Podcast appearances and mentions of ash fontana

Ash Fontana discusses his book "The AI-First Company," and how to compete and win with Artificial Intelligence. Ash became one of the most recognized startup investors in the world after launching online investing at AngelList. He then became a Managing Director of Zetta, the first investment fund that focused on AI. He has appeared in Fast Company, Bloomberg, Forbes, and CNBC, among others. Listen for three action items you can use today. Host, Kevin Craine Do you want to be a guest? DigitalTransformationPodcast.net/guest

Episode Summary:In this episode of First Cheque hosts Cheryl Mack and Maxine Minter sit down with the distinguished investor Ash Fontana to explore the intricacies of early-stage investing and the evolving landscape of artificial intelligence (AI). The conversation delves into Fontana's diverse experiences, ranging from his formative years building web-based marketplaces to his critical role in establishing the AI investment frontier.Fontana shares a captivating narrative of his investment philosophy, advocating for the significance of first-check investments in shaping the trajectories of startups. With an emphasis on determining the long-term competitive advantages of AI ventures, the discussion uncovers the importance of specialization and the strategic deployment of venture funds amidst a rapidly transforming technology sector. Key themes revolve around adapting venture capital models, the intersection of network building, and the fortune of investment careers, providing listeners with a wealth of actionable insights.Key Takeaways:First Cheque investments are critical in establishing a startup's potential and culture.AI investments should focus on companies that exhibit a sustainable competitive advantage, potentially characterized by data network effects.Venture Capital (VC) requires specialisation, especially in fast-evolving fields like AI, to keep pace with rapid advancements and make informed investment decisions.The traditional VC model faces criticism for its performance and lack of innovation; exploring models with lower fees and higher carry could better align incentives.Building and maintaining a robust network is essential for success and longevity in the venture capital industry.Notable Quotes:"The existence proof of adding value is that you allowed the entity through which all subsequent value is created to exist.""As soon as you're competing, you're losing. You should just aim to be in non-competitive situations.""I invest in technology cycles, not market cycles.""I find it really hard to work for other people and in big companies, but I would have worked for a big growth stage or growth stage fund, like Insight, Summit, Bain, one of them.""The bigger the network you can build, the better, the more useful you will be, and therefore, the more lucky you will get."Resources:Ash Fontana's book: "The AI-First Company"Ash Fontana's LinkedIn profileThanks to our sponsors for helping to make this episode of First Cheque possible:Vanta: Join 7,000 global companies like Atlassian and Dovetail that use Vanta to build trust and prove security in real-time. Get 10% offScendar: Scendar is the OG startup accounting firm in Australia. Free 1-hour consultation about your Business' growth plans and finance needs. https://dayone.fm/scendarTuro: Turo is the world's largest carsharing marketplace and it's the perfect app for travel. Download the Turo app and book cars from $38/day Download the Turo app and book cars from $38/day. https://dayone.fm/turo

Interview mit Philipp Adamidis, Co-Founder und CEO von QuantPi In der Nachmittagsfolge begrüßen wir heute Philipp Adamidis, Co-Founder und CEO von QuantPi, und sprechen mit ihm über die erfolgreich abgeschlossene Pre-Seed-Finanzierungsrunde in Höhe von 2,5 Millionen Euro. QuantPi hat eine Plattform entwickelt, mit der Unternehmen sicherstellen können, dass rechtliche, wirtschaftliche, ethische und Reputationsrisiken im Zusammenhang mit ihren KI-Lösungen identifiziert, bewertet und entschärft werden. Zahlreiche Initiativen zur Regulierung und Standardisierung von KI, wie beispielsweise der Artificial Intelligence Act der Europäischen Union (AIA), machen es notwendig, dass KI-basierte Produkte effizient, sicher und konform sind. Durch den AIA werden Unternehmen zum Beispiel mit einer Geldstrafe von bis zu 6% des weltweiten Jahresumsatzes belegt, wenn sie die getroffenen Entscheidungen ihrer künstlichen Intelligenz nicht erklären können. Die Plattform sammelt dafür Artefakte und Metriken über KI-Systeme in den wichtigsten Risiko- und Prüfungsdimensionen und lässt sich nahtlos mit modernen ML- und BI-Tools integrieren. Nach einer Forschungszeit von knapp 7 Jahren wurde QuantPi im Jahr 2020 von führenden Köpfen der Mathematik, Informatik und Wirtschaftswissenschaften als Spin-off des CISPA-Helmholtz-Zentrums für Informationssicherheit und der Universität des Saarlandes gegründet. Ursprünglich sollte lediglich eine Black-Box-KI durch eXplainable AI verständlich gemacht werden. Mit der Forschung und Entwicklung hat sich die Technologie allerdings zu einer ganzheitlichen Plattform entwickelt, die KI sicherer und für die verschiedenen Akteure in Gesellschaft, Forschung und Wirtschaft verständlicher machen kann. Die Saarbrückener Entwicklungsplattform für Responsible AI hat nun in einer Pre-Seed-Finanzierungsrunde 2,5 Millionen Euro unter der Führung von Capnamic eingesammelt. Der deutsche Early-Stage Venture Capital Investor stellt seinen Portfoliounternehmen neben der finanziellen Unterstützung auch sein globales Netzwerk, Hands-On Support und Mentoring zur Verfügung. First Momentum, der Autor von „The AI-First Company“ namens Ash Fontana, der Ex-Instana-Gründer Mirko Novaovic und weitere Business Angels haben sich ebenfalls an der Runde beteiligt. Das frische Kapital möchte QuantPi für die Erweiterung des Teams und den Beginn der Kommerzialisierung der Plattform mit Fokus auf hochsensible und aufgabenkritische Anwendungsfälle in den Bereichen Finanzdienstleistungen, Gesundheitswesen sowie autonomes Fahren einsetzen.

On this podcast I am joined by Ash Fontana, AI start-up investor with Zetta Venture Partners and technology industry thought leader, to talk about his new book: The AI First Company: How to compete and win with Artificial Intelligence. If you are focused on trying to transform your company into an AI powered leader in your industry, Ash's book is going to end up being a well worn and dog eared resource that you will return to again and again!

Today's guest is Ash Fontana, Special Advisor at Zetta Venture Partners based in the Bay Area. After recently publishing his book, “The AI-First Company,” Ash joins us again on the show to discuss some of the core transferable lessons he's learned. Our topic for this episode is advantage. Ash discusses a way of thinking about building momentum around data and gaining long-term advantage as a result. This episode is one of two episodes Ash recently recorded with us. If you enjoyed today's episode, be sure to tune in to his second episode on The AI Consulting Podcast to gain insight on how services companies can turn into AI product companies. 

Ash Fontana discusses his book "The AI-First Company," and how to compete and win with Artificial Intelligence. Ash became one of the most recognized startup investors in the world after launching online investing at AngelList. He then became a Managing Director of Zetta, the first investment fund that focused on AI. He has appeared in Fast Company, Bloomberg, Forbes, and CNBC, among others. Listen for three action items you can use today. Host, Kevin Craine Do you want to be a guest?

