken some of the biggest companies public including Alibaba, Snap, Box, Weibo and more. Today, Imran is the founder and Chief Investment Officer of Proem Asset Management. Prior to co-founding Proem, Imran served as Snap Inc.'s Chief Strategy Officer. Under his leadership, Snap's annual revenue run rate increased to $1.6 billion from zero in less than four years. Previously, Imran was a Managing Director and Head of Global Internet Investment Banking at Credit Suisse where he advised on more than $45 billion-worth of Internet M&A and financing transactions. In Today's Episode with Imran Khan We Discuss: 1. The IPO Market: When Does it Open: How does Imran assess the state of the IPO market today? Can companies really go out with $100-$200M in revenue? Will we see revenue multiples reflate? Can venture continue as an asset class if they do not? When does Imran expect the IPO market to really open? 2. Is M&A F******: How does Imran assess the state of the M&A market today? How do founders need to change how they think about M&A? Why are they to blame for the lack of M&A activity we have today? To what extent can we blame Lina Khan for the lack of M&A? Why would a company go do an M&A process today when it is unlikely to be approved by the SEC? Why does Imran believe in the case of Wiz, it was a mistake for the company not to do the M&A? 3. AI's $600BN Question: Capex Spend: How does Imran analyse the insane capex spend we are seeing from Meta, Google and Amazon? How does Zuck not having his cash cow as the cloud business change how he can act? How does this compare to Google's capex spend 20 years ago? What can we learn from that? 4. Going Public: The Process, The Players and Jack Ma & Jamie Dimon: What is the literal process to take a company public? Who sets the price? What do large institutions want in companies going public? What are some of Imran's biggest lessons from taking Snap and Alibaba public? What are some of Imran's biggest lessons from Jack Ma, Jamie Dimon and Evan Spiegel?  

How does someone land their dream job… right out of college? How does someone position themselves to create some of the biggest breakout products in the tech industry? How does someone walk alongside some of the most successful people in the world?  Well… that's what we're talking about in THIS episode… and you might be surprised to find that someone who's done just that will be quick to tell you that he wasn't motivated by ambition… but instead… by enthusiasm and passion. That's right. Tom Conrad is joining us!  Tom is living a true DREAM THINK DO life!  He dreamed of working for Apple as a kid… and pursued that goal.  While going to the University of Michigan… he secured an internship with Apple… and after a bold conversation… he wound up being recruited by Apple after graduating. In addition to his experience at Apple… Tom's been a vital part of some significant successes. For example… he was a co-creator and Chief Technology officer and Executive Vice President of Product at Pandora… which he helped take from zero to 80 million users. He was the VP of Product for Snap… where he worked side by side with Evan Spiegel. (If you don't know… Evan became the youngest billionaire in the world in 2015.) Tom's now the CEO for Zero… a metabolic health app which is on a mission to extend the lifespan and the health span of the human race.  He's helped the app to grow to almost 14 million users AND… sidebar… they have a 4.8 in the Apple store… with over 435,000 ratings… which is wildly impressive! Now… along with these big wins… Tom is also quick to point to some setbacks along the way.  And we'll talk about those as well… and what Tom learned from them!  It's a great conversation… so let's get to it! WHERE TO FIND TOM: LinkedIN: https://www.linkedin.com/in/tomconrad/ Instagram: https://www.instagram.com/tconrad Zero on Instagram: https://www.instagram.com/zerolongevity A recent article Tom wrote on Medium: Click here EncouragerCON 2024 Mitch mentioned EncouragerCON to kick off this episode. EncouragerCON is our 2.5 day conference for “Encouragers.”  If you are a new or experienced Coach, Speaker or Content Creator… we want YOU there!   Click here to find out more about this incredible event! We'll introduce you to the biggest opportunities in coaching and speaking that are happening RIGHT NOW! Along with strategies that you can use… immediately! With Encourager-CON you'll be surrounded by your fellow Encouragers AND it will be 2.5 days of proven concepts, innovative new approaches, powerful stories and straight-up fun… so YOU can REACH more people… create more REVENUE and find ways to REST as you do! And… remember… use the coupon code: DTD to get a VERY special discount!  It's time sensitive though… so the earlier you use it… the bigger the discount!  Don't miss out!  JOIN US! Check out Mitch's OTHER PODCAST: ENCOURAGING THE ENCOURAGERS You can now check out Mitch's new podcast called “ENCOURAGING THE ENCOURAGERS” anywhere you listen to podcasts.   It's specifically designed for coaches, speakers and content creators and provides quick doses of inspiration, strategy AND… of course… encouragement! Find it on Apple Podcasts:  Click here Find it on Spotify: Click here Find it on Anchor: Click here Find it on Google: Click here LET'S HEAR FROM YOU! Tom's living the DREAM THINK DO life! He's stayed open and he's been willing to experiment and learn as he goes… and it's made all the difference!  It was incredible to learn from his journey! Okay… let's get to it!   You KNOW I'm going to ask… because I am ALWAYS curious about YOU and what YOU heard.   What's something that resonated with you?   More importantly… what's something you're going to DO (big or small) as a result? I want to hear from YOU!   Leave a comment and let me know. And hey… keep bringing YOUR awesome!!! Mitch Minute By Minute: 0:31 Mitch introduces Tom Conrad's impressive career in the tech industry, mentioning his roles at Apple, Pandora, and Snap. 1:29 Overview of Tom's journey, from working at Apple to his involvement in creating Pandora and becoming CEO of Zero. 2:21 How enthusiasm and passion, not ambition, can guide your career and open doors of opportunity. 3:00 How to save at EncouragerCon with a special discount for just Dream Think Do listeners! 4:00 Tom reflects on his childhood dream of working at Apple and how it became a reality. 5:15 Discussion on Tom's internship at Apple and the bold move he made to secure his dream job. 7:06 Tom talks about the impact of that bold conversation and how it led to a job offer. 8:09 Mitch and Tom discuss the importance of taking risks and having bold conversations to achieve career goals. 10:00 Tom shares his early career experiences at Micro Center, which helped build his confidence. 12:00 Tom emphasizes the role of passion over ambition in guiding his career path. 13:00 Tom discusses how serendipity and being in the right place at the right time contributed to his success. 15:00 Mitch highlights Tom's success in building Pandora from the ground up to 80 million users. 18:00 Tom shares the story of joining Savage Beast (later Pandora) after a bold conversation with the CEO. 20:00 Tom reflects on the setbacks he faced during his career and what he learned from those experiences. 22:00 Discussion about Tom's work at Pandora and the importance of creating a simple user experience with cutting-edge algorithms. 24:00 Tom shares his journey of learning from failures, like his experience with Quibi, and how he turned them into lessons. 28:00 Tom and Mitch discuss the importance of perseverance even when faced with setbacks and challenges. 30:00 Tom talks about his current role as CEO of Zero and his mission to improve people's health and longevity. 32:00 Mitch's Minute: Reflecting on the importance of staying passionate, taking bold steps, and learning from both successes and failures.

Instant analysis of Snap ($SNAP) Q2 earnings, as we hear from CEO Evan Spiegel. More than “beat” or “miss” –the Drill Down Earnings with Futurum Group chief market strategist Cory Johnson has the business stories behind stocks on the move.    https://x.com/corytv #Snap #Earnings @Snap $SNAP #Technology #Software #CloudComputing #Chips #AI #ArtificialIntelligence #Semiconductors #Stocks #Trading #Business @DrillDownPod Learn more about your ad choices. Visit megaphone.fm/adchoices

This year, the Olympics have reached gender parity, according to the International Olympic Committee. Venture capitalist Alexis Ohanian, 776 founder and Reddit co-founder and former executive chairman, discusses his long-held belief in the business opportunity of women's sports, as well as Athlos, his new womens-only track meet with the sport's largest prize purse. He says, social media is an important ingredient in the rise of female athlete popularity. For Snap CEO Evan Spiegel, social media is key for the Olympics, too; Snap's augmented reality lens is available through the official Olympics app, for fans in Paris for the Games. Spiegel discusses prospects for the LA 2028 Olympics, and his vision for a future of lenses, instead of screens. Tune into the Olympics on NBC for all the Games!Alexis Ohanian - 4:26Evan Spiegel - 17:06In this episode:Alexis Ohanian, @alexisohanianEvan Spiegel, @evanspiegelBecky Quick, @BeckyQuickJoe Kernen, @JoeSquawkAndrew Ross Sorkin,@andrewrsorkinCameron Costa, @CameronCostaNY

Is today's bounce back for real? Eric Johnston from Cantor Fitzgerald, Courtney Garcia of Payne Capital and Brian Levitt of Invesco give their expert forecasts. Plus, Big Technology's Alex Kantrowitz breaks down the big move in Alphabet post-earnings. And, Julia Boorstin tells us what's behind Snap's surge – and brings us key comments from CEO Evan Spiegel. 

A rapid-fire, insightful look at breaking earnings from Snap ($SNAP) as we hear from CEO Evan Spiegel. More than “beat” or “miss” –the Drill Down Earnings with Futurum Group chief market strategist Cory Johnson has the business stories behind stocks on the move.    https://x.com/corytv #Snap #Earnings @Snap $SNAP #Technology #Software #CloudComputing #Chips #AI #ArtificialIntelligence #Semiconductors #Stocks #Trading #Business @DrillDownPod Learn more about your ad choices. Visit megaphone.fm/adchoices

Snapchat got 0 downloads the day it launched. 6 months in, it had only 127 users. Today Snapchat is an $18B company with 400 million daily active users. Evan Spiegel noticed what even Zuck missed: daily communication is meant to be ephemeral, not recorded for all time.In this episode, we dive deep into how Snapchat went from idea to product-market fit. Our guest is Jeremy Liew, a Partner at Lightspeed and the first investor in Snapchat. He led Lightspeed's seed round in 2012 at a $5M valuation (!!). He shares his four-part B2C framework that helped him understand why Evan and Snap were special before anyone else. If you want to understand why Snapchat took off when so many other consumer startups fail to do so, check this episode out. 

A detailed look at the breaking earnings from Snap (SNAP), with a look at the business story behind these earnings and we hear from CEO Evan Spiegel. https://linktr.ee/drilldownpod The Drill Down Earnings with Futurum Group chief market strategist Cory Johnson offers a quick look at the important takeaways from technology company earnings. More than “beat” or “miss” – it's the business stories behind stocks on the move.  The Drill Down Earnings is a production of Six Five Media and Futurum Group, a leading global technology advisory, media and research firm. Six Five Media's platform spans across multiple OTT and VOD channels that have surpassed 9 million views and over 421 million digital and social media impressions. Learn more about your ad choices. Visit megaphone.fm/adchoices

Snap Inc. recently shared insights into its financial health and strategic positioning during an earnings call held on Tuesday February 6th, 2024. CEO Evan Spiegel took the lead communicating the transformative changes the company has undergone over the past year. Pivoting to a more customer-centric approach, Snap Inc. has heavily invested in its Machine Learning (ML) platform - an effort aimed at enhanced performance for advertising partners and improved relevance and ranking. The revenue growth of approximately 5% year-over-year signaled an upswing in the company's income-generating potential, as it continues to shore up its market position. This progress is noteworthy as it suggests the company's consistent strides in solidifying its profitability. Snap Inc.'s reliance on ML as integral to their strategy reflects their focus on enabling better and more efficient advertising on their platform. The company's increasing reliance on ML technology underscores its continual development efforts aimed at delivering substantial value to advertisers. Despite the progression, Snap Inc. was candid in acknowledging the hurdles standing in their way. The company conveyed a commitment to delivering a seamless content experience across its platform, aiming to drive higher user engagement and promote frequent app usage. Targeting growth potential, Snap Inc. revealed plans to expand its user base, particularly in regions that could be lucrative revenue sources. The company's sights are set on Europe and North America, according to Spiegel, signifying an aspiration to fuel further growth while raising its financial output. The appeal of the platform is evident in the rising number of monthly and daily users, paired with significant growth in total viewing time and viewer count. This combination reflects growing user engagement, contributing to the platform's overall popularity. Looking forward, Snap Inc. seems armed with a clear vision for growth and a robust investment plan. The company's forward-focused strategy, coupled with an innovation mindset, mean it is well-positioned to deal with any possible challenges. Using their current endeavours as a stepping stone, combined with their unwavering dedication to innovation, Snap Inc.'s journey ahead promises to be an exciting one, hinging on a strong blend of ambition and realism. SNAP Company info: https://finance.yahoo.com/quote/SNAP/profile For more PSFK research : www.psfk.com  This email has been published and shared for the purpose of business research and is not intended as investment advice.

