Podcasts about Udacity

This episode of Deep Dives with Iman, featured by Radio 4 Brainport and hosted by Iman Mossavat, features Luis Serrano, founder of Serrano Academy, YouTuber, and author of Grokking Machine Learning. Luis shares his approach to making mathematics accessible and relatable. His career spans mathematician, machine learning engineer at Google, AI educator at Udacity and Apple, Quantum AI researcher at Zapata, and now full-time educator through his YouTube channel. He believes math should feel like music—enjoyable for everyone, not just experts. Listeners will encounter insights on abstraction, inclusive education without gatekeeping, and the growing role of emotional intelligence alongside AI.

Master Google Cloud's most advanced AI certification with this definitive 2025 study guide. From TensorFlow and data pipelines to ML ops, model deployment, and ethical AI—this book delivers the knowledge, tools, and confidence to help you ace the Professional Machine Learning Engineer Exam. Backed by real-world examples, mock exams, and hands-on insights.

The new thin phone era is definitively here with the Galaxy S25 Edge. Apple is working on a way to control your iPhone with your brain. For the first time a flagship DJI drone is NOT available in the US. And flying drones are cool, but you know what else is cool? Submarine drones.Sponsors:For 40% off your order, head to Udacity.com/RIDE and use code RIDELinks:Samsung Debuts $1,099 S25 Edge, Kicking Off Wave of Thin Phones (Bloomberg)Galaxy S25 Edge Hands-On: This Thin Phone Left a Deep Impression (CNET)Apple to Unveil New AI Tool to Increase iPhone Battery Life (Bloomberg)DJI is skipping the US with its most advanced drone yet (The Verge)German defence start-up plans underwater drones for naval surveillance (FT)Audible to Partner With Publishers to Create AI-Voiced Audiobooks (Bloomberg)See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

MeidasTouch host Ben Meiselas reports on Donald Trump blaming his own DOJ lawyers for his unlawful conduct and his violations of Supreme Court orders. Udacity: For 40% OFF your order, head to https://Udacity.com/meidas and use promo code: MEIDAS Visit https://meidasplus.com for more! Remember to subscribe to ALL the MeidasTouch Network Podcasts: MeidasTouch: https://www.meidastouch.com/tag/meidastouch-podcast Legal AF: https://www.meidastouch.com/tag/legal-af MissTrial: https://meidasnews.com/tag/miss-trial The PoliticsGirl Podcast: https://www.meidastouch.com/tag/the-politicsgirl-podcast The Influence Continuum: https://www.meidastouch.com/tag/the-influence-continuum-with-dr-steven-hassan Mea Culpa with Michael Cohen: https://www.meidastouch.com/tag/mea-culpa-with-michael-cohen The Weekend Show: https://www.meidastouch.com/tag/the-weekend-show Burn the Boats: https://www.meidastouch.com/tag/burn-the-boats Majority 54: https://www.meidastouch.com/tag/majority-54 Political Beatdown: https://www.meidastouch.com/tag/political-beatdown On Democracy with FP Wellman: https://www.meidastouch.com/tag/on-democracy-with-fpwellman Uncovered: https://www.meidastouch.com/tag/maga-uncovered Coalition of the Sane: https://meidasnews.com/tag/coalition-of-the-sane Learn more about your ad choices. Visit megaphone.fm/adchoices

Today's digital landscape isn't just shaped by code—it's shaped by how deeply companies listen. Whether in retail, software, or AI, brands that center their design around real user behavior are pulling ahead. Intuit's “Follow Me Home” approach exemplifies this mindset, encouraging teams to observe customers in their daily environments to uncover real needs. This commitment to customer-centric innovation continues to influence how digital products are designed, tested, and trusted.So how do personal passions like music, books, or frustration with bad service help create better digital experiences?On this episode of DisruptED, host Ron J Stefanski welcomes back Scott Wilder, Global Head of Digital Self-Serve at LastPass and longtime friend from their Borders Books and Music days. Together, they reflect on how early exposure to physical retail and analog media helped inform Scott's approach to customer-centric innovation, particularly in building digital self-service solutions rooted in empathy, simplicity, and trust.Key Highlights:Fixing the Fractured Self-Serve Experience – Scott breaks down how disjointed help centers, support portals, and learning sites confuse users and weaken trust. He shares his approach to designing seamless, customer-first digital journeys.Bringing the Customer into the Room – Drawing on his time at Intuit, Scott explains how physically involving customers in product discussions—through calls, visits, or even team meetings—creates more meaningful innovation than spreadsheets ever could.Building Trust in an AI-Driven World – As AI tools become more central to support and learning, Scott argues that trust, clarity, and human touchpoints will define which experiences succeed and which fail.This is a special treat to have Scott Wilder from Last Pass on the DisruptED podcast. Ron and Scott worked together for 5 years at Borders Books and Music. As they acknowledge on these shows, they learned an awful lot about the kind of intellectual curiosity that fuels innovation.Scott is a recognized thought leader in advancing technology after leading a number of highly innovative tech initiatives as a key executive at Intuit, Google, Hubspot, Udacity, Coursera and Adobe. His passion for technology is fueled by intense curiosity about how to make things work better.

Technology disruption continues to reshape how we work, learn, and connect. From bookstores to browsers, the leap from physical to digital has transformed not only industries, but expectations. According to McKinsey & Company, generative AI alone could add up to $4.4 trillion annually to the global economy, making it vital to understand how curiosity, learning, and innovation fuel this transformation.So what can we learn about today's digital evolution by revisiting the early internet days, especially from someone who built online experiences before “online” was mainstream?On this episode of DisruptED, host Ron J Stefanski reconnects with longtime friend and fellow Borders alum Scott Wilder, now the Global Head of Digital Self-Serve at LastPass. Together, they explore how bookstores, browsers, and bold ideas shaped some of today's most essential tech innovations. Their conversation tracks the early signals of technology disruption, from pioneering web platforms to building scalable, AI-enhanced learning and customer experiences.In this episode, Ron and Scott discuss:Borders as a Digital Pioneer – Borders wasn't just about books. Scott recalls how the company experimented with online media, store-level websites, and event integration—laying the groundwork for modern e-commerce personalization.Early Internet Innovation – From launching web support at Silicon Graphics to building web ad infrastructure at AOL, Scott helped define digital customer engagement before it became standard practice.Curiosity as a Catalyst – Whether in edtech or AI, Scott emphasizes how intellectual curiosity drives innovation, fuels collaboration, and helps overcome fear of new technologies.This is a special treat to have Scott Wilder from Last Pass on the DisruptED podcast. Ron and Scott worked together for 5 years at Borders Books and Music. As they acknowledge on these shows, they learned an awful lot about the kind of intellectual curiosity that fuels innovation.Scott is a recognized thought leader in advancing technology after leading a number of highly innovative tech initiatives as a key executive at Intuit, Google, Hubspot, Udacity, Coursera and Adobe. His passion for technology is fueled by intense curiosity about how to make things work better.

MeidasTouch host Ben Meiselas reports on Trump's tarrifs and policies screwing over Elon Musk as Trump's cabinet start to turn against Musk as well.  Thanks to Udacity: For 40% OFF your order, head to Udacity.com/meidas and use promo code: MEIDAS Learn more about your ad choices. Visit megaphone.fm/adchoices

Live from Transform 2025! Sarah Reynolds (they/them) is a creative, award-winning marketing executive and advocate for diversity, equity, inclusion, and belonging (DEIB). A veteran of the HR software market, Sarah is currently Chief Marketing Officer at Hibob, where they bring their deep industry knowledge, passion for storytelling, and keen eye for performance insights to bear in scaling HiBob's global reach. Prior to joining HiBob, Sarah was Chief Marketing Officer at Udacity, Head of Commercial Marketing at APTC, and Vice President of Marketing at Salary.com. An openly non-binary executive, Sarah writes and speaks widely about diversity and inclusion, pay equity, the future of work, and the intersection of bias, ethics, and technology. They have contributed to Forbes, Campaign US, Yahoo Finance, Training Industry Magazine, and the Society for Human Resources blog, and frequently speak at live and virtual events hosted by the National Association of Manufacturers, the Manufacturing Leadership Council, the Manufacturing Institute, WorldatWork, SHRM, HR Dive, AICPA, and more. Learn more about HiBob: https://www.hibob.com/ Connect with Sarah: https://www.linkedin.com/in/sarahlizreynolds/ In this fantastic covo, we dig into: - The state of the TA landscape - How pay transparency supports recruitment and retention efforts - Strategies and technology that can help implement pay transparency policies - Addressing gender, racial, and other pay disparities through benchmarking And so much more! Live from Transform 2025, we're bringing you an exclusive podcast series packed with insights from some of the brightest minds in hiring, talent strategy, and workforce transformation! In this series, we've got incredible guests from Okta, Tubi, Edelman, Greenhouse, Findem, and more, sharing how top organizations are rethinking hiring, culture, and talent acquisition in today's fast-changing world. Greenhouse combines a structured, data-driven hiring approach with AI-embedded workflows that empower recruiters to focus on strategic, high-impact work. From sourcing top talent to personalizing the candidate experience, Greenhouse streamlines and optimizes the entire hiring process. This ensures that every hire is the right hire—eliminating bias, creating fairness, and helping teams make smarter, faster decisions. Over 7,500 companies, including HubSpot, Duolingo, and J.D. Power, trust Greenhouse to build better teams and turn talent into a strategic advantage. Want to learn how today's top companies are winning the talent game? Tune in now and visit Greenhouse.com to transform the way you hire. Thanks for listening. Please follow us on Instagram @NHPTalent and X @AdamJPosner. Visit www.thePOZcast.com for all episodes

Welcome to today's ICYMI, where we kick off the week with a quick game-changing tip from one of our guests that you might have missed. Your network is everything. The way you establish and nurture your own network and reputation can make all the difference in your career success, so we're throwing it back to this great advice from Maha Abouelenein on how to add value to your unique network. Maha Abouelenein is a strategic communication and personal branding expert who has handled communications for some of world's largest tech companies in the Middle East - from Google and Netflix to Udacity and Weber Shandwick, along with promotions and sports marketing programs for the Olympics, NASCAR, Women's Hockey, and the NFL.Maha consulted on strategic communications with the Obama administration and has worked with powerhouses like Gary Vaynerchuk and Deepak Chopra. She was honored as one of the most influential women in Dubai, and nominated as of one of Forbes Power Women of the Middle East. She's the CEO of Digital & Savvy, host of the Savvy Talk podcast, and Best-Selling Author of "7 Rules of Self-Reliance”.Listen to our full episode with Maha here.Tune in every Monday for an expert dose of life advice in under 10 minutes.Follow Maha on Instagram and on her website.Listen to Maha's Podcast, Savvy Talk.Order Maha's book, 7 Rules of Self-Reliance Sign up for our monthly adulting newsletter:teachmehowtoadult.ca/newsletter Follow us on the ‘gram:@teachmehowtoadultmedia@gillian.bernerFollow on TikTok: @teachmehowtoadultSubscribe on YouTube

Have a great point of view to add? Send us a text with your thoughts!Signals over leads. Talent over tech. Confidence over conformity. Therese Parkes, Vice President, Global Market Development and Growth at Udacity, is welcomed back on this week's episode of The Tech Marketing Podcast. With insights sharpened by her shift from tech giant advisory roles to hands-on enterprise transformation. Therese and Jon explore how the B2B buyer journey is changing, why signals matter more than leads, and how AI needs more than just adoption—it demands culture, process, and talent alignment. If you're wrestling with digital transformation or evolving your go-to-market in an AI-driven world, this episode is essential listening.