Welcome to GroundTruth by Dogpatch Advisors, a podcast about company builders, leadership, and how operators use data to build the future of sales. To learn more, check out http://www.groundtruthpod.com (www.groundtruthpod.com) for other Ground Truth episodes and a deeper dive into each story.  In this episode, we talk to Ash Fontana, technology investor and author of the book The AI-First Company. Growing up in Australia, Ash began his path studying law and finance, then quickly turned into the tech space in Silicon Valley. His learnings from investing, building and selling his own startup and being early at Angelist, are distilled into his practical book The AI-First Company. In this book, Ash presents a completely new form of competitive advantage through AI for any kind of business. Learn all about Ash's book, his inspiration, the process behind it, and what he foresees for companies who adopt the AI-First model.  Podcast Summary: 01:01 -  Who is Ash Fontana? Growing up in Australia with Jesuit education and public speaking as his foundation. 03:15 - Ash's first tech companies: What he learned about handling data and how he went from law to full-time AI.  07:52 - The inspiration behind the book: How to put a completely new form of competitive advantage into actionable words, checklists, frameworks, and illustrations. 15:41 -  Data Leaning Effects and how to observe things at scale: Is there a potential for impactful dailies in this business model? 22:23 - Involving different experts in the process: How to build a culture and a feedback loop around the AI-First Model. 30:17 - What Ash hopes the book brings to people: Giving people the power of competitive advantage + Ash's next book.  Episode Resource: Find Ash on https://twitter.com/ashfontana?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor (Twitter )and  https://www.linkedin.com/in/ashfontana/?originalSubdomain=ch (LinkedIn) https://www.theaifirstcompany.com/ (The AI-First Company) https://www.amazon.com/-/es/Ash-Fontana/dp/0593330315/ref=sr_1_1?__mk_es_US=%C3%85M%C3%85%C5%BD%C3%95%C3%91&crid=10TMVI6W40X7T&dchild=1&keywords=the+ai+first+company&qid=1632519033&sprefix=the+ai+first%2Caps%2C200&sr=8-1 (The AI-First Company by Ash Fontana) Credits GroundTruth is a production of https://www.dogpatchadvisors.com/ (Dogpatch Advisors). This episode was written by Jack Buehrer from https://campfirelabs.co/ (Campfire Labs,) sound engineering and studio space provided by TJ Bonaventura and Julian Lewis from https://studiopodsf.com/ (StudioPod), editing and mixing by http://www.nodalab.com (Nodalab,) and video production by Nick Shaheen from https://www.abovetreelinestudios.com/ (Above Treeline Studios).

You can't go anywhere today without hearing the term “artificial intelligence” - governments, industry, and startups are thinking through how to build, leverage and harness AI on a daily basis. But what really is AI and how do you build an AI first company? What's overhyped about AI and what's underhyped and not nearly talked about enough. We answered these questions and more today with Ash Fontana, Managing Director of Zetta Venture Partners. Ash has built a career building and investing in startups - he was an early and senior member of AngelList and since joining Zetta has been in generational AI-first companies like Canva, Invenia, and more.

Paul Meller, Global Head of Engineering at EY, and Ash Fontana, Author of “The AI-First Company”, discuss the current and future state of AI, what role AI should be playing in your company, how to set yourself up for success when it comes to AI, and much more.---------“Part of the cultural change is how do you get people that haven't had to use data before to be open to using data and embrace data in their decisions that they're making? And then to have them take suggestions from AI and machine learning to support them in their work. ” - Paul Meller“If you're not developing AI, someone else will. And if you do start developing it now, then you start compounding your data assets and competitive advantage really quickly.” - Ash Fontana---------Time Stamps* (3:04) Welcome to the AI-first century* (7:07) Why you should be prioritizing AI* (9:33) How to become an AI-first company* (12:58) The data questions you need to be asking your business teams* (23:36) Common AI mistakes to avoid* (31:03) How to create a successful AI startup* (38:24) What are Paul and Ash dying to know about each other?--------SponsorLearn more about CIO Classified and find other episodes at CIOpod.comThis podcast is brought to you by Box, Okta, Slack, and Zoom. Modern employees demand the best tools at work. If your company wants to embrace the modern work environment, you need best-of-breed tools like Box, Okta, Slack, and Zoom.--------LinksAsh's book “The AI-First Company”EY.com

Ash Fontana author of "THE AI-FIRST COMPANY" by The Best Business Minds

Ash Fontana of Zetta Venture Partners joins Nick to discuss How to Value AI, Data Network Effects vs. Data Learning Effects, and Evolution of the VC Asset Class. In this episode we cover: What was the inspiration for the new book? What's the difference between a Data Network Effect and a DLE (data learning effect)? How do you advise those that are building tech where AI will be a valuable piece in the distant future but doesn't really play a role until the growth stage or beyond? Tell us about the Lean AI Method, described in the book, and how companies can use it to start implementing AI. How do you feel about companies using "off-the-shelf" AI, like TensorFlow? Why is now the right time for AI to pervade throughout tech and industry? How do you value AI and determine what's real? How does one put a valuation multiple on fairly nascent category where the value can be exponential and the moat can be unbreachable but there's not a whole lot of precedent? What are the key data categories or types that are most valuable for startups to be capturing and analyzing from day one? How do you find the right types of people with the right capability and mindset to join a startup if they have no formal training or experience directly w/ AI? How do you see the asset class evolving? Do you think the rolling fund product can make the leap to institutional investors, or will it continue to serve smaller, retail investors? What's your opinion on insider rounds? Thoughts on Tiger Global? Does China surpass the U.S. in tech innovation (and AI) over the next decade? Why or Why Not?   Missed a recent episode? Go to The Full Ratchet blog and catch up! Also, follow us on LinkedIn and Twitter. The host of The Full Ratchet is Nick Moran, General Partner of New Stack Ventures, a venture capital firm committed to investing in the exceptions. To learn more about New Stack Ventures by visiting our Website and LinkedIn and be sure to follow us on Twitter. Are you a founder looking for your next investor? Visit our free tool VC-Rank and tell us about your business. We'll send a list of possible investors right to your email's InBox!  

Today's guest is Ash Fontana, Managing Director of Zetta Venture Partners, a firm based in San Francisco. Ash was also a previous guest on our AI in Business Podcast. Today, he gives his recommendations for companies looking to transition from being service-oriented with AI to becoming more product-oriented. Ash also shares some lessons from his experience investing in AI firms and insights from his recently published book, “The AI-First Company: How to Compete and Win with Artificial Intelligence,” on what it takes to iterate and find a scalable business model. Download our whitepaper “Beginning with AI” to learn more about the practical steps for AI deployment at emerj.com/beg1.