The Rich Zeoli Show- Full Episode (02/01/2024): 3:05pm- On Wednesday, Meta CEO Mark Zuckerberg testified before the Senate Judiciary Committee. During Sen. Lindsey Graham's (R-SC) opening statement, he accused Zuckerberg of having blood on his hands—emphatically stating “you have a product that is killing people” as those in attendance applauded. Zuckerberg was also notably grilled by Sen. Ted Cruz (R-TX) and Sen. Josh Hawley (R-MO). Could strict regulations on social media be coming via new legislation? Though there is clearly bipartisan support for legislation to upend Section 230, government should not be in the business of regulating speech online—it ultimately leads to the censorship of American citizens expressing opinions contrary to mainstream narratives. 3:10pm- Meta CEO Mark Zuckerberg publicly apologized to families negatively impacted by social media after being implored by Sen. Josh Hawley (R-MO) to take accountability. Hawley, who notably wrote the “Tyranny of Big Tech” in 2021, has asserted that social media is one of the biggest threats to America. 3:15pm- A newly released Quinnipiac poll shows President Joe Biden with a 6-point national lead over Republican presidential candidate Donald Trump. Though, as Rich notes, the polling results may not be as problematic for Trump as the media is making it seem. First, the poll relied on “registered” voters, not “likely” voters. Plus, it's a national poll and doesn't consider state polling. According to a new Bloomberg News/Morning poll, Trump leads Biden in a hypothetical 2020 rematch by 3 to 10 points in Wisconsin, Pennsylvania, North Carolina, Nevada, Michigan, Georgia, and Arizona. Trump's projected lead expands even further when considering the third-party candidacies of Robert Kennedy Jr., Jill Stein, and Colonel West. 3:30pm- Heather Knight of The New York Times writes: “Fifteen months after city officials were ready to throw a party in the Noe Valley Town Square to celebrate funding for a tiny bathroom with a toilet and sink, nothing but mulch remains in its place. The toilet project broke down the minute taxpayers realized the city was planning an event to celebrate $1.7 million in state funds that local politicians had secured for the lone 150-square-foot structure. That's enough to purchase a single-family home in San Francisco—with multiple bathrooms. Even more confounding was the explanation that the tiny bathroom would take two to three years to install because of the city's labyrinthine permitting and building process. City leaders quickly canceled their potty party, and Gov. Gavin Newsom of California took back the funds.” You can read the full story about San Francisco's $1.7 million toilet here: https://www.nytimes.com/2024/01/24/us/san-francisco-toilet.html 3:45pm- Bud-Light has announced a partnership with comedian Shane Gillis. Will the Gillis affiliation be enough for Bud-Light to bounce back from the criticism it received after working with transgender social media influencer Dylan Mulvaney. 4:05pm- Robby Soave of Reason writes: “There is no pastime more beloved by Congress than beating up on social media executives. On Wednesday, members of the Senate Judiciary Committee engaged in yet another round of fact-free histrionics as they thunderously denounced four tech CEOs—Meta's Mark Zuckerberg, X's Linda Yaccarino, Snapchat's Evan Spiegel, and Discord's Jason Citron—for­ a litany of allegedly unsafe business practices… Many of the Senate's anti-tech crusaders were present, including Republican Sens. Lindsey Graham (SC), Ted Cruz (TX), and Josh Hawley (MO), and Democratic Sens. Dick Durbin (IL), Amy Klobuchar (MN), and Richard Blumenthal (CT). Sen. Elizabeth Warren (MA) wasn't there, though she received several favorable shout-outs from the Republicans. Indeed, both sides of the political aisle were exceedingly pleased with themselves for acting in bipartisan fashion to wildly accuse four business leaders of complicity in despicable crimes against children… In order to obtain this control, senators from both parties have sponsored legislation to repeal or reform Section 230, the federal statute that protects internet companies from some liability. Section 230 was a frequent punching bag at the Wednesday hearing.” You can read the full article here: https://reason.com/2024/02/01/mark-zuckerberg-senate-hearing-graham-facebook/ 4:15pm- While appearing on CNN, Senator Dick Durbin (D-IL) said: “I'm not going to protect Section 230 at the expense of children…if 230 has to go, it has to go.” Section 230 of the Communications Decency Act notably shields social media companies from liability for speech posted to their platforms. 4:35pm- David Propper of The New York Post writes: “A Montana family claims they lost custody of their 14-year-old child after opposing her interest in changing genders — and while the governor's office defended the move, it stressed to The Post that the state does not remove minors to provide gender transition services. The state's Child and Family Services (CFS) reportedly took custody of the teen from her father, Todd Kolstad, and stepmother, Krista, this month, leading the parents to speak out about how the action has ‘destroyed' their family and ‘trampled' their rights.” You can read the full report here: https://nypost.com/2024/01/30/news/montana-parents-lose-custody-of-daughter-after-opposing-transition-report/ 4:50pm- Rich opens the phone lines and gets flooded with off-topic calls—Matt is reprimanded. 5:05pm- On Wednesday, Meta CEO Mark Zuckerberg testified before the Senate Judiciary Committee. During Sen. Lindsey Graham's (R-SC) opening statement, he accused Zuckerberg of having blood on his hands—emphatically stating “you have a product that is killing people” as those in attendance applauded. Zuckerberg was also notably grilled by Sen. Ted Cruz (R-TX) and Sen. Josh Hawley (R-MO). Could strict regulations on social media be coming via new legislation? Though there is clearly bipartisan support for legislation to upend Section 230, government should not be in the business of regulating speech online—it ultimately leads to the censorship of American citizens expressing opinions contrary to mainstream narratives. 5:15pm- While speaking from the House floor, Congresswoman Pramila Jayapal (D-WA) voiced her disagreement with proposed legislation that would allow for the deportation of undocumented migrants convicted of driving while intoxicated (DWI). She also implored society to stop referring to migrants who enter the U.S. unlawfully as “illegals.” 5:20pm- In audio leaked from The San Francisco Standard, Governor Gavin Newsom (D-CA) can be heard retelling a story about how he witnessed a theft while at Target, and how he reprimanded a worker for suggesting California isn't tough on crime. 5:30pm- Teri Hatcher, who was a “Bond-girl” in the film Tomorrow Never Dies, says she is officially done with online dating and is content with being single. 5:45pm- In his latest piece for The New York Post, George Washington University Law Professor Jonathan Turley writes: “Hunter Biden is comparable to children in Japanese internment camps, to undocumented immigrants, to the murdered descendants of the Tsar. At least that's what he argues in a new court filing in his federal gun case, which presents Hunter as one of the most tragic figures since the fall of Troy. Literally. In a brief that borders on delusional, Biden's lawyers say the son of the president who burned through millions from influence peddling is comparable to all those unfortunate and destitute souls.” You can read the full article here: https://nypost.com/2024/01/31/opinion/hunter-biden-compares-self-to-a-romanov-a-migrant-child-and-a-greek-tragedy-in-delusional-court-filing/ 6:05pm- Rich is busy hosting a stand-up comedy show at Club 360 at Parx Casino tonight—so, Mike Opelka hosts hour 4 of the show! 6:10pm- Tomorrow is Groundhog Day! Will you be in Gobbler's Knob partying? Interestingly, PETA is calling for replacing the groundhog with a simple coin toss to determine whether there will be six more weeks of winter. According to calculations, since 1887, Punxsutawney Phil has accurately predicted the winter weather just 39% of the time. 6:35pm- Tommy Christopher of Mediaite writes: “Fulton County District Attorney Fani Willis is standing firm in the face of efforts to get her to step down from the blockbuster election crimes case against former President Donald Trump and 18 co-defendants. Trump and others have demanded DA Willis be removed from the 34-count felony election crimes case on the basis of allegations made in a court filing by one of Trump's co-defendants. Willis is accused of an “improper” relationship with special prosecutor Nathan Wade, whom she hired as part of the Trump election crimes team. But according to a CNN exclusive by Zachary Cohen, Willis has decided she's not going anywhere.” You can read more here: https://www.mediaite.com/news/cnn-sources-say-trump-election-crimes-prosecutor-fani-willis-will-not-step-down-from-blockbuster-rico-case/ 6:40pm- On Thursday, U.S. Capitol Police announced they will not charge a former Senate staffer who allegedly had sex in a Congressional hearing room last year. The incident reportedly occurred where Sen. Amy Klobuchar (D-MN) sits during Senate Judiciary hearings. 

Will Wu is the CTO @ Match Group, the owner and operator of the largest global portfolio of popular online dating services including Tinder, Match.com, OkCupid, and Hinge to name a few. Prior to Match, Will was VP of Product at Snap Inc. As the 35th employee, Will spearheaded the creation of Snapchat's “Discover” content platform. He also led the creation and growth of the “Chat” messaging feature, which today is a primary Snapchat engagement driver that connects hundreds of millions of people each day. In Today's Episode with Will Wu We Discuss: 1. The Journey to Snap CPO: How did Evan make his way into the world of product and come to meet Evan Spiegel? What are 1-2 of his biggest takeaways from his time at Snap? What does Will know now that he wishes he had known when he started in product? 2. How to Hire Product Teams: How does Will structure the interview process for new product hires? What are the most telling questions of a candidate's product skills in hiring? What case studies and tests does Will do to assess a candidate? What are 1-2 of Will's biggest hiring mistakes in product? 3. How to Do Product Reviews Effectively: What are Will's biggest lessons on what it takes to do product reviews well? What are the biggest mistakes product leaders make in product reviews? How can teams drive focus in product reviews? What works? What does not? 4. Product: Art or Science? How does Will balance between gut/intuition and data in product decisions? Is simple always better in product design? What is human-centered design? How does it impact how Will approaches product?

The Rich Zeoli Show- Hour 2: Robby Soave of Reason writes: “There is no pastime more beloved by Congress than beating up on social media executives. On Wednesday, members of the Senate Judiciary Committee engaged in yet another round of fact-free histrionics as they thunderously denounced four tech CEOs—Meta's Mark Zuckerberg, X's Linda Yaccarino, Snapchat's Evan Spiegel, and Discord's Jason Citron—for­ a litany of allegedly unsafe business practices… Many of the Senate's anti-tech crusaders were present, including Republican Sens. Lindsey Graham (SC), Ted Cruz (TX), and Josh Hawley (MO), and Democratic Sens. Dick Durbin (IL), Amy Klobuchar (MN), and Richard Blumenthal (CT). Sen. Elizabeth Warren (MA) wasn't there, though she received several favorable shout-outs from the Republicans. Indeed, both sides of the political aisle were exceedingly pleased with themselves for acting in bipartisan fashion to wildly accuse four business leaders of complicity in despicable crimes against children… In order to obtain this control, senators from both parties have sponsored legislation to repeal or reform Section 230, the federal statute that protects internet companies from some liability. Section 230 was a frequent punching bag at the Wednesday hearing.” You can read the full article here: https://reason.com/2024/02/01/mark-zuckerberg-senate-hearing-graham-facebook/ While appearing on CNN, Senator Dick Durbin (D-IL) said: “I'm not going to protect Section 230 at the expense of children…if 230 has to go, it has to go.” Section 230 of the Communications Decency Act notably shields social media companies from liability for speech posted to their platforms. David Propper of The New York Post writes: “A Montana family claims they lost custody of their 14-year-old child after opposing her interest in changing genders — and while the governor's office defended the move, it stressed to The Post that the state does not remove minors to provide gender transition services. The state's Child and Family Services (CFS) reportedly took custody of the teen from her father, Todd Kolstad, and stepmother, Krista, this month, leading the parents to speak out about how the action has ‘destroyed' their family and ‘trampled' their rights.” You can read the full report here: https://nypost.com/2024/01/30/news/montana-parents-lose-custody-of-daughter-after-opposing-transition-report/ Rich opens the phone lines and gets flooded with off-topic calls—Matt is reprimanded.

¿El Cártel de Sinaloa financió la campaña presidencial de AMLO en el 2006? Esa es la hipótesis de tres investigaciones que se publicaron simultáneamente el martes en distintos medios internacionales y que se basan en un expediente titulado “Operación Polanco” elaborado por la DEA entre 2010 y 2011. Uno de los reportajes publicados fue firmado por la periodista mexicana Anabel Hernández en la agencia de noticias DW. Ella argumenta que el gobierno estadounidense “tiene pruebas sólidas” para concluir que el Cártel de Sinaloa entregó entre 2 y 4 millones de dólares a personas cercanas a López Obrador para ayudar en la campaña de 2006 del hoy presidente de México. Con pequeñas diferencias, se publicó la misma historia en InSight Crime, y por el dos veces ganador del Pulitzer, Tim Golden, quien firmó su artículo en el prestigioso medio independiente ProPublica. Los CEO's de las principales compañías de big tech enfrentaron un intenso interrogatorio en el Congreso de Estados Unidos sobre la explotación sexual infantil en redes sociales. Durante cuatro horas, Mark Zuckerberg de Meta, Linda Yaccarino de X, Shou Zi Chew de Tiktok, Evan Spiegel de Snapchat y Jason Citron de Discord, escucharon preguntas de los legisladores. El senador republicano Lindsey Graham abrió la sesión con una fuerte declaración, señalando que Zuckerberg y las demás compañías presentes tienen sangre en sus manos por tener un producto que está matando a la gente. Otro momento impactante fue cuando el ejecutivo de Meta se dirigió a los padres cuyos hijos se suicidaron tras ser víctimas de abuso en línea, y les pidió disculpas. Además… A pocos días de haber reabierto, una jueza ordenó la suspensión provisional de las corridas de toros en la Plaza México; una granada de mano fue hallada dentro de la Torre de Pemex en la CDMX; la Cámara de Representantes, con mayoría republicana, aprobó los primeros pasos para un “impeachment” en contra de Alejandro Mayorkas, secretario de Seguridad Nacional; y Universal Music Group retiró todo su catálogo musical, que incluye a artistas como Taylor Swift, Rosalía y Harry Styles, de Tiktok.Y para #ElVasoMedioLleno…Si tienes perrijos, gatijos, o cualquier mascot-ijo, sabes que las visitas al veterinario pueden ser un mega golpe a tu cartera…Sin embargo, y por decreto oficial, se deberán establecer clínicas veterinarias públicas en todo México.Para enterarte de más noticias como estas, síguenos en nuestras redes sociales. Estamos en todas las plataformas como @telokwento. Hosted on Acast. See acast.com/privacy for more information.