Brandon Truong, Co-Founder and CPO at ZetaChain, the first Universal Blockchain, where he leads the development of the first universal blockchain for chain abstraction and interoperability. Brandon co-founded Yada, a social and SaaS startup (acquired in 2020), while simultaneously holding leadership roles at Stanford, Udacity, and BuzzFeed.In this conversation, we discuss:- Brandon's journey from start-ups to co-founding ZetaChain- The first universal blockchain: interoperability & user experience- Unlocking DeFi potential for BTC- Enhancing Bitcoin's programmability to seamlessly connect with multiple blockchains- What are universal apps and how to build them- Allowing BTC, ETH, and USDC to flow freely across chains- Omnichain Smart Contracts and Universal EVM- Deploying universal apps in a single place- On November 15th, ZETA becomes the 6th token recognized by the Dubai Financial Services Authority (DFSA)- The future of AI and crypto- Interoperability and cross-chain communicationZetaChainWebsite: www.zetachain.comX: @zetablockchainTelegram: t.me/zetachainofficialBrandon TruongLinkedIn: Brandon Truong ---------------------------------------------------------------------------------  This episode is brought to you by PrimeXBT.  PrimeXBT offers a robust trading system for both beginners and professional traders that demand highly reliable market data and performance. Traders of all experience levels can easily design and customize layouts and widgets to best fit their trading style. PrimeXBT is always offering innovative products and professional trading conditions to all customers.   PrimeXBT is running an exclusive promotion for listeners of the podcast. After making your first deposit, 50% of that first deposit will be credited to your account as a bonus that can be used as additional collateral to open positions.  Code: CRYPTONEWS50  This promotion is available for a month after activation. Click the link below:  PrimeXBT x CRYPTONEWS50

If you're looking for the cheat code to catapult your career trajectory, today's episode is a must-listen. We're learning how to succeed using our most valuable currency: our reputation, and our networks, from global communications strategist Maha Abouelenein.Our reputations matter in every area of our lives, especially in this digital age when comments, reviews and feedback are instant and public. The reality is, everyone has a personal brand — it's not just for influencers — and today you'll learn how to harness yours as a powerful tool.Maha Abouelenein is a strategic communication and personal branding expert who has handled communications for some of world's largest tech companies in the Middle East - from Google and Netflix to Udacity and Weber Shandwick. She supported the largest IPO and acquisition in Egypt's history, along with promotions and sports marketing programs for the Olympics, NASCAR, Women's Hockey, and the NFL.Maha consulted on strategic communications with the Obama administration and has worked with powerhouses like Gary Vaynerchuk and Deepak Chopra. She was honored as one of the most influential women in Dubai, and nominated as of one of Forbes Power Women of the Middle East.She's the CEO of Digital & Savvy, host of the Savvy Talk podcast, and Best-Selling Author of "7 Rules of Self-Reliance”.Ready to listen? Learn how to make yourself indispensable at work:The formula for building self-reliance, and Maha's Seven RulesHow prioritizing my reputation has served me throughout my careerHow to cultivate an authentic personal brand that stands out at workFiguring out what your unique narrative really isHow to elevate your reputation online and in personWhy it's key to be a value creator, and easy ways to add more valueHacks for networking meaningfully online and IRLWhy every leader should be prioritizing storytellingMaha's #1 tip for staying agile in an ever-changing worldHow to stop being a waiter and create your own opportunitiesThe power of strong relationshipsFollow Maha on Instagram and on her website.Listen to Maha's Podcast, Savvy Talk.Order Maha's book, 7 Rules of Self-RelianceThis show is produced by:Gillian Berner, Host, Producer & EditorOlivia Nashmi, Audio EngineerCarolyn Schissler , Designer & Web ProducerFor advertising and sponsorship inquiries, please contact Frequency Podcast Network. Sign up for our monthly adulting newsletter:teachmehowtoadult.ca/newsletter Follow us on the ‘gram:@teachmehowtoadultmedia@gillian.bernerFollow on TikTok: @teachmehowtoadult

Weiterbildung mit KI – Chancen für Unternehmer – Shownotes In dieser Episode von TomsTalkTime geht es um die Rolle der Künstlichen Intelligenz in der Weiterbildung speziell für Unternehmer. In der modernen Geschäftswelt, in der sich alles schnell verändert, wird es immer wichtiger, neue Fähigkeiten zu erlernen und Wissen kontinuierlich zu aktualisieren. KI-gestützte Lernplattformen bieten genau dafür eine Lösung: Sie ermöglichen eine effiziente, flexible und personalisierte Weiterbildung, die sich an deine individuellen Lernziele und Bedürfnisse anpasst. Tom zeigt dir in dieser Episode, wie du KI in deinen Weiterbildungsprozess einbinden kannst, um dich und dein Unternehmen fit für die Zukunft zu machen. Zusammenfassung und Stichpunkte: Möglichkeiten, die KI in der Weiterbildung bietet: Wie Weiterbildung mit KI persönlicher und relevanter für Unternehmer gestaltet. Beispiele für KI-gestützte Lernplattformen: Einblicke in Plattformen wie Coursera und Udacity und ihre spezifischen Vorteile bei Weiterbildung mit KI. Wichtige Skills für Unternehmer: Die Vielzahl an Hard und Soft Skills, die dank KI effizient und flexibel erlernt werden können durch Weiterbildung mit KI. Vorteile gegenüber klassischen Methoden: Flexibilität, Zeitersparnis und individuelle Lernwege mit KI, die sowohl den Lernprozess als auch die Qualität der Inhalte verbessern. Shownotes und Episodendetails In dieser Folge erfährst du, wie du Künstliche Intelligenz gezielt für deine Weiterbildung einsetzen kannst. Kurz: Weiterbildung mit KI. Unternehmer müssen heute mehr denn je am Puls der Zeit bleiben, und genau hier kann KI als „persönlicher Coach“ einen entscheidenden Unterschied machen. KI-Tools können dir helfen, gezielte Lernstrategien zu entwickeln und deine Fortschritte ständig zu überprüfen, sodass du dich konsequent weiterentwickelst und deine Ziele erreichst. Hier sind die wichtigsten Themen, die in dieser Episode behandelt werden: Welche Möglichkeiten bietet Weiterbildung mit KI? Künstliche Intelligenz ermöglicht es dir, nicht nur Wissen zu erlangen, sondern es auch effizient und gezielt auf dich zugeschnitten zu konsumieren. Durch personalisierte Vorschläge, die an deinen Wissensstand, deine beruflichen Ziele und sogar deine bevorzugte Lernweise angepasst sind, bekommst du das Wissen, das für dich wirklich relevant ist. So sparst du Zeit und gewinnst die Flexibilität, die Weiterbildung dann zu machen, wenn es dir passt. Diese Effizienz bietet dir den Vorteil, dass du stets nur das lernst, was du wirklich für dein Business und deine Weiterentwicklung benötigst, ohne von allgemeinem Wissen überfordert zu werden. Beispiele für KI-gestützte Lernplattformen: Plattformen wie Coursera, Udacity und LinkedIn Learning nutzen KI, um den Lernprozess gezielt zu optimieren und deine persönlichen Fortschritte sichtbar zu machen. Diese Plattformen analysieren deine Lerngewohnheiten und Vorlieben und bieten dir Inhalte an, die genau auf dich zugeschnitten sind. Das bedeutet, ob du visuell, textbasiert oder interaktiv lernst – die Plattformen passen sich dynamisch an. Sie fordern dich heraus, gehen auf deine Schwächen ein und helfen dir dabei, deine Fähigkeiten kontinuierlich zu verbessern. Der Lernerfolg wird messbar, da du stets aufbauende und passende Inhalte bekommst, die dir beim Erreichen deiner individuellen Ziele helfen. Wichtige Skills, die Unternehmer durch Weiterbildung mit KI lernen können: KI ist ein „digitaler Trainer“, der dir ermöglicht, eine breite Palette an neuen Skills zu entwickeln – von technischen Grundlagen wie Datenanalyse und Programmieren bis hin zu essentiellen Soft Skills. Entscheidungsfindung und Führungsqualitäten lassen sich mit KI-gesteuerten Programmen ebenfalls simulieren und üben. Diese Programme bieten interaktive Szenarien, in denen du Entscheidungen treffen und in einer sicheren Umgebung Fehler machen kannst. Die KI analysiert dein Verhalten und gibt dir direkt Feedback, sodass du nach und nach strategisch denkst und agierst. Das ermöglicht dir, im Alltag souveräner und erfolgreicher aufzutreten und in deinem unternehmerischen Umfeld fundierte Entscheidungen zu treffen. Vorteile und Herausforderungen von Weiterbildung mit KI gegenüber klassischen Methoden: Die Flexibilität, die KI-Weiterbildung bietet, ist kaum zu übertreffen. Anstatt an feste Zeiten und Orte gebunden zu sein, entscheidest du selbst, wann und wo du lernen möchtest. Das macht es ideal für Unternehmer, die oft wenig Zeit haben, sich aber dennoch kontinuierlich weiterentwickeln möchten. Gleichzeitig bringt der Umgang mit KI gewisse Herausforderungen mit sich. Ein technisches Grundverständnis und Offenheit gegenüber neuen Methoden sind oft gefragt. Doch wenn du dich darauf einlässt, eröffnen sich dir neue Lernwege, die nicht nur effizient, sondern auch auf deine individuellen Ziele zugeschnitten sind. Der große Vorteil gegenüber klassischen Methoden liegt also in der Kombination aus Flexibilität, Effizienz und Personalisierung, die es dir ermöglicht, in deinem eigenen Tempo und genau an den für dich relevanten Themen zu arbeiten. Zusammenfassung: KI-Tools bieten eine personalisierte, zielgerichtete Form der Weiterbildung, die speziell für Unternehmer große Vorteile bringt. KI-gestützte Lernplattformen passen Inhalte auf dich an und optimieren so deinen Lernprozess durch gezieltes Feedback. Unternehmer können sowohl technische Skills als auch Soft Skills mithilfe von KI-gestützten Programmen weiterentwickeln und ihre Entscheidungsfähigkeit in simulationsbasierten Umgebungen trainieren. Die Flexibilität und die Möglichkeit des selbstbestimmten Lernens machen KI-Weiterbildung zu einem Vorteil gegenüber klassischen Methoden. Und denk immer daran: Wer will, findet Wege. Wer nicht will, findet Gründe. Tschüss, mach's gut. Dein Tom.   Hol Dir jetzt Dein Hörbuch "Selfmade Millionäre packen aus" und klicke auf das Bild!     Buchempfehlung bei Amazon: Denken Sie wie Ihre Kunden   +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Mehr Freiheit, mehr Geld und mehr Spaß mit DEINEM eigenen Podcast. Erfahre jetzt, warum es auch für Dich Sinn macht, Deinen eigenen Podcast zu starten. Jetzt hier zum kostenlosen Podcast-Workshop anmelden: https://Podcastkurs.com +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++   So fing alles an. Hier geht´s zur allerersten Episode von TomsTalkTime.com – DER Erfolgspodcast. Und ja, der Qualitätsunterschied sollte zu hören sein. Aber hey, das war 2012…

Hooking your audience is one thing, but keeping them emotionally invested in your content is another. So for this episode of Remarkable, we're taking marketing lessons on doing just that from the Irish dark comedy, Bad Sisters.It's a show about four sisters who plot to kill their diabolical brother-in-law, and the season starts with his funeral.Series creator, Sharon Horgan, says, “We had to keep an audience with us for 10 episodes and keep them wanting the same outcome." That is, the death of their brother-in-law, John Paul. So with the help of our special guest, D2L CMO Brian Finnerty, we're talking about hooking your audience, knowing your target, and doing trial and error. About our guest, Brian FinnertyBrian Finnerty is a B2B marketing specialist with over 25 years experience leading enterprise marketing teams. He currently serves as CMO at D2L. His expertise includes brand strategy, B2B demand generation, and global customer acquisition from mid-market to Fortune 500. He previously served as VP of Revenue Marketing for Udacity. Prior to joining Udacity, Brian served as VP of Growth Marketing at Demandbase, where he was responsible for demand generation, field marketing, and customer marketing at Demandbase. Brian has also been a marketing leader at two ad tech companies, Marin Software and Smaato. He co-founded an e-learning startup that specialized in software developer training, with a rules-based code judging engine. He is an active Customer Advisory Board member for both 6sense and Sendoso.What B2B Companies Can Learn From Bad Sisters:Start with a hook. Bad Sisters grabs viewers' attention because it's about four sisters plotting to kill their brother-in-law, and it starts with his funeral. So the question is: “How did he die?” This is what drives viewers to keep watching. So how can you get your audience invested in your content? What question do you want to inspire them to ask?Know your target. This is a bit tongue-in-cheek, but just like the sisters truly knew their brother-in-law and all the ways they could potentially do him in, so should marketers get to know their audience so they can appeal to them. Brian says, “The sisters do a lot of research and they really know their target audience. Like, what does JP like to eat? What does he like to drink? If you were to poison him, how would you do that? So they really do research, like, ‘What are the ways that we can do this and get away with it, and free our sister from the prison of her marriage?' So they really do their kind of their targeting and their research, which I think any good marketer does.”Do trial and error. Try different marketing strategies and keep dialing it in based on data you get from the tests. Brian says, “[The sisters] do that right throughout the show. Like, they're testing ways to bump this guy off. Some of them end in sort of miserable failure and some of them have some potential of succeeding and you're never quite sure. Not unlike a lot of digital campaigns, where you're trying to find that perfect balance and the right approach.”Quotes*”I think for marketers, if you're not pushing the envelope, testing new messaging and testing new approaches to your website, conversion, optimization, your customer journey, your buyer's journey, then you're not trying hard enough. You're not getting enough data from the market to optimize and improve.”*”In a B2B context, it is tough to really identify a villain. And that kind of marketing turns me off. Some companies will identify their competitors as villains and really go after them. As a marketer, I would say instead of identifying your competitors as a villain, which I think is a mistake, you look at either the cost of doing nothing, or like, ‘What is the counterpoint to your mission?'”Time Stamps[0:55] Meet Brian Finnerty, CMO at D2L[3:02] D2L and Brian's Role as CMO[4:04] How Bad Sisters was created[9:30] Authenticity and Cultural Representation[22:18] B2B Marketing Takeaways from Bad Sisters[22:21] The Importance of a Good Hook[23:00] Research and Targeting in Marketing[24:08] Trial and Error in Marketing[28:30] Creating a Great Villain[33:48] Brand and Content Strategy[36:10] Effective Content Marketing[38:34] Leveraging Content Across Teams[42:58] Favorite Campaigns and Final AdviceLinksConnect with Brian on LinkedInLearn more about D2LAbout Remarkable!Remarkable! is created by the team at Caspian Studios, the premier B2B Podcast-as-a-Service company. Caspian creates both nonfiction and fiction series for B2B companies. If you want a fiction series check out our new offering - The Business Thriller - Hollywood style storytelling for B2B. Learn more at CaspianStudios.com. In today's episode, you heard from Ian Faison (CEO of Caspian Studios) and Meredith Gooderham (Senior Producer). Remarkable was produced this week by Jess Avellino, mixed by Scott Goodrich, and our theme song is “Solomon” by FALAK. Create something remarkable. Rise above the noise.