Ash Fontana became one of the most recognized startup investors in the world after launching online investing at AngelList. He then became a Managing Director of Zetta, the first investment fund that focused on AI. The firm was the lead investor in category-defining AI companies such as Kaggle, Domino, Tractable, Lilt and Invenia. He has appeared in Fast Company, Bloomberg, Forbes, CNBC and at the UN. Ash previously co-founded Topguest, a Founders Fund-backed company that built customer analytics technology for companies like United, Virgin, and InterContinental. Topguest sold in an eight-figure transaction 18 months after the company was founded. From his experiences, he's written his first book, The AI-First Company, the definitive playbook to putting AI first in every business conversation. The playbook is an executable guide for applying AI to business problems, made for real companies, with real budgets, that need strategies and tactics to effectively implement AI. In this podcast, we'll dive into the topics from his book and really understand how you can apply these concepts to infuse AI in your organization. Ash will share with us why the concept we often hold about AI—a big brain in the sky—isn't accurate, and how we should be thinking of AI. He'll also define what it means to be an “AI-First company” and lead us through practical steps you can take now to start moving your organization on the path being an AI leader.__________________________________________________________________________________________"[AI] is very good at discrete things like making the same decision over and over again, very reliably with a predictable output or making very rational decisions or whatnot. So, I think it's important to just remember it's different from our form of intelligence. And that's why it's important to develop, because if it was the same why would we be bothering with all this."-Ash Fontana__________________________________________________________________________________________Episode Timeline:01:06—Introducing Ash Fontana + The topic of today's episode3:06—What is an AI-first company?4:49—How do you describe AI?5:50—Is AI less adaptable than humans at making decisions when the parameters or underlying ideas suddenly shift?7:16—Could you explain how flywheel concept as it relates to AI systems?9:08—How would a legacy or incumbent company approach where to start with AI?10:59—How can a company shift from a lean approach to being "all in"?13:14— What is some of the languages or some of the words that we need to start learning to grasp AI?14:49—What do companies most often get wrong when seeking to prioritize AI? 17:10—What are some resources or a place to start for companies looking to make the first steps?19:20—Where can we find you?__________________________________________________________________________________________Additional Resources:https://www.linkedin.com/in/ashfontana/The AI-First Company(Book)

In this episode, Ash Fontana discusses his book "The AI-First Company:  How to Compete and Win With Artificial Intelligence".  We discuss the role of data network effects, how data learning effects are bigger and more important, and many other AI related topics.

Ash Fontana became one of the most recognized startup investors in the world after launching online investing at AngelList. He then became a Managing Director of Zetta, the first investment fund that focused on AI. The firm was the lead investor in category-defining AI companies such as Kaggle, Domino, Tractable, Lilt and Invenia. He has appeared in Fast Company, Bloomberg, Forbes, CNBC and at the UN. Ash previously co-founded Topguest, a Founders Fund-backed company that built customer analytics technology for companies like United, Virgin, and InterContinental. Topguest sold in an eight-figure transaction 18 months after the company was founded. From his experiences, he's written his first book, The AI-First Company, the definitive playbook to putting AI first in every business conversation. The playbook is an executable guide for applying AI to business problems, made for real companies, with real budgets, that need strategies and tactics to effectively implement AI. In this podcast, we'll dive into the topics from his book and really understand how you can apply these concepts to infuse AI in your organization. Ash will share with us why the concept we often hold about AI—a big brain in the sky—isn't accurate, and how we should be thinking of AI. He'll also define what it means to be an “AI-First company” and lead us through practical steps you can take now to start moving your organization on the path being an AI leader.__________________________________________________________________________________________"[AI] is very good at discrete things like making the same decision over and over again, very reliably with a predictable output or making very rational decisions or whatnot. So, I think it's important to just remember it's different from our form of intelligence. And that's why it's important to develop, because if it was the same why would we be bothering with all this."-Ash Fontana__________________________________________________________________________________________Episode Timeline:01:06—Introducing Ash Fontana + The topic of today's episode3:06—What is an AI-first company?4:49—How do you describe AI?5:50—Is AI less adaptable than humans at making decisions when the parameters or underlying ideas suddenly shift?7:16—Could you explain how flywheel concept as it relates to AI systems?9:08—How would a legacy or incumbent company approach where to start with AI?10:59—How can a company shift from a lean approach to being "all in"?13:14— What is some of the languages or some of the words that we need to start learning to grasp AI?14:49—What do companies most often get wrong when seeking to prioritize AI? 17:10—What are some resources or a place to start for companies looking to make the first steps?19:20—Where can we find you?__________________________________________________________________________________________Additional Resources:https://www.linkedin.com/in/ashfontana/The AI-First Company(Book)

Today on the show, Allison and Gaby interview Artificial Intelligence expert Ash Fontana, who explains how our data is being gathered and used, whether or not technology is going to take all of our jobs, and the (scary yet exciting) future and present of AI. We wrap up with a rowdy game of Hypotheticals--even AI can't save you from America's Favorite Game Show!  Transcription: https://docs.google.com/document/d/1oZgYJSVovc6xSEt_yRE5XYd4g1YpvSVxZLWNV8v6RWs/edit?usp=sharing   This has been a Forever Dog production  Produced by Melisa D. Monts Executive produced by Brett Boham, Joe Cilio and Alex Ramsey To listen to this podcast ad-free  Sign up for Forever Dog Plus at foreverdogpodcasts.com/plus Check out video clips of our podcasts on Youtube at youtube.com/foreverdogteam And make sure to follow us on Twitter, instagram and Facebook at ForeverDogTeam to keep up with all of the latest Forever Dog NewsSupport this podcast at — https://redcircle.com/just-between-us/donationsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Today on the show, Allison and Gaby interview Artificial Intelligence expert Ash Fontana, who explains how our data is being gathered and used, whether or not technology is going to take all of our jobs, and the (scary yet exciting) future and present of AI. We wrap up with a rowdy game of Hypotheticals--even AI can't save you from America's Favorite Game Show!    This has been a Forever Dog production  Produced by Melisa D. Monts Executive produced by Brett Boham, Joe Cilio and Alex Ramsey To listen to this podcast ad-free  Sign up for Forever Dog Plus at foreverdogpodcasts.com/plus Check out video clips of our podcasts on Youtube at youtube.com/foreverdogteam And make sure to follow us on Twitter, instagram and Facebook at ForeverDogTeam to keep up with all of the latest Forever Dog News

Today on the show, Allison and Gaby interview Artificial Intelligence expert Ash Fontana, who explains how our data is being gathered and used, whether or not technology is going to take all of our jobs, and the (scary yet exciting) future and present of AI. We wrap up with a rowdy game of Hypotheticals--even AI can't save you from America's Favorite Game Show! This has been a Forever Dog production Produced by Melisa D. MontsExecutive produced by Brett Boham, Joe Cilio and Alex RamseyTo listen to this podcast ad-free Sign up for Forever Dog Plus at foreverdogpodcasts.com/plusCheck out video clips of our podcasts on Youtube at youtube.com/foreverdogteamAnd make sure to follow us on Twitter, instagram and Facebook at ForeverDogTeam to keep up with all of the latest Forever Dog NewsPrivacy Policy and California Privacy Notice.

Welcome to. Strategy Skills episode 159, an episode with Ash Fontana on the future of AI. Ash just published a great book on AI, THE AI-FIRST COMPANY, please see a link below. THE AI-FIRST COMPANY: https://amzn.to/3zRYW7o Among other insights, Fontana shows readers how to: Make AI your company's first priority. Identify the most valuable data. Build AI teams. Create AI budgets. Integrate AI with existing processes. Measure its effectiveness. Reinvest the profits from automation to build a competitive advantage. About the Author Ash Fontana became one of the most recognized startup investors in the world after launching online investing at AngelList. He then became a Managing Director of Zetta Venture Partners, the first investment fund that focused on AI. The firm was the lead investor in category-defining AI companies such as Kaggle, Domino, Tractable, Lilt and Invenia.  Enjoying our podcast? Get access to sample advanced training episodes here: www.firmsconsulting.com/promo We use affiliate links whenever possible (if you purchase items listed above using our affiliate links, we will get a bonus).