This Day in Legal History: The Passing of the 13th AmendmentOn January 31, 1865, a pivotal moment in American legal history unfolded as Congress passed the 13th Amendment to the Constitution, marking a significant turning point in the nation's journey towards equality and justice. This landmark amendment, which formally abolished slavery in the United States, came as a culmination of years of struggle and civil war, reflecting a profound shift in the national consciousness. Its passage symbolized not just the end of an inhumane practice, but also the beginning of a new era of legal and social reform.The 13th Amendment's journey through Congress was fraught with political challenges, showcasing the deep divisions within the country at the time. It was an extension of President Abraham Lincoln's Emancipation Proclamation of 1863, which had declared slaves in Confederate states to be free. However, the Proclamation itself did not end slavery nationwide, which necessitated a constitutional amendment.The Amendment's language was clear and unequivocal: "Neither slavery nor involuntary servitude, except as a punishment for crime whereof the party shall have been duly convicted, shall exist within the United States, or any place subject to their jurisdiction." This wording ensured that slavery was not merely suspended or mitigated but utterly dismantled in a legal sense.The passage of the 13th Amendment was a complex legal achievement, requiring a two-thirds majority in both the House of Representatives and the Senate, followed by ratification by three-fourths of the states. Its adoption signified a legal recognition of the inalienable rights of a significant portion of the American population, who had been denied freedom and dignity for centuries.Importantly, the 13th Amendment laid the groundwork for further advancements in civil rights. It was followed by the 14th and 15th Amendments, which granted citizenship and voting rights to former slaves, respectively. These Reconstruction Amendments collectively aimed to redefine the landscape of American civil liberties and the legal status of African Americans.In retrospect, the passage of the 13th Amendment on January 31, 1865, stands as a testament to the enduring struggle for human rights and the ongoing evolution of legal principles in the United States. It reminds us that legal frameworks are not static but are capable of transformation, often in response to the demands of justice and equality.In a landmark decision, Delaware Chancery Court Chief Judge Kathaleen St. J. McCormick ruled against Elon Musk's $55 billion compensation package from Tesla, which had been challenged by a Tesla investor as excessive and inadequately justified. This ruling, coming after about a year of deliberation, highlighted the extraordinary scale of the pay deal, noting it was 250 times larger than that of median CEO peers and over 33 times greater than Musk's 2012 compensation, calling it "an unfathomable sum" and "historically unprecedented."The judge criticized the process Tesla used to approve the package, pointing out conflicts of interest among board members. These members, including Tesla's former General Counsel and friends of Musk, were deemed "beholden" to him, leading to a lack of meaningful negotiation. This raised questions about the fairness and necessity of the compensation plan, especially given Musk's significant ownership stake in Tesla and his stated commitment to the company's success.Furthermore, McCormick scrutinized Musk's motivations, highlighting his intention to use the compensation to fund his Mars colonization ambitions through SpaceX. Musk views this endeavor as a moral obligation and a means to protect humanity from potential threats posed by artificial intelligence. However, the judge questioned the necessity of such a large compensation package for retaining Musk and achieving Tesla's goals.The judge's decision also delves into the concept of Musk's control over Tesla, referencing cultural touchstones like Star Trek and Shakespeare's Henry V to illustrate the extent of his influence. She concluded that Musk's control and the cooperative nature of the board rendered the process leading to his pay deal "deeply flawed."In her closing remarks, Judge McCormick sympathized with Musk's legal team for their challenging task of defending the fairness of the largest potential compensation plan in public market history. Ultimately, she likened the flawed justification of Musk's pay package to a defective car design, requiring a "recall" and granting the investor's request for rescission.Musk Judge Says ‘Unfathomable' Deal Made Tesla CEO Overpaid (1)Judge voids Elon Musk's 'unfathomable' $56 billion Tesla pay package | ReutersA Republican-led panel has approved plans to impeach Homeland Security Secretary Alejandro Mayorkas, setting the stage for a historic House vote that could make Mayorkas the first Cabinet secretary impeached in nearly 150 years. The decision, advanced 18-15 along party lines by the Homeland Security Committee, is seen as the GOP's most significant political action against President Joe Biden's administration, especially with border security being a critical issue in the upcoming 2024 presidential election.Republicans, led by Committee Chairman Mark Green, accuse Mayorkas of failing to enforce U.S. immigration laws and compromising public trust, particularly in handling the record-high migrant encounters at the U.S.-Mexico border. Despite this, the effort is expected to fail in the Senate, even with some Republican senators expressing concerns that targeting Mayorkas won't address border problems.Democrats counter these accusations, arguing that the impeachment proceedings are a retaliatory measure and that Mayorkas' actions do not meet the constitutional standard for "high crimes and misdemeanors." The markup session witnessed heated exchanges and procedural objections, reflecting deep partisan divides.Meanwhile, a group of Senate Republicans is working on a bipartisan deal to update immigration laws, contrasting with the House GOP's impeachment bid. This Senate effort, already criticized by leading House Republicans, proposes changes like narrowing asylum access and granting the president broader powers in immigration matters.Mayorkas has defended his record, emphasizing efforts to enforce border policies while maintaining a "tough but humane" approach. His response was criticized by Green as lacking seriousness regarding his responsibilities. The move to impeach Mayorkas has gained momentum rapidly over the past month, with House Speaker Mike Johnson pledging a swift floor vote and GOP leaders actively whipping votes for it.GOP Barrels Toward Impeaching Mayorkas as Democrats Cry Foul (1)Republican US House panel advances impeachment charges against border chief | ReutersAt a U.S. Senate hearing, leaders of major social media platforms, including Meta Platforms Inc., X, Snap Inc., Discord Inc., and TikTok, faced intense scrutiny from lawmakers regarding child online safety. The Senate Judiciary Committee, chaired by Senator Dick Durbin, called these executives to Washington to address concerns over the spread of child sexual abuse material online and the impact of social media on young people's mental health. The hearing began with powerful testimonies from victims of online sexual exploitation on platforms like Facebook, Instagram, and Discord.Senator Lindsey Graham criticized Meta CEO Mark Zuckerberg, accusing him of having "blood on his hands" due to a case of child sexual exploitation linked to his platforms. The hearing aimed to propel legislation targeting online child sexual exploitation, with lawmakers from both parties expressing frustration over the tech industry's slow response to growing accusations. These accusations include allowing underage users on their sites and ignoring the potential harms to teens' mental health.Zuckerberg, facing Congress again, pledged Meta's cooperation in making platforms safer for teenagers, highlighting the company's efforts in deploying tools like parental controls and privacy setting reviews. However, he faced tough questions over his 2021 decision to reject expanding teams overseeing child safety. In contrast, CEOs Linda Yaccarino of X, Evan Spiegel of Snap, Jason Citron of Discord, and Shou Chew of TikTok, some of whom were testifying for the first time, planned to defend their companies' practices in detecting and removing harmful content.The hearing underscored the urgent need for legislative action to safeguard children online, amidst ongoing debates over user privacy and the effectiveness of proposed measures. Lawmakers like Senators Marsha Blackburn and Richard Blumenthal championed a bill to legally require tech companies to protect children from harmful content, reflecting a bipartisan push for stricter regulation of social media platforms.Meta, X, TikTok CEOs Face Senate on Protecting Kids Online (1) Get full access to Minimum Competence - Daily Legal News Podcast at www.minimumcomp.com/subscribe

Mark Zuckerberg van Meta, Linda Yaccarino van X, Shou Zi Chew van TikTok, Evan Spiegel van Snap, en Jason Citron van Discord. Het is een indrukwekkende lijst van topmensen die ondervraagd worden door de Amerikaanse Senaat. Die willen meer weten over wat de bedrijven doen om online seksuele uitbuiting van kinderen op hun platforms tegen te gaan. Het is een dossier waar de Commissie voor Justitie al langer mee bezig is. Nu gaat het over het delen van kinderporno, en ook seksuele beelden van kinderen die door AI zijn gegenereerd. De VS zien steeds meer van dat soort beelden op de platforms circuleren. De bedrijven zeggen er veel werk in te steken om het tegen te gaan. Maar de commissie kijkt of ze meer regels kunnen opleggen. Want, zegt de politiek, er kan niet genoeg onderzoek hiernaar worden gedaan. Verder in deze Tech Update: Uber krijgt een boete van 10 miljoen euro van de Nederlandse Autoriteit Persoonsgegevens. Ze maakten het chauffeurs te moeilijk om te achterhalen hoe lang en met wie hun gegevens werden gedeeld. Amazon Alexa moet binnenkort Nederlands gaan praten. Het bedrijf heeft een aantal klanten gemaild met de vraag wat zij belangrijk vinden dat de stem-assistent kan. See omnystudio.com/listener for privacy information.

In this episode, we speak with Priyanka and Shannon, co-founders of Volv, a media company and app that delivers AI-curated and summarized '9-second' articles. We discuss their journey of creating the app and how they successfully pivoted their branding based on user feedback. The importance of reaching out to celebrities and not being afraid to cold approach potential partners is also highlighted. We also touch on their experience as part of the Snapchat incubator group and meeting with Evan Spiegel. Lastly, we announce the upcoming release of podcast merchandise and a giveaway for our listeners. Chapters

Written version: https://www.justgogrind.com/p/evan-spiegel More about the Just Go Grind newsletter: Learn the tactics, strategies, and stories of world-class founders. I spend 20+ hours each week researching founders like Sam Altman, Melanie Perkins, and Patrick Collison, sharing the best insights with you every Sunday. Subscribe to the Just Go Grind newsletter: https://www.justgogrind.com/subscribe Upgrade to Just Go Grind premium and get: 4 founder deep dives each month Audio editions of the newsletter in a private podcast feed Access to a founder community and weekly office hours Upgrade to premium: https://www.justgogrind.com/upgrade

Tom Conrad is the CEO of Zero and on the board of Sonos. He began his career in engineering at Apple, where he helped build key features that remain in iOS today. Tom was previously the VP of Product at Snap and the chief technology officer of Pandora. He also held leadership positions at notable tech flops Pets.com and Quibi, giving him a unique perspective not only on what it takes to build a successful company but also on lessons from failure. In today's conversation, we discuss:• Lessons learned from the infamous failures of Pets.com and Quibi• Lessons learned from the successes of Apple, Pandora, and Snap• Advice on choosing where to work• Understanding the math formula of a business• How to avoid burnout• Why Tom says not everyone needs to be a founder• What he's building now—Brought to you by Coda—Meet the evolution of docs | Jira Product Discovery—Atlassian's new prioritization and roadmapping tool built for product teams | HelpBar by Chameleon—the free in-app universal search solution built for SaaS—Find the transcript at: https://www.lennyspodcast.com/billion-dollar-failures-and-billion-dollar-success-tom-conrad-quibi-pandora-petscom-snap-ze/#transcript—Where to find Tom Conrad:• X: https://twitter.com/tconrad• LinkedIn: https://www.linkedin.com/in/tomconrad/—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) Tom's background(04:40) Landing a gig at Apple(07:41) Pioneering the blinking folder design on iOS(11:04) Advice on choosing where to work(12:43) The importance of trusting your gut when it comes to people(14:05) Lessons from failed ventures(17:32) Why and how Pets.com shut down (18:30) How Tom's experience at Quibi renewed his passion for building(28:48) Takeaways from Quibi and why it ultimately failed(31:42) Failing is okay(35:04) Tom's career at Apple(39:11) Lessons from You Don't Know Jack(40:24) Lessons from building Pandora(48:24) Looking back at Pandora and what could have been done differently(55:17) How Tom became VP of Product at Snapchat(1:01:31) Tom's philosophy on being involved as CEO(1:05:51) Tom's current role as CEO of Zero, and what he's learned along the way(1:10:37) How Zero builds product(1:18:33) Advice on work-life balance (1:27:22) Contrarian corner: why not everyone needs to be a founder(1:30:08) Lightning round—Referenced:• Ron Lichty on LinkedIn: https://www.linkedin.com/in/ronlichty/• What happened to Pets.com?: https://fourweekmba.com/pets-com-failure/• 11 reasons why Quibi crashed and burned in less than a year: https://www.theverge.com/2020/10/22/21528404/quibi-shut-down-cost-subscribers-content-tv-movies-katzenberg-whitman-tiktok-netflix• Meg Whitman: https://en.wikipedia.org/wiki/Meg_Whitman• Jeffrey Katzenberg on LinkedIn: https://www.linkedin.com/in/jeffrey-katzenberg-4b3b47123/• John Sculley on LinkedIn: https://www.linkedin.com/in/johnsculley/• Flickr: https://www.flickr.com/• How Pandora Soothed the Savage Beast: https://www.fastcompany.com/3001052/how-pandora-soothed-savage-beast• Joe Kennedy on LinkedIn: https://www.linkedin.com/in/joe-kennedy-329417/• Why Did Yahoo Pay $160 Million for Musicmatch?: https://www.wired.com/2007/07/why-did-yahoo-p/• TikTok Is the New TV: https://www.wired.com/story/tiktok-new-show-tv-takeover/• Evan Spiegel on X: https://twitter.com/evanspiegel• Brian Chesky's new playbook: https://www.lennyspodcast.com/brian-cheskys-new-playbook/• What sets great teams apart | Lane Shackleton (CPO of Coda): https://www.lennyspodcast.com/what-sets-great-teams-apart-lane-shackleton-cpo-of-coda/• Flashtags: https://lane.substack.com/p/flashtags• Patrick Spence on LinkedIn: https://www.linkedin.com/in/patrickspence/• The Philosophy of Ikigai: 3 Examples About Finding Purpose: https://positivepsychology.com/ikigai• The Subtle Art of Not Giving a F*ck: A Counterintuitive Approach to Living a Good Life: https://www.amazon.com/Subtle-Art-Not-Giving-Counterintuitive/dp/0062457713• High Growth Handbook: Scaling Startups from 10 to 10,000 People: https://www.amazon.com/High-Growth-Handbook-Elad-Gil/dp/1732265100• Hyperion: https://www.amazon.com/Hyperion-Cantos-Dan-Simmons/dp/0553283685• A Fire Upon the Deep: https://www.amazon.com/Fire-Upon-Deep-Zones-Thought/dp/0812515285/• Mrs. Davis on Peacock: https://www.peacocktv.com/stream-tv/mrs-davis• Watchmen on HBO: https://www.hbo.com/watchmen• Lost on Hulu: https://www.hulu.com/series/lost-466b3994-b574-44f1-88bc-63707507a6cb• Eartune replacement tips: https://eartune.com/products/eartune-fidelity-ufa• Charles Eames's quote: https://www.brainyquote.com/quotes/charles_eames_169188• Compuserve: https://www.compuserve.com/• Steve Wilhite: https://en.wikipedia.org/wiki/Steve_Wilhite—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