In this episode of the AI Leaders Podcast, Harsha Almad, Managing Director and Global Lead of LearnVantage Academies for AI at Accenture, Girish Ganesan, Senior Vice President at S&P Global, and Kai Roemmelt, CEO of Udacity, now part of Accenture, explore how AI is transforming the workforce, the growing need for AI literacy, tailored learning programs, and how automation is reshaping job roles. Tune in to learn how organizations can prepare for rapid technological changes, foster an AI-aware culture, and build trust in AI integration to ensure workforce readiness.

On this Live Greatly podcast episode, Kristel Bauer sits down with Maha Abouelenein, CEO and Founder of Digital and Savvy, a global communications consulting firm with offices in the United States and United Arab Emirates, to discuss the keys to becoming self-reliant.  Kristel and Maha talk about her new book 7 Rules of Self-Reliance: How to Stay Low, Keep Moving, Invest in Yourself and Own Your Future and lots more.  Tune in now! Key Takeaways From This Episode How to become self-reliant A look into Maha's personal journey including moving to Egypt and becoming a caretaker for her parents  How to embrace being a life long learner Why you should live with no regrets How to turn challenges into opportunities A look into Maha'a book 7 Rules of Self-Reliance About Maha: Maha Abouelenein is a strategic communication expert and entrepreneur with more than three decades of experience. As the CEO and Founder of Digital and Savvy, a global communications consulting firm with offices in the United States and United Arab Emirates, Maha has been instrumental in orchestrating transformations in communication strategies for clients that includes global corporate giants, high-growth startups, sports organizations, top governments, CEOs and high-net-worth individuals.  She handled communications for some of world's largest tech companies in the Middle East - from Google and Netflix to Udacity and Careem (Uber Middle East) and more. She helped PR Giant Weber Shandwick cement their presence in the Middle East, opening 18 offices in the region and leading the Cairo operation. She supported the largest IPO & the largest acquisition in Egypt's history at Orascom Telecom. She also supported promotions and sports marketing programs & strategic partnerships for the Olympics, NASCAR, ATP Tennis, Women's Hockey, and the NFL at consumer product giant General Mills before becoming an entrepreneur. Maha is the host of the Savvy Talk Podcast, where she engages in thought-provoking conversations with industry leaders. Maha passionately advocates for the power of storytelling and self-reliance in the modern age, emphasizing personal branding as a transformative pathway to leadership. Maha is a dual citizen, an avid tennis player and resides in Wayzata, Minnesota with her dog Coco.  Connect with Maha: Order 7 Rules of Self-Reliance: https://www.mahaabouelenein.com/book  Website: https://www.mahaabouelenein.com/  LinkedIn: https://www.linkedin.com/in/maha-abouelenein/  Instagram: https://www.instagram.com/mahagaber/  About the Host of the Live Greatly podcast, Kristel Bauer: Kristel Bauer is a corporate wellness and performance expert, keynote speaker and TEDx speaker supporting organizations and individuals on their journeys for more happiness and success. She is the author of Work-Life Tango: Finding Happiness, Harmony, and Peak Performance Wherever You Work (John Murray Business November 19, 2024). With Kristel's healthcare background, she provides data driven actionable strategies to leverage happiness and high-power habits to drive growth mindsets, peak performance, profitability, well-being and a culture of excellence. Kristel's keynotes provide insights to “Live Greatly” while promoting leadership development and team building.   Kristel is the creator and host of her global top self-improvement podcast, Live Greatly. She is a contributing writer for Entrepreneur, and she is an influencer in the business and wellness space having been recognized as a Top 10 Social Media Influencer of 2021 in Forbes. As an Integrative Medicine Fellow & Physician Assistant having practiced clinically in Integrative Psychiatry, Kristel has a unique perspective into attaining a mindset for more happiness and success. Kristel has presented to groups from the American Gas Association, Bank of America, bp, Commercial Metals Company, General Mills, Northwestern University, Santander Bank and many more. Kristel has been featured in Forbes, Forest & Bluff Magazine, Authority Magazine & Podcast Magazine and she has appeared on ABC 7 Chicago, WGN Daytime Chicago, Fox 4's WDAF-TV's Great Day KC, and Ticker News. Kristel lives in the Fort Lauderdale, Florida area and she can be booked for speaking engagements worldwide. To Book Kristel as a speaker for your next event, click here. Website: www.livegreatly.co  Follow Kristel Bauer on: Instagram: @livegreatly_co  LinkedIn: Kristel Bauer Twitter: @livegreatly_co Facebook: @livegreatly.co Youtube: Live Greatly, Kristel Bauer To Watch Kristel Bauer's TEDx talk of Redefining Work/Life Balance in a COVID-19 World click here. Click HERE to check out Kristel's corporate wellness and leadership blog Click HERE to check out Kristel's Travel and Wellness Blog Disclaimer: The contents of this podcast are intended for informational and educational purposes only. Always seek the guidance of your physician for any recommendations specific to you or for any questions regarding your specific health, your sleep patterns changes to diet and exercise, or any medical conditions.  Always consult your physician before starting any supplements or new lifestyle programs. All information, views and statements shared on the Live Greatly podcast are purely the opinions of the authors, and are not medical advice or treatment recommendations.  They have not been evaluated by the food and drug administration.  Opinions of guests are their own and Kristel Bauer & this podcast does not endorse or accept responsibility for statements made by guests.  Neither Kristel Bauer nor this podcast takes responsibility for possible health consequences of a person or persons following the information in this educational content.  Always consult your physician for recommendations specific to you.

Maha Abouelenein has more than 30 years of global communications experience advising corporate giants, high-growth startups, governments, and high-net worth individuals in the USA. She is the CEO of Digital & Savvy, a strategic communication consulting firm based in the U.S. and Dubai, and sits on the Board of Directors of The Associated Press. She launched some of the world's largest tech companies in the Middle East from communications, policy, and business development perspectives - from Google and Netflix to Udacity and Careem (Uber) and more. She supported the largest IPO and the largest acquisition in Egypt's history at Orascom Telecom. She also built sports marketing programs and strategic partnerships for the Olympics, NASCAR, the NBA, ATP Tennis, Golf, and the NFL at consumer product giant General Mills. Connect With Maha Abouelenein! instagram.com/mahagaber linkedin.com/in/maha-abouelenein Join Her Facebook Group: 7 Rules Now! facebook.com/groups/737663898528581 Pre-order Her Book: 7 Rules Of Self-Reliance Here! amazon.com/gp/product/1401978665 penguinrandomhouse.com/books/760285/7-rules-of-self-reliance-by-maha-abouelenein CHAPTERS: 0:00 - Introduction 02:21 - How Did Maha Start in Marketing? 03:46 - Why is Content King in Social Media? 04:46 - Maha on Using Different Social Media Platforms 05:44 - Maha on Giving Value to People/Audience 07:30 - How to Get to Know Your Audience 08:46 - Maha on Customizing a Message 10:29 - How to Create an Interesting Story 11:53 - Maha's Personal Brand Journey 16:41 - Maha on Helping People Communicate Better 17:40 - How Does Communication Change? 19:42 - Maha on Using AI 21:03 - Brian Chesky, Mark Zuckerberg, Shopify's Founder On A Podcast 22:53 - Maha's Podcast Journey 25:00 - How to Invite Big Guests on Your Podcast 27:13 - Maha on Doing Events/Talks 28:34 - Maha's Book: 7 Rules of Self-Reliance 31:22 - What Catalyzed Maha to Write Her Book 32:33 - Maha on Using AI for PR/Marketing 34:24 - How to Know What People Value 36:45 - Maha's Thoughts on Dubai 40:47 - Maha on What Egypt Looks Like Right Now 41:56 - Maha's Advice for Young Entrepreneurs 44:50 - Maha on Using LinkedIn 46:19 - Maha on Building Your Personal Brand 47:02 - Maha's Recent Life Discoveries 48:07 - Maha's Goals for the Next 6 Months 48:40 - Connect with Maha Abouelenein 48:59 - Outro

It's YOUR time to #EdUp  In this episode, #935, brought to YOU by the InsightsEDU 2025 conference YOUR guest is ⁠Victoria Papalian⁠, COO, ⁠Udacity YOUR host is ⁠⁠Dr. Joe Sallustio⁠⁠  How does Udacity create industry-relevant, hands-on learning experiences? Why is constantly updating curriculum crucial in fast-changing tech fields? What are Udacity's new programs in Generative AI & how do partnerships with tech giants like Google enhance them? How has the recent acquisition by Accenture impacted Udacity's mission? What is the significance of Udacity's $24 million scholarship program with AWS in democratizing tech education? How does Udacity partner with higher education institutions like Western Governors University? What are "nanodegrees" & how do they fit into Udacity's various learning modalities? What is Victoria's vision for the future of post-secondary education, particularly regarding individualized learning paths? Listen in to #EdUp! If YOU want exclusive early access to ad-free episodes, extended episodes, bonus episodes, original content, invites to special events, & more, all while helping to sustain EdUp, then... BECOME A SUBSCRIBER TODAY! Thank YOU so much for tuning in. Join us on the next episode for YOUR time to EdUp! Connect with YOUR EdUp Team - ⁠⁠⁠⁠⁠Elvin Freytes⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠Dr. Joe Sallustio⁠⁠⁠⁠⁠ ● Join YOUR EdUp community at ⁠⁠⁠⁠⁠The EdUp Experience⁠⁠⁠⁠⁠! We make education YOUR business!

Apple @ Work is exclusively brought to you by Mosyle, the only Apple Unified Platform. Mosyle is the only solution that integrates in a single professional-grade platform all the solutions necessary to seamlessly and automatically deploy, manage & protect Apple devices at work. Over 45,000 organizations trust Mosyle to make millions of Apple devices work-ready with no effort and at an affordable cost. Request your EXTENDED TRIAL today and understand why Mosyle is everything you need to work with Apple. In this episode of Apple @ Work, I talk with Val Scarlata from Udacity about their newly updated iOS development nanodegree program. Show Notes Udacity Unveils A Completely Revamped IOS Developer Nanodegree Program Connect with Bradley Twitter LinkedIn Listen and subscribe Apple Podcasts Overcast Spotify Pocket Casts Castro RSS Listen to Past Episodes

Maha Abouelenein is the founder and CEO of Digital and Savvy, a success story in strategic communications. The firm focuses on creating value through powerful storytelling. Meeting Maha at the Collision Conference in Toronto recently #collisionconf was an honor. Maha has more than 30 years of global communications experience. She advises corporate giants and high-net-worth individuals across the world. The company is rooted in building meaningful relationships that yield incredible results. Maha launched some of the world's largest tech companies in the Middle East from communications, policy, and business development perspectives – from Google and Netflix to Udacity and Careem (Uber) and more. She supported the largest IPO and the largest acquisition in Egypt's history at Orascom Telecom. She also built sports marketing programs and strategic partnerships for the Olympics, NASCAR, the NBA, ATP Tennis, Golf, and the NFL at consumer product giant General Mills. Listen & Subscribe on: iTunes / Stitcher / Podbean / Overcast / Spotify Contact Info Website: www.DigitalandSavvy.com Book: 7 Rules of Self-Reliance by Maha Abouelenein Most Influential Person My father Effect On Emotions When I feel anxious, upset, worried, or nervous, I take a deep breath and slow down. I always take a deep breath and keep that moment to myself, reminding myself that everything's going to be okay. And you know what? It usually will be okay. Thoughts On Breathing Deepak Chopra introduced me to breath work a couple of years ago. I spent a lot of time with him, and he always talks about activating your vagus nerve. He taught me to practice inhaling and exhaling one side of your nose and then the other. I believe that just doing that right now can completely change our demeanor. Bullying Story Growing up as an Egyptian brown girl in Minnesota, surrounded by blonde hair and blue eyes, I stood out as the only diverse student in my school. Throughout elementary and most of high school, I was different from my classmates. Back then, without the Internet, many people didn't understand my Arab and Egyptian background. I was often called names like “camel jockey” or “towel head,” and when the song “Walk Like an Egyptian” came out, kids would mimic the dance at me. I faced a lot of bullying because of my ethnicity. Nowadays, people embrace and celebrate my Egyptian culture, but back then, it was a source of pain. I believe that mindfulness could have made a difference, helping people realize the impact of their words and actions on others' feelings. We've learned and unlearned a lot since then, and I think mindfulness plays a crucial role in that evolution. Suggested Resources Book: 7 Rules of Self-Reliance; How to Stay Low, Keep Moving, Invest in Yourself, and Own Your Future by Maha Abouelenein App: Calm Related Episodes Deal With Depression By Using Self-Care App, MindStar; CEO Kristin Rulon Aegis Living CEO and Author, Dwayne J. Clark Employee To Entrepreneur and Collective Campus CEO, Steve Glaveski Offer From Bruce Seeking relief from stress and anxiety? As a coach and hypnotist, I'm here to help you conquer your inner critic so you can confidently thrive. Email me at bruce@mindfulnessmode.com with ‘I Am Determined' for a free coaching session. Let me help you pave the way to a fulfilling life.