Discussing AI-First Company and AI First mentality with Ash Fontana. He sheds light on how organizations could embrace analytics, data, and AI to retain a competitive edge. Bio: Ash Fontana became one of the most recognized startup investors in the world after launching online investing at AngelList. He then became a Managing Director of Zetta, the first investment fund that focused on AI. The firm was the lead investor in category-defining AI companies such as Kaggle, Domino, Tractable, Lilt, and Invenia. He has appeared in Fast Company, Bloomberg, Forbes, CNBC, and at the UN. This is his first book. Ash's Book: The AI-First Company: How to Compete and Win with Artificial Intelligence by Ash Fontana https://amzn.to/33C2OL5 Ash's Recommendations: On Intelligence: How a New Understanding of the Brain Will Lead to the Creation of Truly Intelligent Machines by Jeff Hawkins, Sandra Blakeslee https://amzn.to/3vZhksk Neurophilosophy: Toward a Unified Science of the Mind-Brain by Patricia S. Churchland https://amzn.to/2RiKrYO Discussion Timeline: TIMELINE Some questions we covered: 1. Starter: Give your starter pitch 1 point that this book points to: 2. Vishal briefly introduce guest Stage 2: Subject Matter Expertise 3. What is the state of startups today? 4. State of AI in mature organization? 5. AI and Enterprise outlook? Cautionary tale or hopeful story 6. Who will win the AI race? 7. Challenges in AI adoption? Stage 3: Introduction as an author 8. What is an AI-First company? 9. Why write AI First? 10. Why does every company need to prioritize AI over the next decade? 11. What are the most common mistakes companies make when trying to become AI First? 12. What's the difference between “lean-startup” and “lean AI”? 14. How do AI-First companies retain more of the “first mover” advantage than others? 15. AI + Business, will make it more science or art? 16. Can AI be a competitive edge Stage 4: Rapid Fire with Ben Pring [Say what comes to your mind] 17 a. #MachineLearning 17 b. #Technology 17 c. #Leadership 17 d. #FutureOfWork 17 e. #Culture 17 f. #DigitalTransformation 17 g. #Disruption 17 h. #JobsOfFuture 17 i. #FutureofStartup 17 j. #FutureofOrganization 17 k. #AIFirst Stage 5: Closing 18. What are 1-3 best practices that you think are the key to success in your journey? 19. Do you have any favorite read? 20. As a closing remark, what would you like to tell our audience? About TAO.ai[Sponsor]: TAO is building the World's largest and AI-powered Skills Universe and Community powering career development platform empowering some of the World's largest communities/organizations. Learn more at https://TAO.ai About WorkPod: Work Pod takes you on the journey with leaders, experts, academics, authors, and change-makers designing the future of work, workers, and the workplace. About Work2.org WorkPod is managed by Work2.org, a #FutureOfWork community for HR and Organization architects and leaders. Sponsorship / Guest Request should be directed to info@tao.ai Keywords: #FutureofWork #Work2.0 #Work2dot0 #Leadership #Growth #Org2dot0 #Work2 #Org2

Automate to Excellence | Join investor and author of The AI-First Company, Ash Fontana, as he breaks down the power of artificial intelligence. Learn how companies can integrate AI to understand their customers better and optimize business. Subscribe to the FranklinCovey On Leadership email newsletter and receive weekly videos, tools, articles, and podcasts to help you become a better leader. ow.ly/tH5E30kAxfj Time To Go: Are you choosing to sit in the suffering you know versus the challenge you need? https://resources.franklincovey.com/blog/time-to-go Define Your Goals: Use this tool to clarify what success looks like for your team. https://pages.franklincovey.com/2021-Q4-NL-June15_Newsletter-Tool-Download.html

Ash Fontana discusses his book "The AI-First Company," and how to compete and win with Artificial Intelligence. Ash became one of the most recognized startup investors in the world after launching online investing at AngelList. He then became a Managing Director of Zetta, the first investment fund that focused on AI. He has appeared in Fast Company, Bloomberg, Forbes, and CNBC, among others. Listen for three action items you can use today. Host, Kevin Craine

This week on DisrupTV, we interviewed Dmitri Krakovsky, Chief Product Officer at Unit4, Ash Fontana, Managing Director at Zetta Partners and Author of THE AI-FIRST COMPANY and Liz Miller, VP & Principal Analyst at Constellation Research. DisrupTV is a weekly Web series with hosts R “Ray” Wang and Vala Afshar. The show airs live at 11:00 a.m. PT/ 2:00 p.m. ET every Friday. Brought to you by Constellation Executive Network: constellationr.com/CEN.

Ash Fontana is Managing Director of Zetta Venture Partners, a venture capital firm focused on artificial intelligence startups. He's also the author of The AI First Company, a new book that draws on Ash's experience as an entrepreneur and investor and lays out the principles for building a successful business based on data learning effects. In this conversation, we dive into the book's core ideas and discuss the past, present and future of AI.-----------------Thanks to Cofruition for consulting on and producing the show. You can learn more about Entrepreneur First at www.joinef.com and subscribe to my weekly newsletter at tib.matthewclifford.com

AI can offer a new type of competitive advantage, but entrepreneurs need to know what it is and how to unlock it. Ash Fontana, author of The AI First Company and managing director at Zetta Venture Partners – a firm that exclusively invests in early-stage AI startups, joins Azeem Azhar to explore the risks and rewards of applying AI to business problems.

How should Chief Information Officers manage AI in the enterprise, and what challenges may arise? Every CIO must consider these questions from both enterprise technology and business leadership perspectives.Author and AI investor Ash Fontana explains the CIO role and CIO responsibilities when developing organizational capabilities for AI, which he calls the AI-first company.The conversation covers these essential topics:-- What are the CIO’s first steps to adopting enterprise AI?-- How should CIOs start with enterprise AI?-- How much technical knowledge about machine learning models should business leaders possess?-- What are “data learning effects”?-- What is Lean AI?-- Should the CIO or CTO be responsible for investments in AI?-- Culture change and AI adoption-- Enterprise AI investment and financial return-- How to overcome obstacles to AI adoption in the enterprise?====Read the full transcript and watch other videos: https://www.cxotalk.com/episode/chief-information-officer-enterprise-ai-cioSubscribe to our newsletter: https://www.cxotalk.com/subscribe====Ash Fontana is author of the book The AI-First Company. He is an investor focused on AI-first companies at Zetta Venture Partners since 2014. Before Zetta, Ash launched syndicates at AngelList - the biggest startup investing platform in the world that now manages over $2B. Simultaneously, Ash made investments in Canva, Mixmax and others.====A few excerpts from the conversation:Michael Krigsman: In effect, what you're saying is this part of the company that's focused around AI, ideally, it would be the entire company, but let's just start small. This part of the company is using the delivery, using the use of AI tools, and then the delivery of outcomes relating to those tools as its kind of organizing principle. Is that an accurate way to summarize it?Ash Fontana: Yeah, I think that's a good way to summarize it. But again, there's so much nuance across the board here around the degree to which you focus on this, depending on where you're at in your journey, depending on whether you're at the phase where you're just experimenting with a few models to sort of test, like, can we actually make this prediction about the demand of the thing we're selling, the demand of the apparel we're selling next season? Can we make a prediction about a trend in this industry with our consumers, whether they're going to buy this or that color next season? Can we actually make a prediction around this delivery time in our supply chain? Can we do that?Are you at this stage where you're experimenting with that and really trying to discover from the data that you have whether you can do that? If so, the degree to which you invest in data collection, data infrastructure, and the degree to which you jump in the deep end of machine learning different models is very different to the point at which you've done those experiments, you're sure that you can make these predictions, and you want to really double down.This is where I introduce this concept of latent AI. But again, I think that's a good way to put it. There's a lot of nuance depending on the phase you're at. Different parts of your organization can mean different parts of the journey.The part of your organization that is on the marketing side can be really far ahead on the AI journey because there's a lot of data available to survey customers and run predictive models around what different segments will do and how they behave, whereas the part of the organization that's responsible for production might be a bit further back or earlier in the journey because fully roboticizing a production line is quite an undertaking. You'll want to do more experiments and little bits of the production line first, so it depends on where you are.