Alle Infos zu ausgewählten Werbepartnern findest du hier.  Das Buch zum Podcast? JETZT BESTELLEN.  Lieber als Newsletter? Geht auch.  ChatGPT-CEO wird zu Sam Outman. Schlecht läuft's auch für Chargepoint und Applied Materials. Dafür hat GAP mehr als überzeugt, Joe Kaeser kauft bei Siemens Energy ein und der Bitcoin ist stabil. Kleider machen Leute. Manche Leute machen Kleidung sauber. Vestis (WKN: A3EVGB) verdient damit Milliarden. Snap (WKN: A2DLMS) ist zu ineffizient. Das denkt der Gründer Evan Spiegel und will nachts mehr Leute im Office sehen. Was heißt das für die Aktie? Diesen Podcast vom 20.11.2023, 3:00 Uhr stellt dir die Podstars GmbH (Noah Leidinger) zur Verfügung. Learn more about your ad choices. Visit megaphone.fm/adchoices

Today's guest is James Vincent who spent eleven years working directly with Steve Jobs to help build Apple's narrative for some of its hugely ground-breaking products including the iPod, iPhone, iTunes, App Store and iPad.He also founded and was CEO of Media Arts Lab which was a bespoke agency working exclusively for Apple and is host of Fast Company's Innovation in Leaders Podcast.A master storyteller, James is now Founder and CEO of FNDR - an agency which works with game changing entrepreneurs such as Brian Chesky of Airbnb and Evan Spiegel of Snap to help them harness the immense power of an intentional narrative to bring voice to their vision. In this episode, James and I discuss what he was like growing up and how he felt like an outsider to getting the call to come and work with Steve and what was the greatest lesson he learned from him.I found this to be a really insightful conversation and a first-hand glimpse into what it was like working at Apple with both Steve and legends like Jony Ive on campaigns for some of the most iconic products of recent times. I think you will really enjoy it too.James Vincent on Twitter / FNDR / Leaders in Innovation Podcast Danielle Twitter / Instagram / Substack Newsletter Mentioned in this episode:Apple's Mother Nature adApple's iPod Silhouette campaignLeaders in Innovation Podcast 

Following news at Snap, the gang debates what the media gets wrong about founders and how founders need to react in this new market. Discussed https://www.youtube.com/watch?v=WHsHKzYOV2E&t=779s Show Notes (00:00) Opening (06:05) Evan Spiegel's Persistence and Motivation (11:25) Founders and Product as Powerful Motivating Force (15:39) Challenges of Starting Over from Scratch (19:36) Balancing Product and Business Strategy (29:54) The End of the Product-Focused CEO?  (37:02) Crypto Market Update and Outlook

Eerst was er de handelsoorlog met Amerika, toen de corona-restricties, later de problemen in de supplychain en nu de Chinese consument die minder durft uit te geven. Het is klap op klap voor de Chinese economie. Maar goed nieuws: volgend jaar komt de echte groei weer terug. Dat voorspelt de voormalige baas van de Londense beurs. Het ergste is voorbij. Deze aflevering gaan we het hebben over China. Op de dag dat bekend werd dat Tim Cook, baas van Apple, een verrassingsbezoekje bracht. Is 2024 inderdaad het jaar dat China er bovenop komt? Houdt het grote namen als Apple binnenboord of verhuizen ze naar India? Wat is er nodig voor de groei en gaan Nederlandse bedrijven daar van profiteren? Wat ook voorbij komt: de gelekte outlook van Snap. De topman ligt onder vuur, omdat zijn interne voorspellingen op straat liggen. Ook gaat het over een Chinese autobouwer die Tesla bijna voorbij is, afvalmedicijnen die toch niet helpen met afvallen, de grootste cryptoboef en de kwartaalcijfers van Amerikaanse banken. Het 'te mooi om waard te zijn'-aandeel is vandaag een hele sector: luchtvaartaandelen. Ook sluiten we af met een vooruitblik op morgen en dan staat ASML in de hoofdrol.See omnystudio.com/listener for privacy information.

Snapchat launched an AI chatbot recently. And as users flooded to the feature, CEO Evan Spiegel says he discovered users' embrace of AI could improve targeted advertising. Spiegel spoke at the WSJ's Journal House during the Cannes Lions International Festival this week. We bring you highlights from that conversation. Julie Chang hosts. Learn more about your ad choices. Visit megaphone.fm/adchoices

Miranda Kerr is an accomplished model and the founder and CEO of KORA Organics. Born and raised in Australia surrounded by family and farmland, she got her start in modeling at 13 and soon established herself as one of the most in-demand and influential faces in the world of fashion and beauty.In 2007, Victoria's Secret signed Miranda as an Angel, making her the first and only Australian model ever to hold the coveted title. It was only a couple of years later that she would start and self-fund KORA Organics, an award-winning, certified organic skincare brand which is sold in over 30 countries.She is also a mother of three children, a Certified Health Coach, a best-selling author, and a supporter of numerous causes relating to women, children, health, and the environment.*The Founder Hour is brought to you by Outer. Outer makes the world's most beautiful, comfortable, innovative, and high-quality outdoor furniture - ALL from sustainable materials - and is the ONLY outdoor furniture with a patented built-in cover to make protecting it effortless. From teak chairs to fire pit tables, everything Outer makes has the look and feel of what you'd expect at a 5-star resort, for less than you'd pay at a big box store for something that won't last.For a limited time, get 10% off and FREE shipping at www.liveouter.com/thefounderhour. Terms and conditions apply.*This episode is brought to you by “More Than Profit.” If you enjoy The Founder Hour, we think you'll enjoy this podcast too. It celebrates entrepreneurs, investors, and leaders that are living and working with purpose. The host, Bryce Butler, sits down with his guests and shares personal stories about what it's like to succeed…and even fail. But more than that, what motivates them beyond just profit to press forward in their work and as a leader.Check out “More Than Profit” wherever you get your podcasts or at www.morethanprofit.fm.*This episode is brought to you by Jason Wu Beauty, affordable luxury makeup infused with skincare ingredients. Founded on the idea that beauty should be effortless and chic, Jason Wu Beauty is about really showing yourself through the beauty products, not being covered up by them. Whether you prefer minimal, natural elegance or bold glamor, Jason Wu Beauty has the perfect products for you. With colors and shades that can be used with any skin tone, you can create countless looks to enhance your natural beauty and release your inner icon. You will feel beautiful, confident, and completely yourself. Jason Wu Beauty is clean, and always cruelty-free.Available now at Target, JCPenney, Shoppers Drug Mart, and JasonWuBeauty.com.

The Snap CEO talks about the challenges facing the company's AI chatbot, how augmented reality glasses could change how we compute the real world and why a TikTok ban would “help” Snap.  You can follow Kara and Nayeema on Instagram. Search for @karaswisher and @nayeemaraza. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Jack Brody is the VP Product @ Snap. Jack joined Snap in 2014 as a Product Designer, and ultimately helped build out the design organization as the Head of Design before taking on his current role overseeing all of Product for the Snapchat application and Hardware. In his 9 years at Snap, he helped create Memories, the Snap Map, and AR Lenses like Face Swap. In Today's Episode with Jack Brody We Discuss: The Shortest Internship in Tech: How did Jack get an internship with Evan Spiegel and Snap while he was still at college? How did it turn into the shortest internship in tech history? What are the single biggest product lessons Jack has from working with Evan Spiegel? 2. Product 101: Art vs Science: Does Jack believe product is more art or science? If he were to assign numbers to them, what would they be? How does Jack define creativity? What can founders and product leaders do to ensure their teams are as creative as possible? What is the 3 step framework through which product leaders should prioritize product ideas? Does Jack believe that when the CEO is no longer the Head of Product, the company is dead? Does Jack agree with Gustav Soderstrom, "talk is cheap, so we should do more of it"? 3. The SNAP Hiring Process: What Works and What Does Not: What is the hiring process for the product team at SNAP? What questions are most revealing of 10x product people in the interview process? What case studies and tests does Jack use in the interview process? What other roles and functions does Jack bring into the interview process as part of the decision? What are the single biggest mistakes founders make in the hiring process for product? 4. SNAP, The Future, and The World Around Us: What do Jack and SNAP believe will be the future for augmented reality? What country is SNAP not big in today but will be in the next 5 years? Why that one? Why did SNAP tear down its android app and start again? What has been the impact? Were the SNAP glasses a success? What is their future?  

