Episodes
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In this episode, we sit down with Eric Glyman, co-founder of Ramp, the company that revolutionized finance management to become a powerhouse valued at $7.6 billion.
Eric shares the tradition of counting the days since Ramp's founding and how it fosters a sense of urgency and productivity, explains the use of AI to automate expense management and fraud detection, and gives an inside look at Ramp's cutting-edge AI products, including the Ramp Intelligence Suite and experimental agentic AI use cases.
Ramp
Website - https://www.ramp.com
Twitter - https://x.com/tryramp
Eric Glyman
LinkedIn - https://www.linkedin.com/in/eglyman
Twitter - https://x.com/eglyman
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro
(01:49) What is Ramp?
(04:25) How did the company start?
(09:18) Technical aspects of Ramp infrastructure
(12:17) "We can tell you if you're paying too much"
(14:20) Data privacy at Ramp
(16:13) Data infrastructure tools used at Ramp
(17:58) Traditional AI use cases
(24:51) GenAI use cases
(27:47) AI/human interaction
(33:32) Ramp Intelligence Suite
(39:38) How Ramp keeps high product release and product velocity
(42:37) How did Ramp get to product-market fit?
(45:54) Eric's perspective on building a company in NYC
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In this episode, we reconnect with Sharon Zhou, co-founder and CEO of Lamini, to dive deep into the ever-evolving world of enterprise AI.
We discuss how the AI hype is evolving and what enterprises are doing to stay ahead, break down the different players in the Inference market, explore how Memory Tuning is reducing hallucinations in AI models, the role of agents in enterprise AI, and the challenges of making them real-time and reliable.
Lamini
Website - https://www.lamini.ai
Twitter - https://x.com/laminiai
Sharon Zhou
LinkedIn - https://www.linkedin.com/in/zhousharon
Twitter - https://x.com/realsharonzhou
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro
(02:18) The state of the AI market in July, 2024
(10:51) What is Lamini?
(11:43) What is Inference?
(15:36) GPU shortage in the enterprise
(18:06) AMD vs Nvidia
(22:10) What is Lamini's final product?
(25:30) What is Memory Tuning?
(29:01) What is LoRA?
(32:39) More on Memory Tuning
(35:51) Sharon's perspective on AI agents
(40:01) What is next for Lamini?
(41:54) Reasoning vs pure compute in AI
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Episodes manquant?
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In this episode, we sit down with Jeremy Kahn, the AI Editor at Fortune Magazine, who has recently published a book called "Mastering AI: A Survival Guide to Our Superpowered Future".
Jeremy shares his unique insights on AI's potential risks and transformative benefits, including the importance of UI design in maximizing AI's utility, the potential for AI to create a "winner takes most" economy, and the need for thoughtful AI regulation to mitigate risks without stifling innovation.
Book: https://www.amazon.com/Mastering-AI-Survival-Superpowered-Future/dp/1668053322
Jeremy Kahn
LinkedIn - https://www.linkedin.com/in/jeremy-kahn-01100462
Twitter - https://x.com/jeremyakahn
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro
(01:43) Why the UI design is important for AI?
(04:32) The book is called "Mastering AI". Why?
(12:03) Automation Bias vs Automation Surprise
(20:16) The role of AI in the future of science and art
(25:32) "I think mass unemployment is a red herring, but we might see a lot of disruption"
(34:19) Jeremy's perspective on Agentic AI
(36:29) Does AI development need to be regulated?
(38:56) Should we worry about the AGI and Superintelligence?
(42:18) Who provided the most thoughtful conversation for the book?
(43:57) "I didn't use AI for the book at all"
(46:20) Jeremy's work at Fortune
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In this episode, we sit down with Azeem Azhar, an expert on AI and technologies, whose weekly newsletter "The Exponential View" (www.exponentialview.co) is read by nearly two hundred thousand people from around the world.
We delve into the nuances of AI adoption, discussing how LLM's are reshaping industries and what this means for corporate leaders, the dynamics between the U.S., China, and Europe in the AI race, and the concept of sovereign AI.
Azeem Azhar
Website - https://www.exponentialview.co
Twitter - https://x.com/azeem
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro
(02:05) What does the "Exponential" really mean?
(05:43) "Moore's law has not died"
(11:52) Claude is the Macintosh of AI. What does it mean?
(25:57) How does AI affect the enterprise?
(34:06) Asia is more optimistic about AI than the West. Why?
(38:42) Azeem's perspective on the sovereign AI
(45:19) AI in the modern warfare
(48:47) What is the Exponential asymmetry?
(51:59) Energy transition and the influence of AI on it
(55:21) Big Oil vs Chinese Solar: who's going to win?
(59:18) AI opens new possibilities for everyone. How?
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In this episode, we sat down with Aaron Katz, the CEO of ClickHouse, a company that went from an open-source analytical database into a highly successful cloud service, utilized by Spotify, Netflix, Disney, and many more.