If you're thinking about joining a coding bootcamp, then this episode is for you.My guest for this episode is Ramone Smith, a Certified Digital Career Strategist. Ramone has experience in providing career coaching and job search services for technical bootcamp students and alumni. He has worked as a career coach, and job search consultant in various technical bootcamps such as Springboard, Udacity, and Flatiron School. He has also worked as a career coach for Per Scholas.Ramone was also a Customer Success Manager at Indeed.com, ensuring that clients maximize their investment in advertising their open jobs on Indeed's online platform.During our conversation, we explored a variety of topics, including:What types of jobs does Ramone specialize in coaching people for, and what are the key skills needed for success in those roles?What are Ramone's job searching insights from his time at Indeed.com?What specific examples of events and networking activities that can enhance your chances of landing a tech job, as recommended by Ramone?What are some examples of freelance opportunities post-bootcamp that can help jumpstart your tech career?Whether you're a recent bootcamp graduate, a seasoned tech professional, or someone looking to break into the industry, this conversation will give you some practical advice and inspiration for achieving your career goals in the software engineering space.Do you want to learn more on how you can conquer your coding bootcamp and have a successful tech career? Check out more helpful info from Ramone Smith at https://techcareerguides.com/Timestamps:00:00 Are companies more open to hiring straight out of bootcamp?  02:28 Is bootcamp the best route for anyone trying to “break” into tech?08:33 Ramone's tips for job-hunting on sites like Indeed?11:08 Ramone's examples of tips for landing a tech job after completing a bootcamp25:27 What are some red or green flags to look for when looking for a tech bootcamp to join?35:15 Unrealistic bootcamp expectations 49:04 Do they still drug test for these jobs?You can reach out to TEK or DIE by sending a message at https://www.tekordie.com/contact/#TEKorDIE #TEKorDIEpodcastIf you got value out of this episode, subscribe to this podcast and please share this conversation with someone who will benefit from it.We're also on YouTube so check it out for additional content, visuals, etc.

Episode SummaryBrian Finnerty of Udacity discusses effective strategies for aligning content to different stages of the buyer's journey. He stresses the importance of investing in lower funnel proof points like customer success stories and third-party reports. Finnerty also provides tips for validating content assumptions directly with customers. Additionally, he emphasizes optimizing the content mix based on performance data and attribution to opportunities. Throughout the conversation, Finnerty reinforces the importance of tying content marketing efforts directly to pipeline and sales goals. About the guest Brian is a senior marketing executive with deep experience leading successful marketing teams. He believes that marketing can deliver extraordinary results when it harnesses the right blend of full-funnel demand, sales alignment, and rich customer insights. Brian's expertise includes brand strategy, B2B demand generation, and global customer acquisition from mid-market to Fortune 500.  Connect with Brian Finnerty Key takeaways- Map content assets to stages of the buyer's journey, including top-of-funnel awareness content and bottom-of-funnel proof points - Invest in lower-funnel customer success stories and third-party validation reports - Validate content assumptions directly with customers through feedback - Optimize the content mix regularly based on performance data and attribution to opportunities - Track pipeline as the primary metric for measuring content marketing success Quotes "If you're able to track all of those touchpoints, and make sure that they're associated with opportunities in your CRM, then I think you've got a fairly consistent way of assessing how your content engine is performing." -Brian Finnerty Recommended Resource BooksBrian suggests "No Rules Rules" by Reed Hastings and Erin Meyer about Netflix's approach to talent and culture. Podcast Professor Galloway's podcast, ‘The Prof G Pod' for marketing and sales insights. ⁠Connect with Brian Finnerty⁠⁠⁠ | ⁠⁠⁠⁠Follow us on LinkedIn ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Ist ein AI Model eher Uber oder Tesla in Bezug auf Kapitalbedarf und Funding Logik? Zahlen von Crowdstrike, MongoDB, DocuSign und Samsara. Hellofresh bricht nach angepasstem Ausblick massiv ein.

This is our Wednesday show, focused on startup and venture capital news that matters. If you are a founder or an investor, this one is for you!Here's the day's rundown:OpenAI fires back at Musk: In the wake of a lawsuit from former backer Elon Musk, OpenAI is bringing receipts and an argument that Musk wanted to run the company's for-profit arm. Hard to argue against something that you wanted to run, yeah?Monzo raises megaround: Monzo's latest round is proof that the worst of the fintech slump is behind us.All eyes on Ema: With $25 million and a launch from stealth, Ema's work to bring AI to the enterprise is notable. But in such a crowded market, are many startups aiming too high on the stack?Accenture buys Udacity: The former unicorn's final resting place is not what it had dreamed of before, but this deal does bring welcome liquidity to at least one venture-backed startup.A climate boost? An upcoming regulatory choice could unlock a massive wave of demand for carbon-tracking startups.And the latest from OpenView: The Information reports that OpenView is returning most of its latest fund to backers. A weird and slightly sad final chapter for the firm.For episode transcripts and more, head to Equity's Simplecast website.Equity drops at 7 a.m. PT every Monday, Wednesday and Friday, so subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. TechCrunch also has a great show on crypto, a show that interviews founders and more! Credits: Equity is hosted by TechCrunch's Alex Wilhelm and Mary Ann Azevedo. We are produced by Theresa Loconsolo with editing by Kell. Bryce Durbin is our Illustrator. We'd also like to thank the audience development team and Henry Pickavet, who manages TechCrunch audio products.

Today's guest is Nigel Arbery, ESM ServiceNow Senior Director at Jade Global. Founded in 2003, Jade Global create value through their vast portfolio of IT services delivered by highly skilled and experienced consultants. Their services include business application implementations, integrations, software product engineering, cloud services, technology advisory, testing and managed services. Jade Global have domain expertise in a variety of industries including manufacturing, high-tech, energy, pharmaceuticals and warehouse distribution. Nigel has a strong track record of outstanding achievements at multibillion-dollar, world-leading enterprises across multiple industries on both a national and international scope. His career shows an exemplary record of developing and implementing strategies, leading to next-generation business transformation based on the implementation of new and emerging business technologies. Nigel plays a critical role in driving business growth at Jade Global, by ensuring that their solutions meet client needs and contribute to the overall success of the organization. In this episode, Nigel talks about: His background and previous experience within ServiceNow, An insight into the work they do at Jade Global, Why collaboration and honesty is key for successful partnerships, How project success requires finding the right people, The "Next Gen Data Management" book & Udacity course, Why evolving project goals demand continuous communication and clear understanding, How successful partnerships involve going on the journey together, The value of networking in the ServiceNow community

Dive into the future of AI and workplace dynamics with Reed Dailey in the latest episode of the Digital Deep Dive Show! On March 6, 2024, Reed unpacks Meta's new Purple Llama AI model, designed to build responsible AI with an emphasis on trust and safety. He delves into the implications of AI bias at both organizational and federal levels, highlighting the need for checks and balances in AI development. Reed also explores Kara Snyder's intriguing study on workplace interruptions and their impact on performance, considering the shift from in-person to remote interactions. He examines Accenture's strategic acquisition of Udacity, pondering the potential for upskilling staff and enhancing user adoption of new technologies. Additionally, Reed gets fired up about Tableau Pulse's integration with ChatGPT, offering consumer-friendly insights and the prospect of a more intuitive data analysis experience. He shares his insights on Microsoft Dynamics CRM's collaboration with Copilot, focusing on meeting prep and follow-up efficiencies, and the emerging importance of prompt crafting skills. Wrapping up with a personal touch, Reed shares his excitement about attending conferences in Chicago and Boston, where he anticipates gathering fresh insights to share in upcoming episodes. He also seeks listener feedback on the format for future guest interviews. Join Reed for a blend of AI innovation, corporate culture insights, and a sneak peek into his conference adventures. Don't forget to subscribe for the latest deep dives on Apple Podcasts, Spotify, LinkedIn, and more. Engage with the show and the host across social platforms and help shape the content with your feedback. Tune in, get inspired, and stay ahead with the Digital Deep Dive Show! #DigitalDeepDiveShow #AI #FutureOfWork #CorporateCulture #Innovation #LearningAndDevelopment #Analytics #SalesforceAutomation #Podcast Listen and Subscribe: - Apple Podcasts: https://apple.co/3GNBF9b - Spotify: https://spoti.fi/3GO9yGF - LinkedIn: Subscribe Online - Youtube: https://www.youtube.com/@digital3dshow - Web: https://www.podpage.com/digitaldeepdiveshow Connect with the Show: - Instagram: https://Instagram.com/Digital3DShow - Twitter: https://twitter.com/Digital3DShow Connect with the Host: - LinkedIn: https://www.Linkedin.com/in/ReedDailey - Twitter: https://www.twitter.com/ReedDailey - Instagram: https://www.Instagram.com/ReedDailey - X: @ReedDailey Show notes created by https://headliner.app ---

In our very first episode, we had the pleasure of chatting with Luis Serrano—one of the top voices in the AI space. Luis Serrano is a technology and science popularizer, researcher, and practitioner and author of the best-selling book Grokking Machine Learning. He is currently the developer relations lead at Cohere, and has previously worked at several tech companies including Google and Apple. He's also the brains behind popular ML courses on platforms like Coursera and Udacity, and the popular YouTube channel Serrano Academy, with over 135K subscribers. In this episode, we unpack Luis's fascinating journey, from his childhood and maths fears to a deep-seated passion for it and all things related, including AI and ML. We explore his career path in detail uncovering the pivotal moments and learnings, as he navigated through big tech players, changing gears from Maths to AI and Quantum AI, and how he ultimately found his true calling. We further venture into the world of AI, exploring its profound impact on education and society—both the positive advancements and the challenges it presents, and how they are reshaping the world and future. And of course, we touch upon the human side of it all—exploring the themes of humanity and empathy and implications for the future. The podcast ends with a fun and engaging rapid-fire round, again packed with bite-sized learning. So tune in, learn and get inspired!

In this conversation, we have an illuminating discussion with Waymo co-CEO Dmitri Dolgov moderated by Sebastian Thrun who started the Google Self-Driving Car project back in the day, and is also the founder of GoogleX, Google Brain, Waymo and Udacity. Tune in as they dive into the story behind Waymo's fully autonomous cars, and the road that lies ahead in this fascinating industry that is changing the way we move in the world.