2023 is the year of Multimodal AI, and Latent Space is going multimodal too! * This podcast comes with a video demo at the 1hr mark and it's a good excuse to launch our YouTube - please subscribe! * We are also holding two events in San Francisco — the first AI | UX meetup next week (already full; we'll send a recap here on the newsletter) and Latent Space Liftoff Day on May 4th (signup here; but get in touch if you have a high profile launch you'd like to make). * We also joined the Chroma/OpenAI ChatGPT Plugins Hackathon last week where we won the Turing and Replit awards and met some of you in person!This post featured on Hacker News.Out of the five senses of the human body, I'd put sight at the very top. But weirdly when it comes to AI, Computer Vision has felt left out of the recent wave compared to image generation, text reasoning, and even audio transcription. We got our first taste of it with the OCR capabilities demo in the GPT-4 Developer Livestream, but to date GPT-4's vision capability has not yet been released. Meta AI leapfrogged OpenAI and everyone else by fully open sourcing their Segment Anything Model (SAM) last week, complete with paper, model, weights, data (6x more images and 400x more masks than OpenImages), and a very slick demo website. This is a marked change to their previous LLaMA release, which was not commercially licensed. The response has been ecstatic:SAM was the talk of the town at the ChatGPT Plugins Hackathon and I was fortunate enough to book Joseph Nelson who was frantically integrating SAM into Roboflow this past weekend. As a passionate instructor, hacker, and founder, Joseph is possibly the single best person in the world to bring the rest of us up to speed on the state of Computer Vision and the implications of SAM. I was already a fan of him from his previous pod with (hopefully future guest) Beyang Liu of Sourcegraph, so this served as a personal catchup as well. Enjoy! and let us know what other news/models/guests you'd like to have us discuss! - swyxRecorded in-person at the beautiful StudioPod studios in San Francisco.Full transcript is below the fold.Show Notes* Joseph's links: Twitter, Linkedin, Personal* Sourcegraph Podcast and Game Theory Story* Represently* Roboflow at Pioneer and YCombinator* Udacity Self Driving Car dataset story* Computer Vision Annotation Formats* SAM recap - top things to know for those living in a cave* https://segment-anything.com/* https://segment-anything.com/demo* https://arxiv.org/pdf/2304.02643.pdf * https://ai.facebook.com/blog/segment-anything-foundation-model-image-segmentation/* https://blog.roboflow.com/segment-anything-breakdown/* https://ai.facebook.com/datasets/segment-anything/* Ask Roboflow https://ask.roboflow.ai/* GPT-4 Multimodal https://blog.roboflow.com/gpt-4-impact-speculation/Cut for time:* WSJ mention* Des Moines Register story* All In Pod: timestamped mention* In Forbes: underrepresented investors in Series A* Roboflow greatest hits* https://blog.roboflow.com/mountain-dew-contest-computer-vision/* https://blog.roboflow.com/self-driving-car-dataset-missing-pedestrians/* https://blog.roboflow.com/nerualhash-collision/ and Apple CSAM issue * https://www.rf100.org/Timestamps* [00:00:19] Introducing Joseph* [00:02:28] Why Iowa* [00:05:52] Origin of Roboflow* [00:16:12] Why Computer Vision* [00:17:50] Computer Vision Use Cases* [00:26:15] The Economics of Annotation/Segmentation* [00:32:17] Computer Vision Annotation Formats* [00:36:41] Intro to Computer Vision & Segmentation* [00:39:08] YOLO* [00:44:44] World Knowledge of Foundation Models* [00:46:21] Segment Anything Model* [00:51:29] SAM: Zero Shot Transfer* [00:51:53] SAM: Promptability* [00:53:24] SAM: Model Assisted Labeling* [00:56:03] SAM doesn't have labels* [00:59:23] Labeling on the Browser* [01:00:28] Roboflow + SAM Video Demo * [01:07:27] Future Predictions* [01:08:04] GPT4 Multimodality* [01:09:27] Remaining Hard Problems* [01:13:57] Ask Roboflow (2019)* [01:15:26] How to keep up in AITranscripts[00:00:00] Hello everyone. It is me swyx and I'm here with Joseph Nelson. Hey, welcome to the studio. It's nice. Thanks so much having me. We, uh, have a professional setup in here.[00:00:19] Introducing Joseph[00:00:19] Joseph, you and I have known each other online for a little bit. I first heard about you on the Source Graph podcast with bian and I highly, highly recommend that there's a really good game theory story that is the best YC application story I've ever heard and I won't tease further cuz they should go listen to that.[00:00:36] What do you think? It's a good story. It's a good story. It's a good story. So you got your Bachelor of Economics from George Washington, by the way. Fun fact. I'm also an econ major as well. You are very politically active, I guess you, you did a lot of, um, interning in political offices and you were responding to, um, the, the, the sheer amount of load that the Congress people have in terms of the, the support.[00:01:00] So you built, representing, which is Zendesk for Congress. And, uh, I liked in your source guide podcast how you talked about how being more responsive to, to constituents is always a good thing no matter what side of the aisle you're on. You also had a sideline as a data science instructor at General Assembly.[00:01:18] As a consultant in your own consultancy, and you also did a bunch of hackathon stuff with Magic Sudoku, which is your transition from N L P into computer vision. And apparently at TechCrunch Disrupt, disrupt in 2019, you tried to add chess and that was your whole villain origin story for, Hey, computer vision's too hard.[00:01:36] That's full, the platform to do that. Uh, and now you're co-founder c e o of RoboFlow. So that's your bio. Um, what's not in there that[00:01:43] people should know about you? One key thing that people realize within maybe five minutes of meeting me, uh, I'm from Iowa. Yes. And it's like a funnily novel thing. I mean, you know, growing up in Iowa, it's like everyone you know is from Iowa.[00:01:56] But then when I left to go to school, there was not that many Iowans at gw and people were like, oh, like you're, you're Iowa Joe. Like, you know, how'd you find out about this school out here? I was like, oh, well the Pony Express was running that day, so I was able to send. So I really like to lean into it.[00:02:11] And so you kind of become a default ambassador for places that. People don't meet a lot of other people from, so I've kind of taken that upon myself to just make it be a, a part of my identity. So, you know, my handle everywhere Joseph of Iowa, like I I, you can probably find my social security number just from knowing that that's my handle.[00:02:25] Cuz I put it plastered everywhere. So that's, that's probably like one thing.[00:02:28] Why Iowa[00:02:28] What's your best pitch for Iowa? Like why is[00:02:30] Iowa awesome? The people Iowa's filled with people that genuinely care. You know, if you're waiting a long line, someone's gonna strike up a conversation, kinda ask how you were Devrel and it's just like a really genuine place.[00:02:40] It was a wonderful place to grow up too at the time, you know, I thought it was like, uh, yeah, I was kind of embarrassed and then be from there. And then I actually kinda looking back it's like, wow, you know, there's good schools, smart people friendly. The, uh, high school that I went to actually Ben Silverman, the CEO and, or I guess former CEO and co-founder of Pinterest and I have the same teachers in high school at different.[00:03:01] The co-founder, or excuse me, the creator of crispr, the gene editing technique, Dr. Jennifer. Doudna. Oh, so that's the patent debate. There's Doudna. Oh, and then there's Fang Zang. Uh, okay. Yeah. Yeah. So Dr. Fang Zang, who I think ultimately won the patent war, uh, but is also from the same high school.[00:03:18] Well, she won the patent, but Jennifer won the[00:03:20] prize.[00:03:21] I think that's probably, I think that's probably, I, I mean I looked into it a little closely. I think it was something like she won the patent for CRISPR first existing and then Feng got it for, uh, first use on humans, which I guess for commercial reasons is the, perhaps more, more interesting one. But I dunno, biolife Sciences, is that my area of expertise?[00:03:38] Yep. Knowing people that came from Iowa that do cool things, certainly is. Yes. So I'll claim it. Um, but yeah, I, I, we, um, at Roble actually, we're, we're bringing the full team to Iowa for the very first time this last week of, of April. And, well, folks from like Scotland all over, that's your company[00:03:54] retreat.[00:03:54] The Iowa,[00:03:55] yeah. Nice. Well, so we do two a year. You know, we've done Miami, we've done. Some of the smaller teams have done like Nashville or Austin or these sorts of places, but we said, you know, let's bring it back to kinda the origin and the roots. Uh, and we'll, we'll bring the full team to, to Des Moines, Iowa.[00:04:13] So, yeah, like I was mentioning, folks from California to Scotland and many places in between are all gonna descend upon Des Moines for a week of, uh, learning and working. So maybe you can check in with those folks. If, what do they, what do they decide and interpret about what's cool. Our state. Well, one thing, are you actually headquartered in Des Moines on paper?[00:04:30] Yes. Yeah.[00:04:30] Isn't that amazing? That's like everyone's Delaware and you're like,[00:04:33] so doing research. Well, we're, we're incorporated in Delaware. Okay. We we're Delaware Sea like, uh, most companies, but our headquarters Yeah. Is in Des Moines. And part of that's a few things. One, it's like, you know, there's this nice Iowa pride.[00:04:43] And second is, uh, Brad and I both grew up in Brad Mc, co-founder and I grew up in, in Des Moines. And we met each other in the year 2000. We looked it up for the, the YC app. So, you know, I think, I guess more of my life I've known Brad than not, uh, which is kind of crazy. Wow. And during yc, we did it during 2020, so it was like the height of Covid.[00:05:01] And so we actually got a house in Des Moines and lived, worked outta there. I mean, more credit to. So I moved back. I was living in DC at the time, I moved back to to Des Moines. Brad was living in Des Moines, but he moved out of a house with his. To move into what we called our hacker house. And then we had one, uh, member of the team as well, Jacob Sorowitz, who moved from Minneapolis down to Des Moines for the summer.[00:05:21] And frankly, uh, code was a great time to, to build a YC company cuz there wasn't much else to do. I mean, it's kinda like wash your groceries and code. It's sort of the, that was the routine[00:05:30] and you can use, uh, computer vision to help with your groceries as well.[00:05:33] That's exactly right. Tell me what to make.[00:05:35] What's in my fridge? What should I cook? Oh, we'll, we'll, we'll cover[00:05:37] that for with the G P T four, uh, stuff. Exactly. Okay. So you have been featured with in a lot of press events. Uh, but maybe we'll just cover the origin story a little bit in a little bit more detail. So we'll, we'll cover robo flow and then we'll cover, we'll go into segment anything.[00:05:52] Origin of Roboflow[00:05:52] But, uh, I think it's important for people to understand. Robo just because it gives people context for what you're about to show us at the end of the podcast. So Magic Sudoku tc, uh, techers Disrupt, and then you go, you join Pioneer, which is Dan Gross's, um, YC before yc.[00:06:07] Yeah. That's how I think about it.[00:06:08] Yeah, that's a good way. That's a good description of it. Yeah. So I mean, robo flow kind of starts as you mentioned with this magic Sudoku thing. So you mentioned one of my prior business was a company called Represent, and you nailed it. I mean, US Congress gets 80 million messages a year. We built tools that auto sorted them.[00:06:23] They didn't use any intelligent auto sorting. And this is somewhat a solved problem in natural language processing of doing topic modeling or grouping together similar sentiment and things like this. And as you mentioned, I'd like, I worked in DC for a bit and been exposed to some of these problems and when I was like, oh, you know, with programming you can build solutions.[00:06:40] And I think the US Congress is, you know, the US kind of United States is a support center, if you will, and the United States is sports center runs on pretty old software, so mm-hmm. We, um, we built a product for that. It was actually at the time when I was working on representing. Brad, his prior business, um, is a social games company called Hatchlings.[00:07:00] Uh, he phoned me in, in 2017, apple had released augmented reality kit AR kit. And Brad and I are both kind of serial hackers, like I like to go to hackathons, don't really understand new technology until he build something with them type folks. And when AR Kit came out, Brad decided he wanted to build a game with it that would solve Sudoku puzzles.[00:07:19] And the idea of the game would be you take your phone, you hover hold it over top of a Sudoku puzzle, it recognizes the state of the board where it is, and then it fills it all in just right before your eyes. And he phoned me and I was like, Brad, this sounds awesome and sounds like you kinda got it figured out.[00:07:34] What, what's, uh, what, what do you think I can do here? It's like, well, the machine learning piece of this is the part that I'm most uncertain about. Uh, doing the digit recognition and, um, filling in some of those results. I was like, well, I mean digit recognition's like the hell of world of, of computer vision.[00:07:48] That's Yeah, yeah, MNIST, right. So I was like, that that part should be the, the easy part. I was like, ah, I'm, he's like, I'm not so super sure, but. You know, the other parts, the mobile ar game mechanics, I've got pretty well figured out. I was like, I, I think you're wrong. I think you're thinking about the hard part is the easy part.[00:08:02] And he is like, no, you're wrong. The hard part is the easy part. And so long story short, we built this thing and released Magic Sudoku and it kind of caught the Internet's attention of what you could do with augmented reality and, and with computer vision. It, you know, made it to the front ofer and some subreddits it run Product Hunt Air app of the year.[00:08:20] And it was really a, a flash in the pan type app, right? Like we were both running separate companies at the time and mostly wanted to toy around with, with new technology. And, um, kind of a fun fact about Magic Sudoku winning product Hunt Air app of the year. That was the same year that I think the model three came out.[00:08:34] And so Elon Musk won a Golden Kitty who we joked that we share an award with, with Elon Musk. Um, the thinking there was that this is gonna set off a, a revolution of if two random engineers can put together something that makes something, makes a game programmable and at interactive, then surely lots of other engineers will.[00:08:53] Do similar of adding programmable layers on top of real world objects around us. Earlier we were joking about objects in your fridge, you know, and automatically generating recipes and these sorts of things. And like I said, that was 2017. Roboflow was actually co-found, or I guess like incorporated in, in 2019.[00:09:09] So we put this out there, nothing really happened. We went back to our day jobs of, of running our respective businesses, I sold Represently and then as you mentioned, kind of did like consulting stuff to figure out the next sort of thing to, to work on, to get exposed to various problems. Brad appointed a new CEO at his prior business and we got together that summer of 2019.[00:09:27] We said, Hey, you know, maybe we should return to that idea that caught a lot of people's attention and shows what's possible. And you know what, what kind of gives, like the future is here. And we have no one's done anything since. No one's done anything. So why is, why are there not these, these apps proliferated everywhere.[00:09:42] Yeah. And so we said, you know, what we'll do is, um, to add this software layer to the real world. Will build, um, kinda like a super app where if you pointed it at anything, it will recognize it and then you can interact with it. We'll release a developer platform and allow people to make their own interfaces, interactivity for whatever object they're looking at.