Discussing AI First Company and AI First mentality with Ash Fontana. He sheds light on how organizations could embrace analytics, data and AI to retain competitive edge. Bio: Ash Fontana became one of the most recognized startup investors in the world after launching online investing at AngelList. He then became a Managing Director of Zetta, the first investment fund that focused on AI. The firm was the lead investor in category-defining AI companies such as Kaggle, Domino, Tractable, Lilt and Invenia. He has appeared in Fast Company, Bloomberg, Forbes, CNBC and at the UN. This is his first book. Ash's Book: The AI-First Company: How to Compete and Win with Artificial Intelligence by Ash Fontana https://amzn.to/33C2OL5 Ash's Recommendations: On Intelligence: How a New Understanding of the Brain Will Lead to the Creation of Truly Intelligent Machines by Jeff Hawkins, Sandra Blakeslee https://amzn.to/3vZhksk Neurophilosophy: Toward a Unified Science of the Mind-Brain by Patricia S. Churchland https://amzn.to/2RiKrYO Discussion Timeline: TIMELINE Some questions we covered: 1. Starter: Give your starter pitch 1 point that this book points to: 2. Vishal briefly introduce guest Stage 2: Subject Matter Expertise 3. What is the state of startups today? 4. State of AI in mature organization? 5. AI and Enterprise outlook? Cautionary tale or hopeful story 6. Who will win the AI race? 7. Challenges in AI adoption? Stage 3: Introduction as an author 8. What is an AI-First company? 9. Why write AI-First? 10. Why does every company need to prioritize AI over the next decade? 11. What are the most common mistakes companies make when trying to become AI-First? 12. What's the difference between “lean-startup” and “lean AI”? 14. How do AI-First companies retain more of the “first mover” advantage than others? 15. AI + Business, will make it more science or art? 16. Can AI be a competitive edge Stage 4: Rapid Fire with Ben Pring [Say what comes to your mind] 17 a. #MachineLearning 17 b. #Technology 17 c. #Leadership 17 d. #FutureOfWork 17 e. #Culture 17 f. #DigitalTransformation 17 g. #Disruption 17 h. #JobsOfFuture 17 i. #FutureofStartup 17 j. #FutureofOrganization 17 k. #AIFirst Stage 5: Closing 18. What are 1-3 best practices that you think are the key to success in your journey? 19. Do you have any favorite read? 20. As a closing remark, what would you like to tell our audience? About TAO.ai[Sponsor]: TAO is building the World's largest and AI-powered Skills Universe and Community powering career development platform empowering some of the World's largest communities/organizations. Learn more at https://TAO.ai About FutureOfData: FutureOfData takes you on the journey with leaders, experts, academics, authors, and change-makers designing the future of data, analytics, and insights. About AnalyticsWeek.com FutureOfData is managed by AnalyticsWeek.com, a #FutureOfData Leadership community of Organization architects and leaders. Sponsorship / Guest Request should be directed to info@tao.ai Keywords: #FutureofData #Work2.0 #Work2dot0 #Leadership #Growth #Org2dot0 #Work2 #Org2

Ash Fontana (@ashfontana), author of The AI-First Company and partner at Zetta Venture Partners, joined Erik for a fireside chat for Villagers in May 2021. They discussed:- Why AI creates defensibility and a true, compounding, first-mover advantage.- Why AI should be part of all conversations at your startup: about products to build, people to hire, what price to charge — it should all involve AI.- The difference between Lean Startup and Lean AI.- Common mistakes that early AI companies make, like spending too much on marketing and not enough on sales.- The impacts of AI on hiring and the differences between a data PM and an ordinary PM.- What you can do tomorrow to get started building an AI-first company.Thanks for listening — if you like what you hear, please review us on your favorite podcast platform. Check us out on the web at www.villageglobal.vc or get in touch with us on Twitter @villageglobal.Want to get updates from us? Subscribe to get a peek inside the Village. We’ll send you reading recommendations, exclusive event invites, and commentary on the latest happenings in Silicon Valley. www.villageglobal.vc/signup

Ash Fontana, Managing Director of Zetta, discusses his book "The AI-First Company” on why companies need to prioritize artificial intelligence to succeed. Host; Carol Massar. Producer: Paul Brennan. Learn more about your ad-choices at https://www.iheartpodcastnetwork.com

Ash Fontana, Managing Director of Zetta, discusses his book "The AI-First Company” on why companies need to prioritize artificial intelligence to succeed. Host; Carol Massar. Producer: Paul Brennan.

Ash Fontana discusses his book "The AI-First Company," and how to compete and win with Artificial Intelligence. Ash became one of the most recognized startup investors in the world after launching online investing at AngelList. He then became a Managing Director of Zetta, the first investment fund that focused on AI. He has appeared in Fast Company, Bloomberg, Forbes, and CNBC, among others. Listen for three action items you can use today. Host, Kevin Craine Do you want to be a guest? Do you want to be a sponsor?

Ash Fontana is an entrepreneur, investor, and author. As an entrepreneur, he was only of the early employees at an online investing platform called AngelList. From there, he became the Managing Director at Zetta, the first investment fund focused on artificial intelligence. Now, he's the author of the AI-First Company. This conversation is about that book. Ash says that AI-First companies are the only trillion-dollar companies, and soon they will dominate even more industries, more definitively than ever before. But we don't just talk about the book. We also talk about health, continental philosophy, and Ash's obsession with bicycling. Please enjoy my conversation with Ash Fontana.

Artificial Intelligence is already part of our lives in the tools and services we use every day. As AI development accelerates, how can authors and small businesses use it as leverage to expand income and opportunities? Ash Fontana gives some ideas in this interview on The AI-First Company. In the intro, How GPT-3 is quietly […] The post The AI-Powered Micro-Business with Ash Fontana first appeared on The Creative Penn.

In this episode, we speak with industry-leading investor Ash Fontana about his new book, the AI-First Company and discuss the importance of the process, systemic and mindset changes involved in the global deployment of artificial intelligence. In this fascinating episode, Ash takes us through the latest thinking on artificial intelligence and the challenges for companies if they don't operate in an AI-First way.

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A leader in the world of artificial intelligence Ash Fontana joins us to share about his new book, THE AI-FIRST COMPANY: How to Compete and Win with Artificial Intelligence.