Tech entrepreneur Sebastian Thrun talks about his work in Silicon Valley and the future of artificial intelligence. Thrun, formerly a vice president at Google, is the founder or co-founder of Google X (R&D), Waymo (self-driving cars), Google Brain (AI), Kitty Hawk (flying vehicles), and Udacity (online learning). Learn more about your ad choices. Visit megaphone.fm/adchoices

Tech entrepreneur Sebastian Thrun talks about his work in Silicon Valley and the future of artificial intelligence. Thrun, formerly a vice president at Google, is the founder or co-founder of Google X (R&D), Waymo (self-driving cars), Google Brain (AI), Kitty Hawk (flying vehicles), and Udacity (online learning). Learn more about your ad choices. Visit megaphone.fm/adchoices

LG 清空塔 | 雙機一體，清而易舉！吸塵器x掃地機─分進合擊！二合一省空間，雙機自動除塵。全球首發上市，預購送除蟎吸頭https://fstry.pse.is/5kg5w5 —— 以上為播客煮與 Firstory Podcast 廣告 —— ------------------------------- 通勤學英語VIP加值內容與線上課程 ------------------------------- 通勤學英語VIP訂閱方案：https://open.firstory.me/join/15minstoday 社會人核心英語有聲書課程連結：https://15minsengcafe.pse.is/554esm ------------------------------- 15Mins.Today 相關連結 ------------------------------- 歡迎針對這一集留言你的想法： 留言連結 主題投稿/意見回覆 : ask15mins@gmail.com 官方網站：www.15mins.today 加入Clubhouse直播室：https://15minsengcafe.pse.is/46hm8k 訂閱YouTube頻道：https://15minsengcafe.pse.is/3rhuuy 商業合作/贊助來信：15minstoday@gmail.com ------------------------------- 以下是此單集逐字稿 (播放器有不同字數限制，完整文稿可到官網) ------------------------------- Topic: In Race for Tuition-Free College, New Mexico Stakes a Claim As universities across the United States face steep enrollment declines, New Mexico's government is embarking on a pioneering experiment to fight that trend: tuition-free higher education for all state residents. 隨著美國各地大學入學人數急劇下滑，新墨西哥州政府正著手進行一項開創性實驗來應對這一趨勢：為全州居民提供免學費高等教育。 After President Joe Biden's plan for universal free community college failed to gain traction in Congress, New Mexico, one of the nation's poorest states, has emerged with perhaps the most ambitious plans as states scramble to come up with their own initiatives. 在美國總統拜登的全民免費社區大學計畫未能獲得國會支持後，美國最窮的州之一新墨西哥州提出的計畫，可能是各州爭相提出行動倡議中最具雄心的一個。 A new state law approved in a rare show of bipartisanship allocates almost 1% of the state's budget toward covering tuition and fees at public colleges and universities, community colleges and tribal colleges. All state residents from new high school graduates to adults enrolling part-time will be eligible regardless of family income. The program is also open to immigrants regardless of their immigration status. 一項新的州法在兩黨罕見合作下通過，將州預算的1%用於支付公立大學、社區大學與部落學院的學費。所有州民，從剛畢業的高中生到參加兼職教育的成人都有資格參加，無論家庭收入。該計畫也向移民開放，無論他們的移民身分如何。 Some legislators and other critics question whether there should have been income caps and whether the state, newly flush with oil and gas revenue, can secure long-term funding to support the program beyond its first year. The legislation, which seeks to treat college as a public resource similar to primary and secondary education, takes effect in July. 一些議員和其他批評人士質疑是否應設所得限制，以及剛獲大量石油與天然氣收入的該州是否能在計畫實施第一年後，獲得長期資金支持。這項立法將於7月生效，旨在將大學視為與中小學教育類似的公共資源。 Although nearly half the states have embraced similar initiatives that seek to cover at least some tuition expenses for some students, New Mexico's law goes further by covering tuition and fees before other scholarships and sources of financial aid are applied, enabling students to use those other funds for expenses such as lodging, food or child care. 儘管近半的州已採取類似舉措，想幫一些學生支付至少部分學費和雜費，新墨西哥州法律更進一步，在申請其他獎學金和學費補助前，先支付學雜費，讓學生能使用其他資金，支付如住宿、食物或兒童照顧等費用。 “The New Mexico program is very close to ideal,” said Michael Dannenberg, vice president of strategic initiatives and higher education policy at the nonprofit advocacy group Education Reform Now. Considering the state's income levels and available resources, he added that New Mexico's program is among the most generous in the country. 非營利倡議組織Education Reform Now策略倡議暨高教政策副總裁丹能貝格說：「新墨西哥的計畫非常貼近理想。」他表示，考量收入水準與可用資源，新墨西哥州的計畫是全美最慷慨的。 Dannenberg emphasized that New Mexico is going beyond what larger, more prosperous states like Washington and Tennessee have already done. Programs in other states often limit tuition assistance to community colleges, exclude some residents because of family income or impose conditions requiring students to work part time. 丹能貝格強調，新墨西哥州正超越華盛頓和田納西這些更大、更繁榮的州所做的事。其他州通常限制對社區大學的學費補助，因家庭收入排除一些州民，或要求學生兼職。Source article: https://udn.com/news/story/6904/6329103 Next Article Topic: Colleges Slash Budgets in the Pandemic,With ‘Nothing Off-Limits' Ohio Wesleyan University is eliminating 18 majors. The University of Florida's trustees last month took the first steps toward letting the school furlough faculty. The University of California, Berkeley, has paused admissions to its doctoral programs in anthropology, sociology and art history. 美國俄亥俄衛斯理大學取消了18個科系。佛州大學董事會9月採取初步措施，目標是讓校方有權放教師無薪假。柏克萊加州大學則暫停招收人類學、社會學和藝術史的博士班學生。 As it resurges across the country, the coronavirus is forcing universities large and small to make deep and possibly lasting cuts to close widening budget shortfalls. By one estimate, the pandemic has cost colleges at least $120 billion, with even Harvard University, despite its $41.9 billion endowment, reporting a $10 million deficit that has prompted belt tightening. 由於全美各地新冠肺炎疫情再度惡化，美國各大學不論規模大小，都被迫大砍支出，以彌補逐漸擴大的預算缺口，刪減的支出可能長期都不會恢復。有人估計，疫情至少使美國各大學合計損失1200億美元，就連坐擁419億美元辦學基金的哈佛大學也出現1000萬美元預算赤字，被迫勒緊褲帶。 The persistence of the economic downturn is taking a devastating financial toll, pushing many to lay off or furlough employees, delay graduate admissions and even cut or consolidate core programs like liberal arts departments. 經濟持續疲軟造成極其嚴重的財務災情，迫使許多大學裁員或放無薪假，推遲研究所學生入學，甚至取消或合併文科等核心學程。 The University of South Florida announced last month that its College of Education would become a graduate school only, phasing out undergraduate education degrees to help close a $6.8 million budget gap. In Ohio, the University of Akron, citing the coronavirus, successfully invoked a clause in its collective-bargaining agreement in September to supersede tenure rules and lay off 97 unionized faculty members. 南佛州大學上個月宣布，其教育學院將只留下研究所，分階段取消大學部，以彌補680萬美元的預算缺口。在俄亥俄州，艾克朗大學以疫情為由，在9月成功援用團體協約一項條款取代任期規則，裁掉97名加入工會的教師。 “We haven't seen a budget crisis like this in a generation,” said Robert Kelchen, a Seton Hall University associate professor of higher education who has been tracking the administrative response to the pandemic. “There's nothing off-limits at this point.” 西東大學高等教育副教授柯爾欽一直在關注校方對疫情的反應，他說：「這是一個世代以來從未見過的預算危機，在這種關頭，沒有什麼不能碰。」 Even before the pandemic, colleges and universities were grappling with a growing financial crisis, brought on by years of shrinking state support, declining enrollment, and student concerns with skyrocketing tuition and burdensome debt. Now the coronavirus has amplified the financial trouble systemwide, though elite, well-endowed colleges seem sure to weather it with far less pain. 早在疫情爆發前，美國大專院校就為日益嚴重的財務危機而掙扎，原因是州政府補助日漸減少，學生註冊數下滑而且介意學費高漲和學貸負擔沉重，如今，疫情擴大了整個高教體系財務問題，不過，辦學基金厚實的菁英大學似乎可度過難關，且承受的痛苦會少得多。 “We have been in aggressive recession management for 12 years — probably more than 12 years,” Daniel Greenstein, chancellor of the Pennsylvania State System of Higher Education, told his board of governors as they voted to forge ahead with a proposal to merge a half-dozen small schools into two academic entities. 賓州高等教育體系董事會表決通過，大力推動將6個小規模學院併為兩個學術單位，當時總校長葛林斯坦對董事會說：「我們積極從事於衰退問題管理已有12年，應該還不止12年。」 Source article: https://paper.udn.com/udnpaper/POH0067/359091/web/ Next Article Topic: Remember the MOOCs? After Near-Death, They're Booming Sandeep Gupta, a technology manager in California, sees the economic storm caused by the coronavirus as a time “to try to future-proof your working life.” So he is taking an online course in artificial intelligence. 美國加州科技業經理古普塔認為，新冠肺炎引發的經濟風暴是「防止職業生涯被未來淘汰」的時機，所以修讀了一門關於人工智慧的線上課程。 Dr. Robert Davidson, an emergency-room physician in Michigan, says the pandemic has cast “a glaring light on the shortcomings of our public health infrastructure.” So he is pursuing an online master's degree in public health. 密西根州急診室醫師戴維森說，疫情「使我們公衛基礎設施的弱點顯而易見」，所以他在修讀線上公衛碩士學位。 Children and college students aren't the only ones turning to online education during the coronavirus pandemic. Millions of adults have signed up for online classes in the past two months, too — a jolt that could signal a renaissance for big online learning networks that had struggled for years. 在新冠肺炎大流行期間轉而接受線上教育者，不限於兒童和大學生。過去兩個月，數以百萬計的成人也註冊參加線上課程，這令人驚訝的事實可能意味苦撐多年的大型線上學習網路即將再起。 Coursera, in which Gupta and Davidson enrolled, added 10 million new users from mid-March to mid-May, seven times the pace of new sign-ups in the previous year. Enrollments at edX and Udacity, two smaller education sites, have jumped by similar multiples. 古普塔與戴維森註冊的Coursera，從3月中旬到5月中旬增加1000萬新用戶，是去年同期新增註冊人數的七倍。edX與Udacity這兩個規模較小的教育網站，新註冊人數也以類似倍數暴增。 “Crises lead to accelerations, and this is best chance ever for online learning,” said Sebastian Thrun, a co-founder and chairman of Udacity. Udacity共同創辦人兼董事長史朗說：「危機導致改變加速發生，這是線上學習業未曾遇過的最佳良機。」 Coursera, Udacity and edX sprang up nearly a decade ago as high-profile university experiments known as MOOCs, for massive open online courses. They were portrayed as tech-fueled insurgents destined to disrupt the antiquated ways of traditional higher education. But few people completed courses, grappling with the same challenges now facing students forced into distance learning because of the pandemic. Screen fatigue sets in, and attention strays. Coursera、Udacity和edX近十年前出現，嘗試與大學合作推出線上課程而備受矚目，這類課程名為 「大規模開放線上課程」，簡稱「磨課師」。這種課程被描述為獲得科技支持的反叛者，意在顛覆傳統高等教育過時的授課方式。不過，很少有人能修完課程，這些人窮於應付的挑戰，與目前因為疫情被迫遠距學習的學生一樣。長時間盯著螢幕造成疲勞，而且注意力難以集中。 But the online ventures adapted through trial and error, gathering lessons that could provide a road map for school districts and universities pushed online. The instructional ingredients of success, the sites found, include short videos of six minutes or less, interspersed with interactive drills and tests; online forums where students share problems and suggestions; and online mentoring and tutoring. 不過這些線上企業透過反覆試驗來調整，並且積聚了可供被迫線上授課的學區和大學參考的知識和經驗。這些網站發現，線上授課成功的要素包括：短片時間不超過6分鐘，穿插互動練習和測驗；設立線上論壇，讓學生提出問題和建議；並提供線上指導和輔導。 A few top-tier universities, such as the University of Michigan and the Georgia Institute of Technology, offer some full degree programs through the online platforms. 有幾所頂尖大學，如密西根大學和喬治亞理工學院，透過這些線上平台提供一些正式學位學程。 While those academic programs are available, the online schools have tilted toward skills-focused courses that match student demand and hiring trends. 這些線上學校雖提供學術性學程，卻更傾向開設符合學生需要和雇用趨勢的技能課程。 The COVID-19 effect on online learning could broaden the range of popular subjects, education experts say. But so far, training for the tech economy is where the digital-learning money lies. With more of work and everyday life moving online — some of it permanently — that will probably not change. 教育專家指出，新冠肺炎可能會使線上課程熱門科目範圍變得更廣。不過到目前為止，針對科技經濟提供的訓練課程，才是數位教學業的金雞母。隨著更多的工作和日常生活轉移到線上進行，有些是永遠轉到線上，這種情況大概不會改變。 Source articles: https://paper.udn.com/udnpaper/POH0067/354879/web/