[00:10:04] And we decided to start with board games because one, we had a little bit of history there with, with Sudoku two, there's social by default. So if one person, you know finds it, then they'd probably share it among their friend. Group three. There's actually relatively few barriers to entry aside from like, you know, using someone else's brand name in your, your marketing materials.[00:10:19] Yeah. But other than that, there's no real, uh, inhibitors to getting things going and, and four, it's, it's just fun. It would be something that'd be bring us enjoyment to work on. So we spent that summer making, uh, boggle the four by four word game provable, where, you know, unlike Magic Sudoku, which to be clear, totally ruins the game, uh, you, you have to solve Sudoku puzzle.[00:10:40] You don't need to do anything else. But with Boggle, if you and I are playing, we might not find all of the words that adjacent letter tiles. Unveil. So if we have a, an AI tell us, Hey, here's like the best combination of letters that make high scoring words. And so we, we made boggle and released it and that, and that did okay.[00:10:56] I mean maybe the most interesting story was there's a English as a second language program in, in Canada that picked it up and used it as a part of their curriculum to like build vocabulary, which I thought was kind of inspiring. Example, and what happens just when you put things on the internet and then.[00:11:09] We wanted to build one for chess. So this is where you mentioned we went to 2019. TechCrunch Disrupt TechCrunch. Disrupt holds a Hackathon. And this is actually, you know, when Brad and I say we really became co-founders, because we fly out to San Francisco, we rent a hotel room in the Tenderloin. We, uh, we, we, uh, have one room and there's like one, there's room for one bed, and then we're like, oh, you said there was a cot, you know, on the, on the listing.[00:11:32] So they like give us a little, a little cot, the end of the cot, like bled and over into like the bathroom. So like there I am sleeping on the cot with like my head in the bathroom and the Tenderloin, you know, fortunately we're at a hackathon glamorous. Yeah. There wasn't, there wasn't a ton of sleep to be had.[00:11:46] There is, you know, we're, we're just like making and, and shipping these, these sorts of many[00:11:50] people with this hack. So I've never been to one of these things, but[00:11:52] they're huge. Right? Yeah. The Disrupt Hackathon, um, I don't, I don't know numbers, but few hundreds, you know, classically had been a place where it launched a lot of famous Yeah.[00:12:01] Sort of flare. Yeah. And I think it's, you know, kind of slowed down as a place for true company generation. But for us, Brad and I, who likes just doing hackathons, being, making things in compressed time skills, it seemed like a, a fun thing to do. And like I said, we'd been working on things, but it was only there that like, you're, you're stuck in a maybe not so great glamorous situation together and you're just there to make a, a program and you wanna make it be the best and compete against others.[00:12:26] And so we add support to the app that we were called was called Board Boss. We couldn't call it anything with Boggle cause of IP rights were called. So we called it Board Boss and it supported Boggle and then we were gonna support chess, which, you know, has no IP rights around it. Uh, it's an open game.[00:12:39] And we did so in 48 hours, we built an app that, or added fit capability to. Point your phone at a chess board. It understands the state of the chess board and converts it to um, a known notation. Then it passes that to stock fish, the open source chess engine for making move recommendations and it makes move recommendations to, to players.[00:13:00] So you could either play against like an ammunition to AI or improve your own game. We learn that one of the key ways users like to use this was just to record their games. Cuz it's almost like reviewing game film of what you should have done differently. Game. Yeah, yeah, exactly. And I guess the highlight of, uh, of chess Boss was, you know, we get to the first round of judging, we get to the second round of judging.[00:13:16] And during the second round of judging, that's when like, TechCrunch kind of brings around like some like celebs and stuff. They'll come by. Evan Spiegel drops by Ooh. Oh, and he uh, he comes up to our, our, our booth and um, he's like, oh, so what does, what does this all do? And you know, he takes an interest in it cuz the underpinnings of, of AR interacting with the.[00:13:33] And, uh, he is kinda like, you know, I could use this to like cheat on chess with my friends. And we're like, well, you know, that wasn't exactly the, the thesis of why we made it, but glad that, uh, at least you think it's kind of neat. Um, wait, but he already started Snapchat by then? Oh, yeah. Oh yeah. This, this is 2019, I think.[00:13:49] Oh, okay, okay. Yeah, he was kind of just checking out things that were new and, and judging didn't end up winning any, um, awards within Disrupt, but I think what we won was actually. Maybe more important maybe like the, the quote, like the co-founders medal along the way. Yep. The friends we made along the way there we go to, to play to the meme.[00:14:06] I would've preferred to win, to be clear. Yes. You played a win. So you did win, uh,[00:14:11] $15,000 from some Des Moines, uh, con[00:14:14] contest. Yeah. Yeah. The, uh, that was nice. Yeah. Slightly after that we did, we did win. Um, some, some grants and some other things for some of the work that we've been doing. John Papa John supporting the, uh, the local tech scene.[00:14:24] Yeah. Well, so there's not the one you're thinking of. Okay. Uh, there's a guy whose name is Papa John, like that's his, that's his, that's his last name. His first name is John. So it's not the Papa John's you're thinking of that has some problematic undertones. It's like this guy who's totally different. I feel bad for him.[00:14:38] His press must just be like, oh, uh, all over the place. But yeah, he's this figure in the Iowa entrepreneurial scene who, um, he actually was like doing SPACs before they were cool and these sorts of things, but yeah, he funds like grants that encourage entrepreneurship in the state. And since we'd done YC and in the state, we were eligible for some of the awards that they were providing.[00:14:56] But yeah, it was disrupt that we realized, you know, um, the tools that we made, you know, it took us better part of a summer to add Boggle support and it took us 48 hours to add chest support. So adding the ability for programmable interfaces for any object, we built a lot of those internal tools and our apps were kind of doing like the very famous shark fin where like it picks up really fast, then it kind of like slowly peters off.[00:15:20] Mm-hmm. And so we're like, okay, if we're getting these like shark fin graphs, we gotta try something different. Um, there's something different. I remember like the week before Thanksgiving 2019 sitting down and we wrote this Readme for, actually it's still the Readme at the base repo of Robo Flow today has spent relatively unedited of the manifesto.[00:15:36] Like, we're gonna build tools that enable people to make the world programmable. And there's like six phases and, you know, there's still, uh, many, many, many phases to go into what we wrote even at that time to, to present. But it's largely been, um, right in line with what we thought we would, we would do, which is give engineers the tools to add software to real world objects, which is largely predicated on computer vision. So finding the right images, getting the right sorts of video frames, maybe annotating them, uh, finding the right sort of models to use to do this, monitoring the performance, all these sorts of things. And that from, I mean, we released that in early 2020, and it's kind of, that's what's really started to click.[00:16:12] Why Computer Vision[00:16:12] Awesome. I think we should just kind[00:16:13] of[00:16:14] go right into where you are today and like the, the products that you offer, just just to give people an overview and then we can go into the, the SAM stuff. So what is the clear, concise elevator pitch? I think you mentioned a bunch of things like make the world programmable so you don't ha like computer vision is a means to an end.[00:16:30] Like there's, there's something beyond that. Yeah.[00:16:32] I mean, the, the big picture mission for the business and the company and what we're working on is, is making the world programmable, making it read and write and interactive, kind of more entertaining, more e. More fun and computer vision is the technology by which we can achieve that pretty quickly.[00:16:48] So like the one liner for the, the product in, in the company is providing engineers with the tools for data and models to build programmable interfaces. Um, and that can be workflows, that could be the, uh, data processing, it could be the actual model training. But yeah, Rob helps you use production ready computer vision workflows fast.[00:17:10] And I like that.[00:17:11] In part of your other pitch that I've heard, uh, is that you basically scale from the very smallest scales to the very largest scales, right? Like the sort of microbiology use case all the way to[00:17:20] astronomy. Yeah. Yeah. The, the joke that I like to make is like anything, um, underneath a microscope and, and through a telescope and everything in between needs to, needs to be seen.[00:17:27] I mean, we have people that run models in outer space, uh, underwater remote places under supervision and, and known places. The crazy thing is that like, All parts of, of not just the world, but the universe need to be observed and understood and acted upon. So vision is gonna be, I dunno, I feel like we're in the very, very, very beginnings of all the ways we're gonna see it.[00:17:50] Computer Vision Use Cases[00:17:50] Awesome. Let's go into a lo a few like top use cases, cuz I think that really helps to like highlight the big names that you've, big logos that you've already got. I've got Walmart and Cardinal Health, but I don't, I don't know if you wanna pull out any other names, like, just to illustrate, because the reason by the way, the reason I think that a lot of developers don't get into computer vision is because they think they don't need it.[00:18:11] Um, or they think like, oh, like when I do robotics, I'll do it. But I think if, if you see like the breadth of use cases, then you get a little bit more inspiration as to like, oh, I can use[00:18:19] CVS lfa. Yeah. It's kind of like, um, you know, by giving, by making it be so straightforward to use vision, it becomes almost like a given that it's a set of features that you could power on top of it.[00:18:32] And like you mentioned, there's, yeah, there's Fortune One there over half the Fortune 100. I've used the, the tools that Robel provides just as much as 250,000 developers. And so over a quarter million engineers finding and developing and creating various apps, and I mean, those apps are, are, are far and wide.[00:18:49] Just as you mentioned. I mean everything from say, like, one I like to talk about was like sushi detection of like finding the like right sorts of fish and ingredients that are in a given piece of, of sushi that you're looking at to say like roof estimation of like finding. If there's like, uh, hail damage on, on a given roof, of course, self-driving cars and understanding the scenes around us is sort of the, you know, very early computer vision everywhere.[00:19:13] Use case hardhat detection, like finding out if like a given workplace is, is, is safe, uh, disseminate, have the right p p p on or p p e on, are there the right distance from various machines? A huge place that vision has been used is environmental monitoring. Uh, what's the count of species? Can we verify that the environment's not changing in unexpected ways or like river banks are become, uh, becoming recessed in ways that we anticipate from satellite imagery, plant phenotyping.[00:19:37] I mean, people have used these apps for like understanding their plants and identifying them. And that dataset that's actually largely open, which is what's given a proliferation to the iNaturalist, is, is that whole, uh, hub of, of products. Lots of, um, people that do manufacturing. So, like Rivian for example, is a Rubal customer, and you know, they're trying to scale from 1000 cars to 25,000 cars to a hundred thousand cars in very short order.[00:20:00] And that relies on having the. Ability to visually ensure that every part that they're making is produced correctly and right in time. Medical use cases. You know, there's actually, this morning I was emailing with a user who's accelerating early cancer detection through breaking apart various parts of cells and doing counts of those cells.[00:20:23] And actually a lot of wet lab work that folks that are doing their PhDs or have done their PhDs are deeply familiar with that is often required to do very manually of, of counting, uh, micro plasms or, or things like this. There's. All sorts of, um, like traffic counting and smart cities use cases of understanding curb utilization to which sort of vehicles are, are present.[00:20:44] Uh, ooh. That can be[00:20:46] really good for city planning actually.[00:20:47] Yeah. I mean, one of our customers does exactly this. They, they measure and do they call it like smart curb utilization, where uhhuh, they wanna basically make a curb be almost like a dynamic space where like during these amounts of time, it's zoned for this during these amounts of times.[00:20:59] It's zoned for this based on the flows and e ebbs and flows of traffic throughout the day. So yeah, I mean the, the, the truth is that like, you're right, it's like a developer might be like, oh, how would I use vision? And then all of a sudden it's like, oh man, all these things are at my fingertips. Like I can just, everything you can see.[00:21:13] Yeah. Right. I can just, I can just add functionality for my app to understand and ingest the way, like, and usually the way that someone gets like almost nerd sniped into this is like, they have like a home automation project, so it's like send Yeah. Give us a few. Yeah. So send me a text when, um, a package shows up so I can like prevent package theft so I can like go down and grab it right away or.[00:21:29] We had a, uh, this one's pretty, pretty niche, but it's pretty funny. There was this guy who, during the pandemic wa, wanted to make sure his cat had like the proper, uh, workout. And so I've shared the story where he basically decided that. He'd make a cat workout machine with computer vision, you might be alone.[00:21:43] You're like, what does that look like? Well, what he decided was he would take a robotic arm strap, a laser pointer to it, and then train a machine to recognize his cat and his cat only, and point the laser pointer consistently 10 feet away from the cat. There's actually a video of you if you type an YouTube cat laser turret, you'll find Dave's video.[00:22:01] Uh, and hopefully Dave's cat has, has lost the weight that it needs to, cuz that's just the, that's an intense workout I have to say. But yeah, so like, that's like a, um, you know, these, uh, home automation projects are pretty common places for people to get into smart bird feeders. I've seen people that like are, are logging and understanding what sort of birds are, uh, in their background.[00:22:18] There's a member of our team that was working on actually this as, as a whole company and has open sourced a lot of the data for doing bird species identification. And now there's, I think there's even a company that's, uh, founded to create like a smart bird feeder, like captures photos and tells you which ones you've attracted to your yard.[00:22:32] I met that. Do, you know, get around the, uh, car sharing company that heard it? Them never used them. They did a SPAC last year and they had raised at like, They're unicorn. They raised at like 1.2 billion, I think in the, the prior round and inspected a similar price. I met the CTO of, of Getaround because he was, uh, using Rob Flow to hack into his Tesla cameras to identify other vehicles that are like often nearby him.[00:22:56] So he's basically building his own custom license plate recognition, and he just wanted like, keep, like, keep tabs of like, when he drives by his friends or when he sees like regular sorts of folks. And so he was doing like automated license plate recognition by tapping into his, uh, camera feeds. And by the way, Elliot's like one of the like OG hackers, he was, I think one of the very first people to like, um, she break iPhones and, and these sorts of things.