Today Emerj welcomes the return of the great and brilliant Ash Fontana, General Partner at Zetta Ventures. Zetta primarily invests in AI-first companies with B2B business models, with a portfolio including Kaggle, Domo, and other notables. Ash's career has spanned private equity, investment banking, as well as venture capital. In this episode, he offers a valuable perspective on where AI is taking financial services. Episode topics include: AI-driven risk measurement, risk prediction, and risk mitigation. Want to learn more about AI in financial services? Get Emerj's pdf guide: emerj.com/fin1

A time travel episode with the wonderful Ash Fontana - Angel Investor and all round business wizard, talks to me over mint tea. Before the pandemic! How much to struggle, and how not to get caught up in questioning big life choices. Intellectual Honesty. Community. Ambition. Competency. Success. Find Ash at @ashfontana on instagram and twitter

Discover how AI may shift the workflows and approaches to trading as we interview Ash Fontana, managing director at Zetta Venture Partners, a Silicon Valley-based venture capital firm focused on AI-first companies with B2B business models. Ash shares his valuable perspective on the present and future of AI in trading. Access Emerj's AI in Financial Services Vendor Landscape Brief here: emerj.com/vl1

Ash Fontana of Zetta Venture Partners joins Nick on a special Crisis Coverage installment to discuss The AI Investing Playbook; Why "Dev Tools" for Data Scientists is the Next Great Opportunity; When Fund Returns Don't Fit the Power Law; and Ash's Favorite Investment Heuristic from Naval Ravikant. In this episode, we cover: Zetta III was announced recently, a $180M fund for founders building AI-first companies. You went from $60M -> $125M -> $180M... how was the fundraise different this time around? Quickly can you give us your definition of an AI-first company? What will you be doing differently with the new fund and how does the pandemic affect your approach? Tom Tunguz just mentioned that in the data they're analyzing they are seeing a drop in spend on Machine Learning Infrastructure.  How much of a concern is this to you and your portfolio companies? With the launch of the new fund, you outline focus areas both Applications as well as infrastructure and tools...Is the application-layer ready to leverage AI in a significant way or is there still a lot headway that needs to be made at the infrastructure level first? Carlota Perez has written about technology cycles and how new technologies typically go through this installment phase, w/ rapid development and heavy investment, followed by crash and subsequent recovery leading to the deployment phase...  in your estimation where are we in the tech life cycle of AI and is it really ready (or will it be ready over the next 3-7 years) for mass deployment? How effective are the AI models today when much of the input data, generally speaking, is flawed? Talk about the next 3-5 years for Data Science... we've seen significant advances in developer tools and systems for software but I still feel like we're at very early stages in evolution, efficiency and scalability of data science tools/fundamentals. Does your fund returns follow the power law? Part of the advantage to AI-first startups is the supreme data moat that they can build, preventing others from gaining traction w/ competitive solutions. While this is an advantage for the startups that get a head start (and their investors) is there an adverse impact on other startups that are founded later and don't have the extensive data sets? Many of the startups you invest in are "deep-tech" and will not monetize and grow ARR the same way many familiar SaaS or transactional businesses will.  What are the major gating factors to raise each of a Seed Round, a Series A and a Series B, in these longer cycle tech-first approaches? You've create a Playbook on how to build an AI-first company.  It's evergreen with plans to update regularly as you work w/ companies...  I wonder if you might give us the basics... What do AI-First companies have in their DNA and when building a company, what's the sequence and major building blocks required at the early stages? Last time you were on the show you mentioned you learned a lot of great heuristics and mental models from Naval Ravikant. Can you give us a couple of these that have been really valuable in helping you quickly frame startup investment potential? To listen more, please visit http://fullratchet.net/podcast-episodes/ for all of our other episodes. Also, follow us on twitter @TheFullRatchet for updates and more information.

Ash Fontana (@ashfontana), General Partner at Zetta, and Leo Polovets (@lpolovets), General Partner at Susa Ventures, join Erik on this episode. They Discuss:- What does the future of venture capital look like?- Which firms are leading venture capital and who will be the top venture firms 10 years from now?- Being a generalist investor versus a specialist- Portfolio structure and the role of follow-on funding as part of a firm's strategy- Is it important to have one portfolio company that can return the entire fund?- Are there moats in venture capital?- The role of pricing power in venture capital- How is venture similar and different to company building?- Compounding Data Moats- Request for StartupsThanks for listening — if you like what you hear, please review us on your favorite podcast platform.Check us out on the web at villageglobal.vc or get in touch with us on Twitter @villageglobal.Venture Stories is brought to you by Village Global, and is hosted by co-founder and partner, Erik Torenberg.

Ash Fontana (@ashfontana), General Partner at Zetta, and Leo Polovets (@lpolovets), General Partner at Susa Ventures, join Erik on this episode. They Discuss:- What does the future of venture capital look like?- Which firms are leading venture capital and who will be the top venture firms 10 years from now?- Being a generalist investor versus a specialist- Portfolio structure and the role of follow-on funding as part of a firm's strategy- Is it important to have one portfolio company that can return the entire fund?- Are there moats in venture capital?- The role of pricing power in venture capital- How is venture similar and different to company building?- Compounding Data Moats- Request for StartupsThanks for listening — if you like what you hear, please review us on your favorite podcast platform.Check us out on the web at villageglobal.vc or get in touch with us on Twitter @villageglobal.Venture Stories is brought to you by Village Global, and is hosted by co-founder and partner, Erik Torenberg.

Ash Fontana is a Managing Director @ Zetta Venture Partners, the fund that invests in AI-first companies with B2B business models. As for Ash, prior to Zetta he started the money side of AngelList, where, he launched online investing, created the first startup ‘index fund’. He also ran special projects like AngelList’s expansion into Europe and the UK. Simultaneously, Ash led syndicates and made investments in Canva, Mixmax and others. Before AngelList, Ash co-founded Topguest, a Founders Fund-backed company that built customer analytics technology and was ultimately sold in an 8 figure transaction 18 months after the company was founded. In Today’s Episode You Will Learn: 1.) How Ash made his way into the world of venture with AngelList and how that led to his joining Zetta today, investing exclusively in AI? What did Ash's time working on his family farm teach him about vertically integrated businesses? What were his biggest takeaways from AngelList and working alongside Naval? 2.) What does AI-first really mean to Ash? How crucial is it for companies to have proprietary datasets today? Are data moats truly defensible and real? What are the 5 characteristics that determine the level of defensibility of a dataset? How does Ash analyse the quality of a dataset? What does Ash do to determine if they are predictive of value? 3.) We often hear the term, "system of record", why is Ash so much more excited by the "system of intelligence"? Why is the basis of competitive advantage shifting from SaaS today as a model? How do the margin structure vastly differ when comparing AI-first companies to SaaS companies? How does that mean one should view capital efficiency? 4.) What does Ash believe drives business model quality? What are the commonalities in the business models of those that have made it big? Why does Ash believe it is difficult for incumbent companies to become AI-first? How difficult is it for incumbents to acquire smaller AI-first firms and integrate their policies and technology? 5.) Why does Ash love Howard marks and what has been his biggest learnings from studying him? How has Ash applied these learnings to his investing today? What has Ash also learned from the Italian masters of design? How has this study helped Ash as a VC? What has Ash optimised lately? What is Ash's favourite optimisation? Items Mentioned In Today’s Show: Ash’s Fave Book: The Strategy of Life: Teleology and Mechanics in Nineteenth-Century German Biology As always you can follow Harry, The Twenty Minute VC and Ash on Twitter here!  