In a world where technology is moving at an unprecedented pace, what will the jobs of the future look like?Kai Roemmelt, CEO of the online learning platform Udacity, and Lisa Gevelber, a key figure at Google responsible for building the Grow with Google program, unpack the seismic changes reshaping the tech and education realms.From disrupting hiring norms to redefining how we acquire degrees and engage globally, this episode poses the question: How can you skillfully navigate the challenges and seize the opportunities awaiting in this evolving landscape? Topics covered: 00:00 - The Future of Jobs03:15 - Job growth over the last 80 years05:06 - The shelf-life of jobs09:11 - Education trends12:25 - The importance of learning the foundations17:18 - Regional access to education20:19 - How companies are hiring and looking at strategic priorities22:58 - The economic mobility and economic stability of degrees 25:59 - Job and training trends at Grow with Google28:11 - Do companies train or hire for skills?29:23 - The future of the traditional degree31:10 - The employer and educator ecosystem 35:36 - How to approach upskilling  Resources: Find Kai on LinkedIn: https://www.linkedin.com/in/kai-roemmeltFind Lisa on LinkedIn: https://www.linkedin.com/in/lisagevelberLearn more about Udacity: https://www.udacity.comLearn more about Grow with Google: https://grow.googleStay Updated: Find a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

DETAILS | What is a Modern People Leader, and what traits define them? There are 6! Join Daniel and Steven Huerta–the hosts of the fantastic Modern People Leader podcast–in an evolutionary discussion on HR Leadership in today's dynamic business landscape. After 155 episodes with HR leaders, they have distilled their research and insights for our show. We engage in a candid discussion on the following megatrends: The traits of a Modern People Leader, Generative AI in HR, does HR finally have a seat at the C-Suite table, the idea of running HR as a product team, and what HR will look like in 2030. This episode is an essential listen for all leaders, including CHROs, CPOs, HR Leaders, HR professionals, and business leaders seeking to evolve their leadership approach and adapt to the rapidly changing workforce. GUESTS | Daniel Huerta | Driven by the belief that people are a company's most vital asset, Daniel is on a mission to help organizations maximize their human capital potential. He co-hosts The Modern People Leader podcast, where he explores the latest trends, insights, and best practices in the HR industry. Prior to going full-time at The Modern People Leader, he spent over 8 years driving marketing strategies for some of the most influential companies in the field, including Humu and Udacity. Outside of work, he's an avid golfer, basketball player, and husband. Stephen Huerta | Stephen is an accomplished entrepreneur and former corporate HR executive passionate about making the world a better place to work. He co-hosts The Modern People Leader podcast. Stephen is also the co-founder of 'Workify,' a recently acquired employee feedback platform. Before Workify, Stephen spent five years at Goldman Sachs as Vice President, Diversity Officer, and Director of HR Technology. Outside of work, he's a proud dad of two daughters, a fitness enthusiast, and a pitmaster.   OVERVIEW | Are you ready to ADAPT and REINVENT YOURSELF for the most disrupted and digital workforce in history? It is estimated over 1 billion people will need reskilling by 2030, and more than 300 million jobs will be impacted by AI  — work, identity, and what it means to be human are rapidly changing. Join hosts Nate Thompson and Alex Schwartz and the TOP VOICES in the Future of Work to uncover how to meet this dynamic new reality driven by AI, hybrid work, societal shifts, and our increasingly digital world. Discover why a Future of Work Mindset is your key to prepare, navigate and thrive! We are grateful you are here, and welcome to the TDW Tribe! www.thedisruptedworkforce.com

In this episode, Katee chats with Sarah Reynolds. Sarah is an award-winning B2B SaaS marketing expert and proud architect of high-performing teams. A committed advocate for inclusive, people-centric growth strategies, Sarah has over 10 years' of experience shaping & leading global marketing programs that deliver transformative results for modern companies. Before joining HiBob, Sarah was Chief Marketing Officer at Udacity, where they led global brand, marketing and communications. Previously, they were Head of Commercial Marketing at PTC, where they focused on pipeline generation, value-driven messaging, and marketing operations excellence, and Vice President of Marketing at Salary.com, where they oversaw global marketing. Sarah is openly queer, trans, and non-binary and is keen to dispel hurtful stereotypes often associated with this group and the wider LGBTQIA+ community. Using their leadership position as a platform, Sarah is passionate about the use of inclusive language as a way to call out unconscious bias and dismantle the barriers impacting people's sense of belonging and access to opportunities. Graduating Summa Cum Laude from Hamilton College, NY State, USA, Sarah lives just outside of Boston, Massachusetts with their husband and greyhound. In addition to their deep interest in the HR space and commitment to democratizing opportunities for all, Sarah is a big foodie, who enjoys cooking, and eating al fresco in the garden when the weather permits. If you like what you hear, we would like to encourage you to subscribe to our channel! We would also appreciate it if you would rate this channel by going here: RateThisPodcast.com/inclusiveaf We create this podcast as a labor of love. But if you would like to support this channel you can buy us a cup of coffee here: https://www.buymeacoffee.com/InclusiveAF

Jonathan Dion d'AWS présente "AI Ready", un programme éducatif sur l'IA générative comprenant des cours gratuits, des bourses via Udacity pour les étudiants défavorisés et un partenariat avec code.org pour l'éducation des jeunes. L'initiative vise à simplifier l'apprentissage de l'IA générative et pourrait augmenter l'employabilité et les revenus des participants.

Siddharth Srivastav is the co-founder of Able Jobs, the edtech platform that makes entry-level hiring easier for companies in India. It aims to upskill early graduates for entry level private jobs across domains such as sales, customer support, accounting, etc. Prior to founding Able Jobs, Siddharth was a product management professional. He used to be a co-founder for Sworlite and Plato, a college startup and a chat app for 1-1 career mentoring. And an Associate Product Manager at Playment and a Product Manager at Udacity respectively.MORE: https://aerowong.com/ttc21-siddharth-srivastava/

MLOps Coffee Sessions #162 with Soham Chatterjee, From LLMs to TinyML: The Dynamic Spectrum of MLOps co-hosted by Abi Aryan. // Abstract Explore the spectrum of MLOps from large language models (LLMs) to TinyML. Soham highlights the difficulties of scaling machine learning models and cautions against relying exclusively on open AI's API due to its limitations. Soham is particularly interested in the effective deployment of models and the integration of IoT with deep learning. He offers insights into the challenges and strategies involved in deploying models in constrained environments, such as remote areas with limited power and utilizing small devices like Arduino Nano. // Bio Soham leads the machine learning team at Sleek, where he builds tools for automated accounting and back-office management. As an electrical engineer, Soham has a passion for the intersection of machine learning and electronics, specifically TinyML/Edge Computing. He has several courses on MLOps and TinyMLOps available on Udacity and LinkedIn, with more courses in the works. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Abi on LinkedIn: https://www.linkedin.com/in/goabiaryan/ Connect with Soham on LinkedIn: https://www.linkedin.com/in/soham-chatterjee

TODAY'S GUEST   Irene Au is Design Partner at Khosla Ventures, where she works with early-, mid-, and late-stage startup CEOs. She is dedicated to raising the strategic value of design and user research within software companies through better methods, practices, processes, leadership, talent, and quality. Irene has unprecedented experience elevating the strategic importance of design within technology companies, having built and led the entire User Experience and Design teams at Google, Yahoo!, and Udacity. She began her career as an interaction designer at Netscape Communications, where she worked on the design of the internet's first commercial web browser.   Irene also teaches yoga at Avalon Yoga Center in Palo Alto where she is among the teacher training program faculty and is a frequent author and speaker on mindfulness practices, design, and creativity. An adjunct lecturer at Stanford University, she teaches product design in the mechanical engineering department. Irene also serves as a trustee for the Smithsonian Cooper Hewitt Museum of Design.   Irene authored the definitive O'Reilly book, Design in Venture Capital, and her popular essays can be found on Medium. She has been featured in WIRED magazine, Fast Company magazine, CommArts magazine, and on the cover of Mindful magazine.   EPISODE SUMMARY   In this conversation we talk about: Developing listening skills as an introspective child, and how feeling like an outsider helped her develop those skills. Her electrical engineering studies, and her transition into looking at how technology influences society and people and how we live.  Her time at Netscape, and tying together the products for a consistent look and feel across a suite of products that came out at the time called Netscape Communicator.  Her move from Netscape to Yahoo!, and what went wrong for Yahoo! as a company trying to find its way. Her time at Google as we look at it from all angles. What was the state of design at Google before she joined and what were the changes she tried to implement as she brought human-centered design and practices to Google? Hiring strategies, staff training, and how design workshops ultimately became the Design Sprint at Google. What is design and what is a designer? And the role of the designer in venture capital.   I think my greatest takeaway from this interview is this sense of hope that someone like Irene is able to walk into these very "techy" cultures and produce real change. And all it takes is really showing the value of the work and being willing to engage and promote better practices. I think Irene will be an inspiration to many non-engineers who find themselves in heavy engineering cultures and want to make a contribution.    This conversation with Irene is one of many weekly conversations we already have lined up for you with thinkers, best-selling authors, designers, makers, scientists, impact entrepreneurs, and others who are working to change our world for the better. So please follow this podcast on your favorite podcast app, or head over to remakepod.org to subscribe.   And now, let's jump right in with Irene Au.   TIMESTAMP CHAPTERS   [5:54] Life in the Present [7:08] Early Childhood Driving Forces [9:40] A Journey to Design [13:20] Entering Netscape [16:00] The Challenges of the Early Internet [19:23] A Transition From Netscape to Yahoo! [22:58] The Infrastructure of Yahoo! [30:14] Good Design Versus Bad Design [34:04] The Winners and the Failures [39:48] Infusing Design With Google [45:55] Design Thinking Workshops [52:13] A Sideways Career Move [58:35] What is Design Today? [1:05:26] The Human Meaning of Design [1:08:58] A Short Sermon   EPISODE LINKS Irene's Links

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

Irene Au is Design Partner at Khosla Ventures, working with early, mid, and late-stage startup CEOs. She is dedicated to raising the value of design and user research within software companies through better methods, practices, processes, leadership, and talent. Through her mentorship of the next generation of designers, she helps companies build an empathetic understanding of user needs, inspiring and informing product design and experiences. Irene has unprecedented experience elevating the strategic importance of innovation within technology companies, having built and led the entire User Experience and Design teams at Google, Yahoo!, and Udacity. She began her career as an interaction designer at Netscape Communications, where she worked on the design of the internet's first commercial web browser.   For ten years, Irene taught yoga at Avalon Yoga Center in Palo Alto, where she also is among the teacher training program faculty. She is a frequent author and speaker on mindfulness practices, design, and creativity. She is an adjunct lecturer at Stanford University and teaches Product Design in the mechanical engineering department. Irene is also a trustee for the Cooper Hewitt Smithsonian Museum of Design. Irene authored the definitive O'Reilly book, Design in Venture Capital, and her popular essays can be found on Medium. In addition, she has been featured in Wired magazine, Fast Company magazine, CommArts magazine, and on the cover of Mindful magazine.Irene graduated magna cum laude from the Honors College at the University of South Carolina in Electrical and Computer Engineering. She received her Master's Degree from the Department of Mechanical and Industrial Engineering, focusing on Human-Computer Interaction at the University of Illinois at Urbana-Champaign. In this episode, Irene Au shared great insights on The Psychology of Design: How Human Behaviour and emotion influence Design Decisions. We started the episode by defining the intersection of psychology and design and what fundamental principles designers should consider when adding human behaviour and emotion to their work. Then Irene shared a few product examples where psychology played a crucial role in shaping the final product. We then discussed how designers could use colour, typography, and other visual elements to evoke specific emotional responses in users and the best practices for doing so effectively. In the end, Irene spoke on how cultural and societal factors influence design decisions and what strategies designers can use to create designs that resonate with diverse audiences. Irene Au Websitehttps://medium.com/design-your-life Book Recommendation by Irene Au The Design of Everyday Things - Don Norman The Creative Act: A Way of Being - Rick Rubin Geometry of Design - Kimberly Elam Thank you for listening to this episode of Nodes of Design. We hope you enjoy the Nodes of Design Podcast on your favourite podcast platforms- Apple Podcast, Spotify, Google Podcasts, Amazon Music, and many more. If this episode helped you understand and learn something new, please share and join the knowledge-sharing community #Spreadknowledge. This podcast aims to make design education accessible to all. Nodes of Design is a non-profit and self-sponsored initiative by Tejj.