[00:23:14] Mm-hmm. So yeah, the project that I want, uh, that I'm gonna work on right now for my new place in San Francisco is. There's two doors. There's like a gate and then the other door. And sometimes we like forget to close, close the gate. So like, basically if it sees that the gate is open, it'll like send us all a text or something like this to make sure that the gate is, is closed at the front of our house.[00:23:32] That's[00:23:32] really cool. And I'll, I'll call out one thing that readers and listeners can, uh, read out on, on your history. One of your most popular initial, um, viral blog post was about, um, autonomous vehicle data sets and how, uh, the one that Udacity was using was missing like one third of humans. And, uh, it's not, it's pretty problematic for cars to miss humans.[00:23:53] Yeah, yeah, actually, so yeah, the Udacity self-driving car data set, which look to their credit, it was just meant to be used for, for academic use. Um, and like as a part of courses on, on Udacity, right? Yeah. But the, the team that released it, kind of hastily labeled and let it go out there to just start to use and train some models.[00:24:11] I think that likely some, some, uh, maybe commercial use cases maybe may have come and, and used, uh, the dataset, who's to say? But Brad and I discovered this dataset. And when we were working on dataset improvement tools at Rob Flow, we ran through our tools and identified some like pretty, as you mentioned, key issues.[00:24:26] Like for example, a lot of strollers weren't labeled and I hope our self-driving cars do those, these sorts of things. And so we relabeled the whole dataset by hand. I have this very fond memory is February, 2020. Brad and I are in Taiwan. So like Covid is actually just, just getting going. And the reason we were there is we were like, Hey, we can work on this from anywhere for a little bit.[00:24:44] And so we spent like a, uh, let's go closer to Covid. Well, you know, I like to say we uh, we got early indicators of, uh, how bad it was gonna be. I bought a bunch of like N 90 fives before going o I remember going to the, the like buying a bunch of N 95 s and getting this craziest look like this like crazy tin hat guy.[00:25:04] Wow. What is he doing? And then here's how you knew. I, I also got got by how bad it was gonna be. I left all of them in Taiwan cuz it's like, oh, you all need these. We'll be fine over in the us. And then come to find out, of course that Taiwan was a lot better in terms of, um, I think, yeah. Safety. But anyway, we were in Taiwan because we had planned this trip and you know, at the time we weren't super sure about the, uh, covid, these sorts of things.[00:25:22] We always canceled it. We didn't, but I have this, this very specific time. Brad and I were riding on the train from Clay back to Taipei. It's like a four hour ride. And you mentioned Pioneer earlier, we were competing in Pioneer, which is almost like a gamified to-do list. Mm-hmm. Every week you say what you're gonna do and then other people evaluate.[00:25:37] Did you actually do the things you said you were going to do? One of the things we said we were gonna do was like this, I think re-release of this data set. And so it's like late, we'd had a whole week, like, you know, weekend behind us and, uh, we're on this train and it was very unpleasant situation, but we relabeled this, this data set, and one sitting got it submitted before like the Sunday, Sunday countdown clock starts voting for, for.[00:25:57] And, um, once that data got out back out there, just as you mentioned, it kind of picked up and Venture beat, um, noticed and wrote some stories about it. And we really rereleased of course, the data set that we did our best job of labeling. And now if anyone's listening, they can probably go out and like find some errors that we surely still have and maybe call us out and, you know, put us, put us on blast.[00:26:15] The Economics of Annotation (Segmentation)[00:26:15] But,[00:26:16] um, well, well the reason I like this story is because it, it draws attention to the idea that annotation is difficult and basically anyone looking to use computer vision in their business who may not have an off-the-shelf data set is going to have to get involved in annotation. And I don't know what it costs.[00:26:34] And that's probably one of the biggest hurdles for me to estimate how big a task this is. Right? So my question at a higher level is tell the customers, how do you tell customers to estimate the economics of annotation? Like how many images do, do we need? How much, how long is it gonna take? That, that kinda stuff.[00:26:50] How much money and then what are the nuances to doing it well, right? Like, cuz obviously Udacity had a poor quality job, you guys had proved it, and there's errors every everywhere. Like where do[00:26:59] these things go wrong? The really good news about annotation in general is that like annotation of course is a means to an end to have a model be able to recognize a thing.[00:27:08] Increasingly there's models that are coming out that can recognize things zero shot without any annotation, which we're gonna talk about. Yeah. Which, we'll, we'll talk more about that in a moment. But in general, the good news is that like the trend is that annotation is gonna become decreasingly a blocker to starting to use computer vision in meaningful ways.[00:27:24] Now that said, just as you mentioned, there's a lot of places where you still need to do. Annotation. I mean, even with these zero shot models, they might have of blind spots, or maybe you're a business, as you mentioned, that you know, it's proprietary data. Like only Rivian knows what a rivian is supposed to look like, right?[00:27:39] Uh, at the time of, at the time of it being produced, like underneath the hood and, and all these sorts of things. And so, yeah, that's gonna necessarily require annotation. So your question of how long is it gonna take, how do you estimate these sorts of things, it really comes down to the complexity of the problem that you're solving and the amount of variance in the scene.[00:27:57] So let's give some contextual examples. If you're trying to recognize, we'll say a scratch on one specific part and you have very strong lighting. You might need fewer images because you control the lighting, you know the exact part and maybe you're lucky in the scratch. Happens more often than not in similar parts or similar, uh, portions of the given part.[00:28:17] So in that context, you, you, the function of variance, the variance is, is, is lower. So the number of images you need is also lower to start getting up to work. Now the orders of magnitude we're talking about is that like you can have an initial like working model from like 30 to 50 images. Yeah. In this context, which is shockingly low.[00:28:32] Like I feel like there's kind of an open secret in computer vision now, the general heuristic that often. Users, is that like, you know, maybe 200 images per class is when you start to have a model that you can rely[00:28:45] on? Rely meaning like 90, 99, 90, 90%, um,[00:28:50] uh, like what's 85 plus 85? Okay. Um, that's good. Again, these are very, very finger in the wind estimates cuz the variance we're talking about.[00:28:59] But the real question is like, at what point, like the framing is not like at what point do it get to 99, right? The framing is at what point can I use this thing to be better than the alternative, which is humans, which maybe humans or maybe like this problem wasn't possible at all. And so usually the question isn't like, how do I get to 99?[00:29:15] A hundred percent? It's how do I ensure that like the value I am able to get from putting this thing in production is greater than the alternative? In fact, even if you have a model that's less accurate than humans, there might be some circumstances where you can tolerate, uh, a greater amount of inaccuracy.[00:29:32] And if you look at the accuracy relative to the cost, Using a model is extremely cheap. Using a human for the same sort of task can be very expensive. Now, in terms of the actual accuracy of of what you get, there's probably some point at which the cost, but relative accuracy exceeds of a model, exceeds the high cost and hopefully high accuracy of, of a human comparable, like for example, there's like cameras that will track soccer balls or track events happening during sporting matches.[00:30:02] And you can go through and you know, we actually have users that work in sports analytics. You can go through and have a human. Hours and hours of footage. Cuz not just watching their team, they're watching every other team, they're watching scouting teams, they're watching junior teams, they're watching competitors.[00:30:15] And you could have them like, you know, track and follow every single time the ball goes within blank region of the field or every time blank player goes into, uh, this portion of the field. And you could have, you know, exact, like a hundred percent accuracy if that person, maybe, maybe not a hundred, a human may be like 95, 90 7% accuracy of every single time the ball is in this region or this player is on the field.[00:30:36] Truthfully, maybe if you're scouting analytics, you actually don't need 97% accuracy of knowing that that player is on the field. And in fact, if you can just have a model run at a 1000th, a 10000th of the cost and goes through and finds all the times that Messi was present on the field mm-hmm. That the ball was in this region of the.[00:30:54] Then even if that model is slightly less accurate, the cost is just so orders of magnitude different. And the stakes like the stakes of this problem, of knowing like the total number of minutes that Messi played will say are such that we have a higher air tolerance, that it's a no-brainer to start to use Yeah, a computer vision model in this context.[00:31:12] So not every problem requires equivalent or greater human performance. Even when it does, you'd be surprised at how fast models get there. And in the times when you, uh, really look at a problem, the question is, how much accuracy do I need to start to get value from this? This thing, like the package example is a great one, right?[00:31:27] Like I could in theory set up a camera that's constantly watching in front of my porch and I could watch the camera whenever I have a package and then go down. But of course, I'm not gonna do that. I value my time to do other sorts of things instead. And so like there, there's this net new capability of, oh, great, I can have an always on thing that tells me when a package shows up, even if you know the, the thing that's gonna text me.[00:31:46] When a package shows up, let's say a flat pack shows up instead of a box and it doesn't know what a flat pack likes, looks like initially. Doesn't matter. It doesn't matter because I didn't have this capability at all before. And I think that's the true case where a lot of computer vision problems exist is like it.[00:32:00] It's like you didn't even have this capability, this superpower before at all, let alone assigning a given human to do the task. And that's where we see like this explosion of, of value.[00:32:10] Awesome. Awesome. That was a really good overview. I want to leave time for the others, but I, I really want to dive into a couple more things with regards to Robo Flow.[00:32:17] Computer Vision Annotation Formats[00:32:17] So one is, apparently your original pitch for Robo Flow was with regards to conversion tools for computer vision data sets. And I'm sure as, as a result of your job, you have a lot of rants. I've been digging for rants basically on like the best or the worst annotation formats. What do we know? Cause most of us, oh my gosh, we only know, like, you know, I like,[00:32:38] okay, so when we talk about computer vision annotation formats, what we're talking about is if you have an image and you, you picture a boing box around my face on that image.[00:32:46] Yeah. How do you describe where that Monty box is? X, Y, Z X Y coordinates. Okay. X, y coordinates. How, what do you mean from the top lefts.[00:32:52] Okay. You, you, you, you take X and Y and then, and then the. The length and, and the width of the, the[00:32:58] box. Okay. So you got like a top left coordinate and like the bottom right coordinate or like the, the center of the bottom.[00:33:02] Yeah. Yeah. Top, left, bottom right. Yeah. That's one type of format. Okay. But then, um, I come along and I'm like, you know what? I want to do a different format where I wanna just put the center of the box, right. And give the length and width. Right. And by the way, we didn't even talk about what X and Y we're talking about.[00:33:14] Is X a pixel count? Is a relative pixel count? Is it an absolute pixel count? So the point is, the number of ways to describe where a box lives in a freaking image is endless, uh, seemingly and. Everyone decided to kind of create their own different ways of describing the coordinates and positions of where in this context of bounding Box is present.[00:33:39] Uh, so there's some formats, for example, that like use re, so for the x and y, like Y is, uh, like the left, most part of the image is zero. And the right most part of the image is one. So the, the coordinate is like anywhere from zero to one. So 0.6 is, you know, 60% of your way right up the image to describe the coordinate.[00:33:53] I guess that was, that was X instead of Y. But the point is there, of the zero to one is the way that we determined where that was in the position, or we're gonna do an absolute pixel position anyway. We got sick, we got sick of all these different annotation formats. So why do you even have to convert between formats?[00:34:07] Is is another part of this, this story. So different training frameworks, like if you're using TensorFlow, you need like TF Records. If you're using PyTorch, it's probably gonna be, well it depends on like what model you're using, but someone might use Coco JSON with PyTorch. Someone else might use like a, just a YAML file and a text file.[00:34:21] And to describe the cor it's point is everyone that creates a model. Or creates a dataset rather, has created different ways of describing where and how a bounding box is present in the image. And we got sick of all these different formats and doing these in writing all these different converter scripts.[00:34:39] And so we made a tool that just converts from one script, one type of format to another. And the, the key thing is that like if you get that converter script wrong, your model doesn't not work. It just fails silently. Yeah. Because the bounding boxes are now all in the wrong places. And so you need a way to visualize and be sure that your converter script, blah, blah blah.[00:34:54] So that was the very first tool we released of robo. It was just a converter script, you know, like these, like these PDF to word converters that you find. It was basically that for computer vision, like dead simple, really annoying thing. And we put it out there and people found some, some value in, in that.[00:35:08] And you know, to this day that's still like a surprisingly painful[00:35:11] problem. Um, yeah, so you and I met at the Dall-E Hackathon at OpenAI, and we were, I was trying to implement this like face masking thing, and I immediately ran into that problem because, um, you know, the, the parameters that Dall-E expected were different from the one that I got from my face, uh, facial detection thing.[00:35:28] One day it'll go away, but that day is not today. Uh, the worst format that we work with is, is. The mart form, it just makes no sense. And it's like, I think, I think it's a one off annotation format that this university in China started to use to describe where annotations exist in a book mart. I, I don't know, I dunno why that So best[00:35:45] would be TF record or some something similar.[00:35:48] Yeah, I think like, here's your chance to like tell everybody to use one one standard and like, let's, let's, can[00:35:53] I just tell them to use, we have a package that does this for you. I'm just gonna tell you to use the row full package that converts them all, uh, for you. So you don't have to think about this. I mean, Coco JSON is pretty good.[00:36:04] It's like one of the larger industry norms and you know, it's in JS O compared to like V xml, which is an XML format and Coco json is pretty descriptive, but you know, it has, has its own sort of drawbacks and flaws and has random like, attribute, I dunno. Um, yeah, I think the best way to handle this problem is to not have to think about it, which is what we did.