My guest on today’s First Meeting is Ash Fontana, a Managing Director at Zetta Ventures, a venture capital firm that backs Artificial Intelligence companies with B2B business models.  The firm invests in early-stage companies with unique data sets and models, and rolls up their sleeves to help founders by using a playbook Zetta created specifically for AI companies.  Ash started his career as an entrepreneur and investor, and before joining Zetta started and built the money side of AngelList alongside Naval Ravikant. Our conversation covers Ash’s background, Zetta’s thesis, team, and strategy, and turns to Zetta’s sourcing, due diligence, decision making, portfolio construction, working for portfolio companies, and investment examples.  Along the way, we cover the evolution of AI, assessing data sets, misperceptions about AI, competing with the tech giants, and the future of investing in the space. Learn More Read the Transcript Subscribe to the Capital Allocators Blog or Monthly Mailing List Don't Subscribe, but Let Us Know Who You Are Write a review on iTunes Follow Ted on twitter at @tseides Review past episodes of the Podcast

“Data is the new oil” has become one of the most common catch phrases in popular media. It makes sense right? Wrong. At least according to Ash Fontana, Managing Director at Zetta Venture Partners and one of the most nuanced thinkers on AI today.  Ash believes we are squarely in the fourth era of computing, the intelligence era. In this era, data aggregation is less interesting than matching data sets to tactical problems. And with good reason. The intelligence era is an inflection point; traditional I.T. infrastructure will change to enable the development of self-learning software and previously data-starved markets — from agriculture to sales — will benefit from the information generated by self-learning software.  Ash thinks about AI companies with an incredibly human centric approach; when he evaluates data sets and companies, he asks how much human activity can the company free up if it works at scale.  In this episode, we chatted all things AI with Ash. We talked about a number of topics; some of my favorite included: (1) the utility of data for AI first companies, (2) why data strategy is fundamentally different for an AI driven company vs. a normal software company, (3) why Ash is bearish on SaaS and (4) how do you compete with Google, Amazon and Facebook in a data driven world. It was a pleasure to have Ash on the show to get his thoughts on the future of AI. His perspective was incredibly thoughtful and I personally learned an incredible amount from him in this conversation. 

This episode is part of a three-part series taking listeners behind the curtain to discuss the inner workings of venture capital. Parker Thompson (@pt), partner at AngelList, and Ash Fontana (@ashfontana), general partner at Zetta Ventures, join Erik on this episode.They start off by discussing why topics around VC and portfolio construction in particular are so controversial. Parker and Ash give a rundown of how they invest with their respective funds and what their theses are when it comes to venture investing. They address the perennial debate of how much money to allot to initial round investing versus reserves for follow-on investing. It gets pointed out that based on the data, new funds are as likely as existing funds to succeed, and they talk about whether there’s a universal answer to the question of how much money under management a VC would ideally like to have. The three of them talk about the possibility of scaling up a fund with operating partners and discuss research that shows that the more companies invested in, the better the returns. That trend continues to hold, in theory, no matter how big the fund gets. However, Parker brings up the "math versus reality dichotomy," and they talk about why in practice scaling up infinitely doesn’t work.Erik asks both of them how they would set up their fund if they had no constraints, and they talk about why "fund size is destiny" in venture. Ash and Parker explain why even though venture firms say that the founder is their customer, really the LPs are the actual customers. They also talk about why innovation is needed on the standard “2 and 20” model (2% management fees and 20% carry), discuss potential replacement models, and explain why Y Combinator has the best business model in venture, even though there are some pitfalls for entrepreneurs.Thanks for listening — if you like what you hear, please review us on your favorite podcast platform. Check us out on the web at villageglobal.vc or get in touch with us on Twitter @villageglobal.Venture Stories is brought to you by Village Global, is hosted by co-founder and partner, Erik Torenberg and is produced by Brett Bolkowy.

This episode is part of a three-part series taking listeners behind the curtain to discuss the inner workings of venture capital. Parker Thompson (@pt), partner at AngelList, and Ash Fontana (@ashfontana), general partner at Zetta Ventures, join Erik on this episode.They start off by discussing why topics around VC and portfolio construction in particular are so controversial. Parker and Ash give a rundown of how they invest with their respective funds and what their theses are when it comes to venture investing. They address the perennial debate of how much money to allot to initial round investing versus reserves for follow-on investing. It gets pointed out that based on the data, new funds are as likely as existing funds to succeed, and they talk about whether there’s a universal answer to the question of how much money under management a VC would ideally like to have. The three of them talk about the possibility of scaling up a fund with operating partners and discuss research that shows that the more companies invested in, the better the returns. That trend continues to hold, in theory, no matter how big the fund gets. However, Parker brings up the "math versus reality dichotomy," and they talk about why in practice scaling up infinitely doesn’t work.Erik asks both of them how they would set up their fund if they had no constraints, and they talk about why "fund size is destiny" in venture. Ash and Parker explain why even though venture firms say that the founder is their customer, really the LPs are the actual customers. They also talk about why innovation is needed on the standard “2 and 20” model (2% management fees and 20% carry), discuss potential replacement models, and explain why Y Combinator has the best business model in venture, even though there are some pitfalls for entrepreneurs.Thanks for listening — if you like what you hear, please review us on your favorite podcast platform. Check us out on the web at villageglobal.vc or get in touch with us on Twitter @villageglobal.Venture Stories is brought to you by Village Global, is hosted by co-founder and partner, Erik Torenberg and is produced by Brett Bolkowy.

In the first all-Australian episode of Venture Stories Erik interviews returning guest Ash Fontana (@ashfontana), general partner at Zetta Ventures, and his fellow countryman, Anthony Goldbloom (@antgoldbloom), CEO of Kaggle.Ash’s fund is the first fund devoted exclusively to AI and machine learning, and the three talk about how to evaluate companies, founders and ideas in the space. Ash says that the founders he looks for are often pre-traction but post-data, meaning that they have the data but are trying to find a way to make their machine learning work commercially viable. He points out that certain data-gathering techniques just aren’t viable for a startup when “you have to lose money to learn in the machine learning space.”The trio discuss a number of the coolest current applications of machine learning as well as where they would like to see companies bring machine learning in the future. They talk about the present and potential future impact of machine learning techniques in data labeling, oil and gas, healthcare, and the enterprise.Anthony and Ash also talk about some of the trends they see coming in machine learning, including moving data and machine learning to the cloud as well as the use of private or disguised data to allow sensitive data sets to be analyzed by a broader group of people. They also discuss which areas prospective founders should avoid and why machine learning is conducive to certain types of problems but not others.Thanks for listening — if you like what you hear, please review us on your favorite podcast platform. Check us out on the web at villageglobal.vc or get in touch with us on Twitter @villageglobal.Venture Stories is brought to you by Village Global and is hosted by co-founder and partner, Erik Torenberg. Colin Campbell is our audio engineer and the show is produced by Brett Bolkowy.

In the first all-Australian episode of Venture Stories Erik interviews returning guest Ash Fontana (@ashfontana), general partner at Zetta Ventures, and his fellow countryman, Anthony Goldbloom (@antgoldbloom), CEO of Kaggle.Ash’s fund is the first fund devoted exclusively to AI and machine learning, and the three talk about how to evaluate companies, founders and ideas in the space. Ash says that the founders he looks for are often pre-traction but post-data, meaning that they have the data but are trying to find a way to make their machine learning work commercially viable. He points out that certain data-gathering techniques just aren’t viable for a startup when “you have to lose money to learn in the machine learning space.”The trio discuss a number of the coolest current applications of machine learning as well as where they would like to see companies bring machine learning in the future. They talk about the present and potential future impact of machine learning techniques in data labeling, oil and gas, healthcare, and the enterprise.Anthony and Ash also talk about some of the trends they see coming in machine learning, including moving data and machine learning to the cloud as well as the use of private or disguised data to allow sensitive data sets to be analyzed by a broader group of people. They also discuss which areas prospective founders should avoid and why machine learning is conducive to certain types of problems but not others.Thanks for listening — if you like what you hear, please review us on your favorite podcast platform. Check us out on the web at villageglobal.vc or get in touch with us on Twitter @villageglobal.Venture Stories is brought to you by Village Global and is hosted by co-founder and partner, Erik Torenberg. Colin Campbell is our audio engineer and the show is produced by Brett Bolkowy.