歡迎留言告訴我們你對這一集的想法： https://open.firstory.me/user/cl81kivnk00dn01wffhwxdg2s/comments Topic: In Race for Tuition-Free College, New Mexico Stakes a Claim As universities across the United States face steep enrollment declines, New Mexico's government is embarking on a pioneering experiment to fight that trend: tuition-free higher education for all state residents. 隨著美國各地大學入學人數急劇下滑，新墨西哥州政府正著手進行一項開創性實驗來應對這一趨勢：為全州居民提供免學費高等教育。 + Sure? After President Joe Biden's plan for universal free community college failed to gain traction in Congress, New Mexico, one of the nation's poorest states, has emerged with perhaps the most ambitious plans as states scramble to come up with their own initiatives. 在美國總統拜登的全民免費社區大學計畫未能獲得國會支持後，美國最窮的州之一新墨西哥州提出的計畫，可能是各州爭相提出行動倡議中最具雄心的一個。 A new state law approved in a rare show of bipartisanship allocates almost 1% of the state's budget toward covering tuition and fees at public colleges and universities, community colleges and tribal colleges. All state residents from new high school graduates to adults enrolling part-time will be eligible regardless of family income. The program is also open to immigrants regardless of their immigration status. 一項新的州法在兩黨罕見合作下通過，將州預算的1%用於支付公立大學、社區大學與部落學院的學費。所有州民，從剛畢業的高中生到參加兼職教育的成人都有資格參加，無論家庭收入。該計畫也向移民開放，無論他們的移民身分如何。 Some legislators and other critics question whether there should have been income caps and whether the state, newly flush with oil and gas revenue, can secure long-term funding to support the program beyond its first year. The legislation, which seeks to treat college as a public resource similar to primary and secondary education, takes effect in July. 一些議員和其他批評人士質疑是否應設所得限制，以及剛獲大量石油與天然氣收入的該州是否能在計畫實施第一年後，獲得長期資金支持。這項立法將於7月生效，旨在將大學視為與中小學教育類似的公共資源。 Although nearly half the states have embraced similar initiatives that seek to cover at least some tuition expenses for some students, New Mexico's law goes further by covering tuition and fees before other scholarships and sources of financial aid are applied, enabling students to use those other funds for expenses such as lodging, food or child care. 儘管近半的州已採取類似舉措，想幫一些學生支付至少部分學費和雜費，新墨西哥州法律更進一步，在申請其他獎學金和學費補助前，先支付學雜費，讓學生能使用其他資金，支付如住宿、食物或兒童照顧等費用。 “The New Mexico program is very close to ideal,” said Michael Dannenberg, vice president of strategic initiatives and higher education policy at the nonprofit advocacy group Education Reform Now. Considering the state's income levels and available resources, he added that New Mexico's program is among the most generous in the country. 非營利倡議組織Education Reform Now策略倡議暨高教政策副總裁丹能貝格說：「新墨西哥的計畫非常貼近理想。」他表示，考量收入水準與可用資源，新墨西哥州的計畫是全美最慷慨的。 Dannenberg emphasized that New Mexico is going beyond what larger, more prosperous states like Washington and Tennessee have already done. Programs in other states often limit tuition assistance to community colleges, exclude some residents because of family income or impose conditions requiring students to work part time. 丹能貝格強調，新墨西哥州正超越華盛頓和田納西這些更大、更繁榮的州所做的事。其他州通常限制對社區大學的學費補助，因家庭收入排除一些州民，或要求學生兼職。Source article: https://udn.com/news/story/6904/6329103 Next Article Topic: Colleges Slash Budgets in the Pandemic,With ‘Nothing Off-Limits' Ohio Wesleyan University is eliminating 18 majors. The University of Florida's trustees last month took the first steps toward letting the school furlough faculty. The University of California, Berkeley, has paused admissions to its doctoral programs in anthropology, sociology and art history. 美國俄亥俄衛斯理大學取消了18個科系。佛州大學董事會9月採取初步措施，目標是讓校方有權放教師無薪假。柏克萊加州大學則暫停招收人類學、社會學和藝術史的博士班學生。 As it resurges across the country, the coronavirus is forcing universities large and small to make deep and possibly lasting cuts to close widening budget shortfalls. By one estimate, the pandemic has cost colleges at least $120 billion, with even Harvard University, despite its $41.9 billion endowment, reporting a $10 million deficit that has prompted belt tightening. 由於全美各地新冠肺炎疫情再度惡化，美國各大學不論規模大小，都被迫大砍支出，以彌補逐漸擴大的預算缺口，刪減的支出可能長期都不會恢復。有人估計，疫情至少使美國各大學合計損失1200億美元，就連坐擁419億美元辦學基金的哈佛大學也出現1000萬美元預算赤字，被迫勒緊褲帶。 The persistence of the economic downturn is taking a devastating financial toll, pushing many to lay off or furlough employees, delay graduate admissions and even cut or consolidate core programs like liberal arts departments. 經濟持續疲軟造成極其嚴重的財務災情，迫使許多大學裁員或放無薪假，推遲研究所學生入學，甚至取消或合併文科等核心學程。 The University of South Florida announced last month that its College of Education would become a graduate school only, phasing out undergraduate education degrees to help close a $6.8 million budget gap. In Ohio, the University of Akron, citing the coronavirus, successfully invoked a clause in its collective-bargaining agreement in September to supersede tenure rules and lay off 97 unionized faculty members. 南佛州大學上個月宣布，其教育學院將只留下研究所，分階段取消大學部，以彌補680萬美元的預算缺口。在俄亥俄州，艾克朗大學以疫情為由，在9月成功援用團體協約一項條款取代任期規則，裁掉97名加入工會的教師。 “We haven't seen a budget crisis like this in a generation,” said Robert Kelchen, a Seton Hall University associate professor of higher education who has been tracking the administrative response to the pandemic. “There's nothing off-limits at this point.” 西東大學高等教育副教授柯爾欽一直在關注校方對疫情的反應，他說：「這是一個世代以來從未見過的預算危機，在這種關頭，沒有什麼不能碰。」 Even before the pandemic, colleges and universities were grappling with a growing financial crisis, brought on by years of shrinking state support, declining enrollment, and student concerns with skyrocketing tuition and burdensome debt. Now the coronavirus has amplified the financial trouble systemwide, though elite, well-endowed colleges seem sure to weather it with far less pain. 早在疫情爆發前，美國大專院校就為日益嚴重的財務危機而掙扎，原因是州政府補助日漸減少，學生註冊數下滑而且介意學費高漲和學貸負擔沉重，如今，疫情擴大了整個高教體系財務問題，不過，辦學基金厚實的菁英大學似乎可度過難關，且承受的痛苦會少得多。 “We have been in aggressive recession management for 12 years — probably more than 12 years,” Daniel Greenstein, chancellor of the Pennsylvania State System of Higher Education, told his board of governors as they voted to forge ahead with a proposal to merge a half-dozen small schools into two academic entities. 賓州高等教育體系董事會表決通過，大力推動將6個小規模學院併為兩個學術單位，當時總校長葛林斯坦對董事會說：「我們積極從事於衰退問題管理已有12年，應該還不止12年。」 Source article: https://paper.udn.com/udnpaper/POH0067/359091/web/ Next Article Topic: Remember the MOOCs? After Near-Death, They're Booming Sandeep Gupta, a technology manager in California, sees the economic storm caused by the coronavirus as a time “to try to future-proof your working life.” So he is taking an online course in artificial intelligence. 美國加州科技業經理古普塔認為，新冠肺炎引發的經濟風暴是「防止職業生涯被未來淘汰」的時機，所以修讀了一門關於人工智慧的線上課程。 Dr. Robert Davidson, an emergency-room physician in Michigan, says the pandemic has cast “a glaring light on the shortcomings of our public health infrastructure.” So he is pursuing an online master's degree in public health. 密西根州急診室醫師戴維森說，疫情「使我們公衛基礎設施的弱點顯而易見」，所以他在修讀線上公衛碩士學位。 Children and college students aren't the only ones turning to online education during the coronavirus pandemic. Millions of adults have signed up for online classes in the past two months, too — a jolt that could signal a renaissance for big online learning networks that had struggled for years. 在新冠肺炎大流行期間轉而接受線上教育者，不限於兒童和大學生。過去兩個月，數以百萬計的成人也註冊參加線上課程，這令人驚訝的事實可能意味苦撐多年的大型線上學習網路即將再起。 Coursera, in which Gupta and Davidson enrolled, added 10 million new users from mid-March to mid-May, seven times the pace of new sign-ups in the previous year. Enrollments at edX and Udacity, two smaller education sites, have jumped by similar multiples. 古普塔與戴維森註冊的Coursera，從3月中旬到5月中旬增加1000萬新用戶，是去年同期新增註冊人數的七倍。edX與Udacity這兩個規模較小的教育網站，新註冊人數也以類似倍數暴增。 “Crises lead to accelerations, and this is best chance ever for online learning,” said Sebastian Thrun, a co-founder and chairman of Udacity. Udacity共同創辦人兼董事長史朗說：「危機導致改變加速發生，這是線上學習業未曾遇過的最佳良機。」 Coursera, Udacity and edX sprang up nearly a decade ago as high-profile university experiments known as MOOCs, for massive open online courses. They were portrayed as tech-fueled insurgents destined to disrupt the antiquated ways of traditional higher education. But few people completed courses, grappling with the same challenges now facing students forced into distance learning because of the pandemic. Screen fatigue sets in, and attention strays. Coursera、Udacity和edX近十年前出現，嘗試與大學合作推出線上課程而備受矚目，這類課程名為 「大規模開放線上課程」，簡稱「磨課師」。這種課程被描述為獲得科技支持的反叛者，意在顛覆傳統高等教育過時的授課方式。不過，很少有人能修完課程，這些人窮於應付的挑戰，與目前因為疫情被迫遠距學習的學生一樣。長時間盯著螢幕造成疲勞，而且注意力難以集中。 But the online ventures adapted through trial and error, gathering lessons that could provide a road map for school districts and universities pushed online. The instructional ingredients of success, the sites found, include short videos of six minutes or less, interspersed with interactive drills and tests; online forums where students share problems and suggestions; and online mentoring and tutoring. 不過這些線上企業透過反覆試驗來調整，並且積聚了可供被迫線上授課的學區和大學參考的知識和經驗。這些網站發現，線上授課成功的要素包括：短片時間不超過6分鐘，穿插互動練習和測驗；設立線上論壇，讓學生提出問題和建議；並提供線上指導和輔導。 A few top-tier universities, such as the University of Michigan and the Georgia Institute of Technology, offer some full degree programs through the online platforms. 有幾所頂尖大學，如密西根大學和喬治亞理工學院，透過這些線上平台提供一些正式學位學程。 While those academic programs are available, the online schools have tilted toward skills-focused courses that match student demand and hiring trends. 這些線上學校雖提供學術性學程，卻更傾向開設符合學生需要和雇用趨勢的技能課程。 The COVID-19 effect on online learning could broaden the range of popular subjects, education experts say. But so far, training for the tech economy is where the digital-learning money lies. With more of work and everyday life moving online — some of it permanently — that will probably not change. 教育專家指出，新冠肺炎可能會使線上課程熱門科目範圍變得更廣。不過到目前為止，針對科技經濟提供的訓練課程，才是數位教學業的金雞母。隨著更多的工作和日常生活轉移到線上進行，有些是永遠轉到線上，這種情況大概不會改變。 Source articles: https://paper.udn.com/udnpaper/POH0067/354879/web/ Powered by Firstory Hosting

Tech News & AMA #22 with our community members Yousssouf, Kawtar, Abderahim, Otmane and Mohammed. During this episode, we discuss last tech news related to AI, GPT-3, and much more. Guets Kawtar Choubari Mohammed Daoudi Soubai Abderahim Otmane Fettal Notes 0:00:00 - Introduction and welcoming 0:04:00 - Guests learning during the last period and Productivity in Ramadan. 0:42:50 - ChatGpt Plugins, how is will be used in the future? and the launch of Bard Google assistant. 1:11:00 - How nerves vs excited our guests about AI revolution we are living in? 1:27:00 - Spark of AGI with GPT-4. 1:47:00 - QA 2:10:00 - Future of education with AI revolution. 2:23:00 - WrapUp & Goodbye. Links T3 FuturePedia Sam Altman: OpenAI CEO on GPT-4, ChatGPT, and the Future of AI | Lex Fridman Podcast Bard Authjs 'Sparks of AGI' - Bombshell GPT-4 Paper: Fully Read w/ 15 Revelations Menara Programme Google Summer code Udacity scholarships Google Developer Student Clubs markprompt Embeddings open ai docs Humata Prepared and Presented by Youssouf EL Azizi

When was the last time you talked about your broader career vision in a one-on-one? This week on the podcast, we're talking about why it's so important for managers to have big picture career conversations with their direct reports. Siya Raj Purohit discusses her tips and tricks to coach teammates and develop a strong career vision. Purohit is the Global EdTech& Workforce Development Category Lead at Amazon Web Services, where she coaches team members to follow their unique career pathways. Purohit's strong career vision has shaped many of her professional steps, starting at age 19 when she wrote a book about the skills gap in the field of engineering. She has worked throughout the EdTech industry at Udacity and Springboard, and she is also the Co-founder and General Partner at Pathway Ventures. Learn more about Udemy Business at https://bit.ly/udemy-podcast.