[00:36:21] We just created a, uh, library that, that converts and uses things. Uh, for us. We've double checked the heck out of it. There's been hundreds of thousands of people that have used the library and battle tested all these different formats to find those silent errors. So I feel pretty good about no longer having to have a favorite format and instead just rely on.[00:36:38] Dot load in the format that I need. Great[00:36:41] Intro to Computer Vision Segmentation[00:36:41] service to the community. Yeah. Let's go into segmentation because is at the top of everyone's minds, but before we get into segment, anything, I feel like we need a little bit of context on the state-of-the-art prior to Sam, which seems to be YOLO and uh, you are the leading expert as far as I know.[00:36:56] Yeah.[00:36:57] Computer vision, there's various task types. There's classification problems where we just like assign tags to images, like, you know, maybe safe work, not safe work, sort of tagging sort of stuff. Or we have object detection, which are the boing boxes that you see and all the formats I was mentioning in ranting about there's instant segmentation, which is the polygon shapes and produces really, really good looking demos.[00:37:19] So a lot of people like instant segmentation.[00:37:21] This would be like counting pills when you point 'em out on the, on the table. Yeah. So, or[00:37:25] soccer players on the field. So interestingly, um, counting you could do with bounding boxes. Okay. Cause you could just say, you know, a box around a person. Well, I could count, you know, 12 players on the field.[00:37:35] Masks are most useful. Polygons are most useful if you need very precise area measurements. So you have an aerial photo of a home and you want to know, and the home's not a perfect box, and you want to know the rough square footage of that home. Well, if you know the distance between like the drone and, and the ground.[00:37:53] And you have the precise polygon shape of the home, then you can calculate how big that home is from aerial photos. And then insurers can, you know, provide say accurate estimates and that's maybe why this is useful. So polygons and, and instant segmentation are, are those types of tasks? There's a key point detection task and key point is, you know, if you've seen those demos of like all the joints on like a hand kind of, kind of outlined, there's visual question answering tasks, visual q and a.[00:38:21] And that's like, you know, some of the stuff that multi-modality is absolutely crushing for, you know, here's an image, tell me what food is in this image. And then you can pass that and you can make a recipe out of it. But like, um, yeah, the visual question in answering task type is where multi-modality is gonna have and is already having an enormous impact.[00:38:40] So that's not a comprehensive survey, very problem type, but it's enough to, to go into why SAM is significant. So these various task types, you know, which model to use for which given circumstance. Most things is highly dependent on what you're ultimately aiming to do. Like if you need to run a model on the edge, you're gonna need a smaller model, cuz it is gonna run on edge, compute and process in, in, in real time.[00:39:01] If you're gonna run a model on the cloud, then of course you, uh, generally have more compute at your disposal Considerations like this now, uh,[00:39:08] YOLO[00:39:08] just to pause. Yeah. Do you have to explain YOLO first before you go to Sam, or[00:39:11] Yeah, yeah, sure. So, yeah. Yeah, we should. So object detection world. So for a while I talked about various different task types and you can kinda think about a slide scale of like classification, then obvious detection.[00:39:20] And on the right, at most point you have like segmentation tasks. Object detection. The bounding boxes is especially useful for a wide, like it's, it's surprisingly versatile. Whereas like classification is kind of brittle. Like you only have a tag for the whole image. Well, that doesn't, you can't count things with tags.[00:39:35] And on the other hand, like the mask side of things, like drawing masks is painstaking. And so like labeling is just a bit more difficult. Plus like the processing to produce masks requires more compute. And so usually a lot of folks kind of landed for a long time on obvious detection being a really happy medium of affording you with rich capabilities because you can do things like count, track, measure.[00:39:56] In some CAGR context with bounding boxes, you can see how many things are present. You can actually get a sense of how fast something's moving by tracking the object or bounding box across multiple frames and comparing the timestamp of where it was across those frames. So obviously detection is a very common task type that solves lots of things that you want do with a given model.[00:40:15] In obviously detection. There's been various model frameworks over time. So kind of really early on there's like R-CNN uh, then there's faster rc n n and these sorts of family models, which are based on like resnet kind of architectures. And then a big thing happens, and that is single shot detectors. So faster, rc n n despite its name is, is very slow cuz it takes two passes on the image.[00:40:37] Uh, the first pass is, it finds par pixels in the image that are most interesting to, uh, create a bounding box candidate out of. And then it passes that to a, a classifier that then does classification of the bounding box of interest. Right. Yeah. You can see, you can see why that would be slow. Yeah. Cause you have to do two passes.[00:40:53] You know, kind of actually led by, uh, like mobile net was I think the first large, uh, single shot detector. And as its name implies, it was meant to be run on edge devices and mobile devices and Google released mobile net. So it's a popular implementation that you find in TensorFlow. And what single shot detectors did is they said, Hey, instead of looking at the image twice, what if we just kind of have a, a backbone that finds candidate bounding boxes?[00:41:19] And then we, we set loss functions for objectness. We set loss function. That's a real thing. We set loss functions for objectness, like how much obj, how object do this part of the images. We send a loss function for classification, and then we run the image through the model on a single pass. And that saves lots of compute time and you know, it's not necessarily as accurate, but if you have lesser compute, it can be extremely useful.[00:41:42] And then the advances in both modeling techniques in compute and data quality, single shot detectors, SSDs has become, uh, really, really popular. One of the biggest SSDs that has become really popular is the YOLO family models, as you described. And so YOLO stands for you only look once. Yeah, right, of course.[00:42:02] Uh, Drake's, uh, other album, um, so Joseph Redman introduces YOLO at the University of Washington. And Joseph Redman is, uh, kind of a, a fun guy. So for listeners, for an Easter egg, I'm gonna tell you to Google Joseph Redman resume, and you'll find, you'll find My Little Pony. That's all I'll say. And so he introduces the very first YOLO architecture, which is a single shot detector, and he also does it in a framework called Darknet, which is like this, this own framework that compiles the Cs, frankly, kind of tough to work with, but allows you to benefit from the speedups that advance when you operate in a low level language like.[00:42:36] And then he releases, well, what colloquially is known as YOLO V two, but a paper's called YOLO 9,000 cuz Joseph Redmond thought it'd be funny to have something over 9,000. So get a sense for, yeah, some fun. And then he releases, uh, YOLO V three and YOLO V three is kind of like where things really start to click because it goes from being an SSD that's very limited to competitive and, and, and superior to actually mobile That and some of these other single shot detectors, which is awesome because you have this sort of solo, I mean, him and and his advisor, Ali, at University of Washington have these, uh, models that are becoming really, really powerful and capable and competitive with these large research organizations.[00:43:09] Joseph Edmond leaves Computer Vision Research, but there had been Alexia ab, one of the maintainers of Darknet released Yola VI four. And another, uh, researcher, Glenn Yer, uh, jocker had been working on YOLO V three, but in a PyTorch implementation, cuz remember YOLO is in a dark implementation. And so then, you know, YOLO V three and then Glenn continues to make additional improvements to YOLO V three and pretty soon his improvements on Yolov theory, he's like, oh, this is kind of its own things.[00:43:36] Then he releases YOLO V five[00:43:38] with some naming[00:43:39] controversy that we don't have Big naming controversy. The, the too long didn't read on the naming controversy is because Glen was not originally involved with Darknet. How is he allowed to use the YOLO moniker? Roe got in a lot of trouble cuz we wrote a bunch of content about YOLO V five and people were like, ah, why are you naming it that we're not?[00:43:55] Um, but you know,[00:43:56] cool. But anyway, so state-of-the-art goes to v8. Is what I gather.[00:44:00] Yeah, yeah. So yeah. Yeah. You're, you're just like, okay, I got V five. I'll skip to the end. Uh, unless, unless there's something, I mean, I don't want, well, so I mean, there's some interesting things. Um, in the yolo, there's like, there's like a bunch of YOLO variants.[00:44:10] So YOLOs become this, like this, this catchall for various single shot, yeah. For various single shot, basically like runs on the edge, it's quick detection framework. And so there's, um, like YOLO R, there's YOLO S, which is a transformer based, uh, yolo, yet look like you only look at one sequence is what s stands were.[00:44:27] Um, the pp yo, which, uh, is PAT Paddle implementation, which is by, which Chinese Google is, is their implementation of, of TensorFlow, if you will. So basically YOLO has like all these variants. And now, um, yo vii, which is Glen has been working on, is now I think kind of like, uh, one of the choice models to use for single shot detection.[00:44:44] World Knowledge of Foundation Models[00:44:44] Well, I think a lot of those models, you know, Asking the first principal's question, like let's say you wanna find like a bus detector. Do you need to like go find a bunch of photos of buses or maybe like a chair detector? Do you need to go find a bunch of photos of chairs? It's like, oh no. You know, actually those images are present not only in the cocoa data set, but those are objects that exist like kind of broadly on the internet.[00:45:02] And so computer visions kind of been like us included, have been like really pushing for and encouraging models that already possess a lot of context about the world. And so, you know, if GB T's idea and i's idea OpenAI was okay, models can only understand things that are in their corpus. What if we just make their corpus the size of everything on the internet?[00:45:20] The same thing that happened in imagery, what's happening now? And that's kinda what Sam represents, which is kind of a new evolution of, earlier on we were talking about the cost of annotation and I said, well, good news. Annotations then become decreasingly necessary to start to get to value. Now you gotta think about it more, kind of like, you'll probably need to do some annotation because you might want to find a custom object, or Sam might not be perfect, but what's about to happen is a big opportunity where you want the benefits of a yolo, right?[00:45:47] Where it can run really fast, it can run on the edge, it's very cheap. But you want the knowledge of a large foundation model that already knows everything about buses and knows everything about shoes, knows everything about real, if the name is true, anything segment, anything model. And so there's gonna be this novel opportunity to take what these large models know, and I guess it's kind of like a form of distilling, like distill them down into smaller architectures that you can use in versatile ways to run in real time to run on the edge.[00:46:13] And that's now happening. And what we're seeing in actually kind of like pulling that, that future forward with, with, with Robo Flow.[00:46:21] Segment Anything Model[00:46:21] So we could talk a bit about, um, about SAM and what it represents maybe into, in relation to like these, these YOLO models. So Sam is Facebook segment Everything Model. It came out last week, um, the first week of April.[00:46:34] It has 24,000 GitHub stars at the time of, of this recording within its first week. And why, what does it do? Segment? Everything is a zero shot segmentation model. And as we're describing, creating masks is a very arduous task. Creating masks of objects that are not already represented means you have to go label a bunch of masks and then train a model and then hope that it finds those masks in new images.[00:47:00] And the promise of Segment anything is that in fact you just pass at any image and it finds all of the masks of relevant things that you might be curious about finding in a given image. And it works remarkably. Segment anything in credit to Facebook and the fair Facebook research team, they not only released the model permissive license to move things forward, they released the full data set, all 11 million images and 1.1 billion segmentation masks and three model sizes.[00:47:29] The largest ones like 2.5 gigabytes, which is not enormous. Medium ones like 1.2 and the smallest one is like 400, 3 75 megabytes. And for context,[00:47:38] for, for people listening, that's six times more than the previous alternative, which, which is apparently open images, uh, in terms of number images, and then 400 times more masks than open[00:47:47] images as well.[00:47:48] Exactly, yeah. So huge, huge order magnitude gain in terms of dataset accessibility plus like the model and how it works. And so the question becomes, okay, so like segment. What, what do I do with this? Like, what does it allow me to do? And it didn't Rob float well. Yeah, you should. Yeah. Um, it's already there.[00:48:04] You um, that part's done. Uh, but the thing that you can do with segment anything is you can almost, like, I almost think about like this, kinda like this model arbitrage where you can basically like distill down a giant model. So let's say like, like let's return to the package example. Okay. The package problem of, I wanna get a text when a package appears on my front porch before segment anything.[00:48:25] The way that I would go solve this problem is I would go collect some images of packages on my porch and I would label them, uh, with bounding boxes or maybe masks in that part. As you mentioned, it can be a long process and I would train a model. And that model it actually probably worked pretty well cause it's purpose-built.[00:48:44] The camera position, my porch, the packages I'm receiving. But that's gonna take some time, like everything that I just mentioned the

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Aleen starts off by recapping the *fab* Marcus Mumford concert she went to, including all of her celeb sightings—Evan Spiegel and Hilary Duff's husband. Sami and Jordana wonder how TF she recognized them, before they defer the conversation to Jordana. AKA, the Selena Gomez point person, to discuss Selena's new documentary (it's beside the point that Jordana doesn't follow Selena on Instagram). They get into a *passionate* debate about the documentary, but come to the consensus that the first half is better. Then onto another documentary…of sorts. They debrief the new “Buying Beverly Hills” reality show with Kyle Richards' fam, and share their takes on the daughters and the nepotism. They wrap up with a discussion about *that* new Jennifer Aniston cover before going through celebs who are allegedly disliked—is Julia Roberts more bitchy than diva or diva than bitchy? Learn more about your ad choices. Visit megaphone.fm/adchoices

2022 has been a difficult year for Snap, Inc. Shortly after announcing layoffs, Snap CEO Evan Spiegel sat down with Kara and Scott to discuss the challenges facing his company, and why he thinks they can be overcome. Recorded on September 7 at Code 2022 in Los Angeles. Learn more about your ad choices. Visit podcastchoices.com/adchoices

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