Erik and co-host for this episode Ash Fontana (@ashfontana) of Zetta Venture Partners interview Ali Hamed (@AliBHamed), investor at CoVenture.Ali gives us a primer on the online lending space and compares and contrasts it to offline lending. He explains why payday lenders with astronomical APRs actually have small margins. He also talks about how government can improve the regulatory environment to allow for more disruption of traditional lending and help new companies get a foothold.They talk about crypto and whether people will be making loans against Bitcoin anytime soon as well as the idea of personal ICOs and why Ali thinks they are a bad idea.The trio finish with a rapid-fire round where Erik names a venture firm and Ali talks about what he thinks that company should do in the future. Thanks for listening — if you like what you hear, please review us on your favorite podcast platform. Check us out on the web at villageglobal.vc or get in touch with us on Twitter @villageglobal.Venture Stories is brought to you by Village Global and is hosted by co-founder and partner, Erik Torenberg. Colin Campbell is our audio engineer and the show is produced by Brett Bolkowy.

Erik and co-host for this episode Ash Fontana (@ashfontana) of Zetta Venture Partners interview Ali Hamed (@AliBHamed), investor at CoVenture.Ali gives us a primer on the online lending space and compares and contrasts it to offline lending. He explains why payday lenders with astronomical APRs actually have small margins. He also talks about how government can improve the regulatory environment to allow for more disruption of traditional lending and help new companies get a foothold.They talk about crypto and whether people will be making loans against Bitcoin anytime soon as well as the idea of personal ICOs and why Ali thinks they are a bad idea.The trio finish with a rapid-fire round where Erik names a venture firm and Ali talks about what he thinks that company should do in the future. Thanks for listening — if you like what you hear, please review us on your favorite podcast platform. Check us out on the web at villageglobal.vc or get in touch with us on Twitter @villageglobal.Venture Stories is brought to you by Village Global and is hosted by co-founder and partner, Erik Torenberg. Colin Campbell is our audio engineer and the show is produced by Brett Bolkowy.

My guest this week is Ash Fontana, a managing partner at venture capital firm Zetta, who invests in companies which build software that uses artificial intelligence methods like machine learning to predict and prescribe outcomes. Ash’s combined experience as a founder, entrepreneur, and investor give him the perfect background to discuss with us one of the hottest topics in business and investing. This conversation is useful for anyone trying to evolve their own way of dealing with data. Of particular interest are the ways that Ash and his team evaluate data sets and how they think about competitive advantage in this new world—where he advocates a new term to replace the concept of moat: loops.  If we can use data to do things better than humans, or if we can supercharge our intuitions with predictive models, we can harness the power of this new technology. What Ash has taught me is that data itself is dumb. But great data sets can represent the fuel for incredible companies. Let’s dive into how that may be. Please enjoy this conversation on how AI is changing business, and how we might profit from that change.   For more episodes go to InvestorFieldGuide.com/podcast. Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub. Follow Patrick on Twitter at @patrick_oshag   Books Referenced The Most Important Thing: Uncommon Sense for The Thoughtful Investor   Links Referenced Jerry Neumann Podcast Episode Ali Hamed Podcast Episode   Show Notes 2:25 - (First Question) – A look at their very specific investment strategy 3:35 – Future of competitive advantage in the SaaS industry 6:45 – How startups and new companies can compete against software giants that are pretty well entrenched in the market 8:38 – How do copies with narrow focuses attract VC money which is looking for massive returns 12:28 – The stages in which AI will be enabled 15:55 – Framework of an AI company 18:49 – Importance of the feedback in the AI company framework 20:56 – Examples of AI companies 23:50 – Why companies that are AI from the start will have a significant advantage in the space 26:21 – How do companies change their thinking about compiling useful data 32:18 – Regulation of AI 35:03 – Preventing other companies from leap frogging you in the AI space 37:57 – Some of his favorite AI companies 40:43 – How much has he seen in the finance world             41:07 – Jerry Neumann Podcast Episode 43:10 – Why the focus on B2B AI companies 45:34 – Major components of the enterprise stack that he focuses on for AI 49:30 – What impact will all of this AI have the daily lives of people 51:38 – Biggest problems that he is excited to see AI tacklet 53:04 – How do you value the intangible asset of an AI model 57:13 – How Ash thinks about getting other investors into firms they seeded 1::00:27 – Other investors that Ash really respects             1:01:15 – The Most Important Thing: Uncommon Sense for The Thoughtful Investor             1:03:29 – Ali Hamed Podcast Episode 1:04:04 – Where would Ash invest outside of AI 1:07:11 – More about his family nut business 1:11:18 – Favorite macadamia nut story 1:12:05 – Kindest thing anyone has done for Ash   Learn More For more episodes go to InvestorFieldGuide.com/podcast.  Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub Follow Patrick on twitter at @patrick_oshag

Ash Fontana of Zetta Venture Partners joins Nick to discuss Why SaaS is not a fit for VC and How AI Compounds Competitive Advantage. In this episode, we cover: Categories of AI that Ash is most interested in The difference between real AI and AI-enabled companies Why SaaS will cease to be investable by VCs The current AI stage of adoption How he times the market The four phases of AI What phase of AI they invest in How AI is and will be affected by limited data How startups can compete for talent w/ GAFA (Google, Amazon, Facebook, Apple) The moats being created by their AI-first portcos How they think about metrics and milestones for AI-backed companies If AI should be feared and finally we wrap up w/ Ash's thoughts on Chris Dixon's position that we will see a movement from centralization back to decentralization in tech-- and the role that AI will play   To listen more, please visit http://fullratchet.net/podcast-episodes/ for all of our other episodes. Also, follow us on twitter @TheFullRatchet for updates and more information.

Erik interviews Ash Fontana (@ashfontana) of Zetta Venture Partners with his co-host for this episode, Abie Katz of August Capital. They talk about how Ash got his fund started and how and why he structured it the way he did. They discuss how to manage growth in a venture fund and the relative importance of being a recognizable brand in the space. They ask Ash what he looks for in a machine learning startup and Ash explains why sometimes it’s better to stay small. He also talks about how and why to be intellectually honest about your investing decisions. Check us out on the web at villageglobal.vc/podcast.

Erik interviews Ash Fontana (@ashfontana) of Zetta Venture Partners with his co-host for this episode, Abie Katz of August Capital. They talk about how Ash got his fund started and how and why he structured it the way he did. They discuss how to manage growth in a venture fund and the relative importance of being a recognizable brand in the space. They ask Ash what he looks for in a machine learning startup and Ash explains why sometimes it’s better to stay small. He also talks about how and why to be intellectually honest about your investing decisions. Check us out on the web at villageglobal.vc/podcast.