1. ChatGPT, Pt. 1: APIsOpenAI launches an API for ChatGPT, plus dedicated capacity for enterprise customers | TechCrunchIntroducing Q-Chat, the world's first AI tutor built with OpenAI's ChatGPT | QuizletChatGT, Pt 2: Ramifications of ChatGPTThe evolution of ChatGPT will fuel the future of higher education, says Udacity's Sebastian ThrunWill ChatGPT Make Students Turn Away From Homework-Help Services? | EdSurge News2. Federal Guidelines on TPS DelayedDepartment of Education Delays Guidance on TPS Expansion3. Interesting AcquisitionsIXL Learning Acquires Teachers Pay Teachers, the World's Largest Platform for Educator-Created ContentPaper™ acquires MajorClarity to Create a Comprehensive Career & College Readiness PlatformEducation services company Perdoceo acquires coding bootcamp school Coding Dojo for $52.8M4. TikTok Launches New Edtech Platform GeniusJoy for MathTikTok's parent ByteDance is building a new 'AI-based' edtech platform called GeniusJoy and is hiring in Los Angeles and SingaporeFrom TikTok to Trigonometry: Could ByteDance Corner the Market on Edtech?Funding RoundsNew Markets Venture Partners Raises Over $160 Million Chinese platform Nowcoder raises $50mStudentFinance secures $41m for ISAs in Europe Moroccan KOOLSKOOLS raises $960,000 

Siya Raj Purohit is the Global Edtech & Workforce Development Lead at Amazon's AWS Marketplace and a General Partner at Pathway Ventures. She's an operator-investor in the Edtech and Future of Work sectors who helps grow & invest in companies that drive economic mobility through innovative models of earning, learning, and community building. Siya is an edtech veteran and a true insider, as an early employee at Udacity & Springboard, a graduate of Harvard GSE's TIE program, and an author; she published her first book: “Engineering America” while she was an undergraduate at the University of Texas at Austin. Resource Recommendations from SiyaMatt Tower's Ed Tech Thoughts newsletterThe work of business professor and author Adam Grant

Happy Holidays from all of us at Google! This week, hosts Carter Morgan, Stephanie Wong, and Max Saltonstall are sharing their favorite moments from the year! From great partnerships with national companies, new releases in some of your favorite Google software tools, and a trillion digits of pi, we're breaking down some 2022 highlights and introducing special guest Podcast Producer Kevin McCormack to help with a fun podcast trivia game! Carter Morgan Carter Morgan is Developer Advocate for Google Cloud, where he creates and hosts content on Google's Youtube channel, co-hosts several Google Cloud podcasts, and designs courses like the Udacity course “Scalable Microservices with Kubernetes” he co-created with Kelsey Hightower. Carter Morgan is an international standup comedian, who's approach of creating unique moments with the audience in front of him has seen him perform all over the world, including in Paris, London, the Melbourne International Comedy Festival with Joe White. And in 2019, and the 2019 Edinburgh Fringe Festival. Previously, he was a programmer for the USAF and Microsoft. Stephanie Wong Stephanie Wong is a Developer Advocate focusing on online content across all Google Cloud products. She's a host of the GCP Podcast and the Where the Internet Lives podcast, along with many GCP Youtube video series. She is the winner of a 2021 Webby Award for her content about data centers. Previously she was a Customer Engineer at Google and at Oracle. Outside of her tech life she is a former pageant queen and hip hop dancer and has an unhealthy obsession with dogs. Max Saltonstall Max Saltonstall is a Developer Relations Engineer at Google Cloud. He is a father, teacher, storyteller, speaker, educator, nefarious villain, game designer, juggler, and is only part zombie. Cool things of the week Boost medical discoveries with AlphaFold on Vertex AI blog 6 common mistakes to avoid in RESTful web API Design blog Marketing Analytics With Google Cloud blog Our Favorite Episodes of 2022 Stephanie's Favorites GCP Podcast Episode 290: Resiliency at Shopify with Camilo Lopez and Tai Dickerson podcast GCP Podcast Episode 315: Cloud Functions (2nd gen) with Jaisen Mathai and Sara Ford podcast GCP Podcast Episode 307: FinOps with Joe Daly podcast Carter's Favorites GCP Podcast Episode 308: New Pi World Record with Emma Haruka Iwao and Sara Ford podcast GCP Podcast Episode 327: ML/AI Data Science for Data Analytics with Jed Dougherty and Dan Darnell podcast GCP Podcast Episode 289: Cloud Security Megatrends with Phil Venables podcast Max's Favorites GCP Podcast Episode 316: Google Cloud for Higher Education with Laurie White and Aaron Yeats podcast GCP Podcast Episode 317: Launching Products at Google Cloud with Anita Kibunguchy-Grant and Gabe Weiss podcast GCP Podcast Episode 325: Digital Sovereignty with Archana Ramamoorthy and Julien Blanchez podcast Stephanie's Honorable Mentions GCP Podcast Episode 323: Next 2022 with Forrest Brazeal and Stephanie Wong podcast GCP Podcast Episode 298: Celebrating Women's History Month with Vidya Nagarajan Raman podcast Carter's Honorable Mentions GCP Podcast Episode 312: Managed Service for Prometheus with Lee Yanco and Ashish Kumar podcast GCP Podcast Episode 290: Resiliency at Shopify with Camilo Lopez and Tai Dickerson podcast Max's Honorable Mentions GCP Podcast Episode 326: Assured Workloads with Key Access Justifications with Bryce Buffaloe and Seth Denney | Google Cloud Platform Podcast podcast Hosts Stephanie Wong, Carter Morgan and Max Saltonstall

What should a newsroom report on? Does journalism know its own purpose? Do we? What ethics should we live by, and why? Samarth Bansal joins Amit Varma in episode 299 of The Seen and the Unseen to talk about living the examined life, and asking the fundamental questions. (For full linked show notes, go to SeenUnseen.in.) Also check out: 1. Samarth Bansal on Twitter and his own website. 2. The Interval -- Samarth Bansal's newsletter. 3. Truth Be Told -- Samarth Bansal's Food and Fitness newsletter with Shashank Mehta and others. 4. Journalists refer to themselves as storytellers. Is that a mistake? -- Samarth Bansal. 5. Why the event-oriented structure of news doesn't help in understanding how the world works -- Samarth Bansal. 6. A different way to think about Indian media -- Samarth Bansal. 7. Sugar-coated conspiracies: How ‘publication bias' amplifies half-truths -- Samarth Bansal. 8. How I approach and manage my freelance journalism career -- Samarth Bansal. 9. Thoughts and observations on data journalism in India -- Samarth Bansal. 10. Why I am relearning statistics -- Samarth Bansal. 11. The Wire's TekFog investigation: A futile search for evidence -- Samarth Bansal. 12. Indian pollsters are doing fine. Here is how forecasts work -- Samarth Bansal. 13. Lessons learnt from my 52-week workout streak -- Samarth Bansal. 14. The pursuit of truth with Samarth Bansal -- An interview by In Old News. 15. The Prem Panicker Files -- Episode 217 of The Seen and the Unseen. 16. Amitava Kumar Finds the Breath of Life — Episode 265 of The Seen and the Unseen. 17. Chandrahas Choudhury's Country of Literature -- Episode 288 of The Seen and the Unseen. 18. Rukmini Sees India's Multitudes -- Episode 261 of The Seen and the Unseen (w Rukmini S). 19. The Importance of Data Journalism — Episode 196 of The Seen and the Unseen (w Rukmini S). 20. Pramit Bhattacharya Believes in Just One Ism — Episode 256 of The Seen and the Unseen. 21. The Importance of the 1991 Reforms -- Episode 237 of The Seen and the Unseen (w Shruti Rajagopalan and Ajay Shah). 22. Strangers Drowning -- Larissa MacFarquhar. 23. Larissa MacFarquhar on Getting Inside Someone's Head -- Episode 58 of Conversations With Tyler. 24. Dil Dhadakne Do -- Zoya Akhtar. 25. Kapoor & Sons -- Shakun Batra. 26. Why are India's housewives killing themselves? -- Soutik Biswas. 27. Tum Itna Jo Muskura Rahe Ho -- Jagjit Singh's ghazal from Arth. 28. Alice Evans Studies the Great Gender Divergence -- Episode 297 of The Seen and the Unseen. 29. Amit Varma's tweet on winning the Asian Championships of Match Poker. 30. Wanting — Luke Burgis. 31. The Life and Times of Nilanjana Roy -- Episode 284 of The Seen and the Unseen. 32. Dead Poets Society -- Peter Weir. 33. Amusing Ourselves to Death — Neil Postman. 34. Deep Work — Cal Newport. 35. Ira Glass on the Creative Process. 36. The Parable of the Pottery Class. 37. Behave -- Robert Sapolsky. 38. The Biology of Good and Evil -- Robert Sapolsky speaks to Sam Harris in episode 91 of The Making Sense Podcast. 39. Robert Sapolsky's biology lectures on YouTube. 40. The Confidence Gap — Katty Kay and Claire Shipman. 41. The Overconfidence Game -- Episode 6 of Against the Rules with Michael Lewis. 42. Men Explain Things to Me -- Rebecca Solnit. 43. ‘Let Me Interrupt Your Expertise With My Confidence' — New Yorker cartoon by Jason Adam Katzenstein. 44. Free Will on Wikipedia, Brittanica and Stanford Encyclopedia of Philosophy. 45. Free Will -- Sam Harris. 46. The Blind Watchmaker -- Richard Dawkins. 47. The CBS 60 Minutes documentary on the Indian Institute of Technology. 48. Steve Jobs' 2005 Stanford Commencement Address. 49. A Student's Guide to Startups -- Paul Graham. 50. Paul Graham's essays. 51. Coursera and Udacity. 52. The Last Lecture -- Randy Pausch. 53. The Gell-Mann Amnesia Effect. 54. The Blank Slate — Steven Pinker. 55. The Moral Animal -- Robert Wright. 56. Ezra Klein Interviews Noam Chomsky. 57. Dhanya Rajendran Fights the Gaze -- Episode 267 of The Seen and the Unseen. 58. Tamasha -- Imtiaz Ali. 59. The Turn of the Tortoise -- TN Ninan. 60. Bad Blood -- John Carreyrou. 61. Narendra Modi takes a Great Leap Backwards — Amit Varma (on Demonetisation). 62. Enabled by technology, young Indians show what it means to be a citizen -- Amit Varma. 63. Episodes of The Seen and the Unseen with Aakar Patel: 1, 2. 64. Adults in the Room -- Yanis Varoufakis. 65. Larry Summers at Harvard, Wikipedia, Twitter and his own website. 66. India's 50 Most Powerful People of 2009 -- List by Business Week including, heh, Amit Varma. 67. The theory of the interlocking public. 68. CRISPR gene editing. 69. Genetic Engineering -- Episode 165 of The Seen and the Unseen (w Shambhavi Naik). 70. The Internet's Own Boy: The Story of Aaron Swartz -- Brian Knappenberger. 71. I Hate the News -- Aaron Swartz. 72. Everybody Loves a Good Drought -- P Sainath. 73. Why everyone hates the mainstream media -- Andrew Potter. 74. Income Tax department raids Dainik Bhaskar premises across the country -- The Hindu. 75. Apar Gupta and Internet Freedom Foundation. 76. The Revolt of the Public -- Martin Gurri. 77. The best stats you've ever seen -- Hans Rosling. 79. Lessons from an Ankhon Dekhi Prime Minister — Amit Varma. 80. Introduction to the Human Brain -- Nancy Kanwisher. 81. Future Shock -- Alvin Toffler. 82. The Trial of the Chicago 7 -- Aaron Sorkin. Check out Amit's online course, The Art of Clear Writing. And subscribe to The India Uncut Newsletter. It's free! Episode art: ‘Reflection' by Simahina.

698: In a fireside chat from our September 2022 Metis Strategy Digital Symposium, Peter High speaks with Gabe Dalporto, CEO of Udacity, to discuss the skills that will be necessary for employees in the Digital Age and how companies can foster the upskilling essential to keep pace with their digital transformations. Gabe looks at the current state of digital skills and where Udacity fits in the spectrum of overall education. He describes the three main skill sets that will be crucial for companies to train employees in, the path ahead for employees in non-technical roles, and the best practices for companies developing their own in-house digital academies. Finally, Gabe advises incoming college students on what skills to learn for their future careers.

698: In a fireside chat from our September 2022 Metis Strategy Digital Symposium, Peter High speaks with Gabe Dalporto, CEO of Udacity, to discuss the skills that will be necessary for employees in the Digital Age and how companies can foster the upskilling essential to keep pace with their digital transformations. Gabe looks at the current state of digital skills and where Udacity fits in the spectrum of overall education. He describes the three main skill sets that will be crucial for companies to train employees in, the path ahead for employees in non-technical roles, and the best practices for companies developing their own in-house digital academies. Finally, Gabe advises incoming college students on what skills to learn for their future careers.