Aaron Katz provides intriguing insights into the challenges of transitioning an open-source project into a thriving business, ClickHouse's go-to-market strategy, the role of technical support in pre-sales, and the strategic decision to avoid traditional SDR and CSM roles.
CLICKHOUSE
Website - https://clickhouse.com/
Twitter - https://x.com/clickhousedb
Aaron Katz
LinkedIn - https://www.linkedin.com/in/aaron-katz-5762094
Twitter - https://x.com/ceo_clickhouse
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro
(00:56) What is ClickHouse?
(04:28) What are the use cases for ClickHouse?
(06:17) Reducing the latency: why the world shifts to real-time
(09:05) How did ClickHouse evolve from an open-source to a cloud product?
(15:01) "Open source is the future of software"
(17:27) Self-hosted deployments
(18:45) ClickHouse's roadmap
(20:51) Is there a real-time data stack?
(22:25) ClickHouse partners in data ingestion
(24:32) Who are ClickHouse's main competitors?
(27:35) ClickHouse's sales process
(36:44) Is partnerships a good go-to-market strategy?
(37:44) When is the right time for startups to start partnering?
(38:22) Aaron's story of becoming the CEO
(43:50) Team and culture when working on two continents
(46:15) What's next? -
In this episode, we sit down with Daniel Dines, the co-founder and CEO of UiPath. From a small rented apartment in Bucharest to $1.3 billion in revenue, UiPath's story is one of perseverance, innovation, and strategic pivots.
Daniel shares his insights on the pivotal moments that shaped UiPath, how to build a robust go-to-market strategy, the role of partnerships, and the lessons learned in hiring and managing a sales organization.
UIPath
Website - https://www.uipath.com/
Twitter - https://x.com/UiPath
Daniel Dines
LinkedIn - https://www.linkedin.com/in/danieldines
Twitter - https://x.com/danieldines
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro
(01:38) UiPath was founded in an apartment in Bucharest. How did it all start?
(08:05) Building a global product
(11:26) The growth stage.
(18:50) "We were AI from the beginning"
(20:10) Raising the first round of funding.
(23:48) Working with the board.
(25:11) How did UiPath expand from the Romanian to the global market?
(35:00) Process Mining, Task Mining, and Communications Mining.
(41:41) The Automation Layer explained.
(45:28) The use cases for using AI in UiPath's automations
(56:22) UiPath's strategy for Gen AI adoption.
(58:27) The team.
(59:42) How important are partnerships for enterprise
(01:02:48) Recruiting the best salespeople in the industry
(01:07:10) Scaling from a software engineer to the CEO of a large company.
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In this episode, we sit down with Howie Liu, co-founder and CEO of Airtable, to explore the incredible journey of Airtable from its early days to becoming a powerhouse in the enterprise software space.Howie provides a candid look at the challenges and learnings from transitioning Airtable from a PLG product to an enterprise platform, how companies are transforming their marketing operations with AI, and the transformative potential of AI in automating workflows and enhancing business processes.AIRTABLEWebsite - https://www.airtable.com/Twitter - https://x.com/airtableHowie Liu LinkedIn - https://www.linkedin.com/in/howieliu/Twitter - https://x.com/howietlFIRSTMARKWebsite - https://firstmark.comTwitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/Twitter - https://twitter.com/mattturck(00:00) Intro
(02:40) What is Airtable in 2024?
(05:35) How does Airtable apply AI to its products?
(11:56) What are the AI use cases in Airtable?
(18:35) The tech behind Airtable's AI capabilities
(22:22) Is Airtable going to become an AI-first company?
(25:15) Will AI kill programming as we know it?
(29:24) How do big enterprises think about AI?
(34:46) How did Airtable go from PLG to a large enterprise product?
(41:00) AI Categories
(47:47) "We definitely had our hiccups"
(51:20) Was PLG a ZIRP-era phenomenon?
(56:29) Howie's journey as a CEO -
In this episode, we sat down with Tomasz Tunguz (https://twitter.com/ttunguz), the founder of Theory Ventures and a leading voice in the tech investment space.
We discussed the transformative potential of Ethereum as a database company, the importance of data security in a decentralized world, and the evolving landscape of AI technologies from foundational models to AI-native applications.
📰 Article "What If LLMs Change the Business Model of the Internet?": https://tomtunguz.com/what-if-llms-change-the-business-model-of-the-internet/
✍️ Tomasz' blog: https://tomtunguz.com
Theory Ventures
Website - https://theory.ventures/
Twitter - https://twitter.com/Theoryvc
Tomasz Tunguz
LinkedIn - https://www.linkedin.com/in/tomasztunguz
Twitter - https://twitter.com/ttunguz
Blog - https://tomtunguz.com/
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturckLISTEN ON:
YouTube - https://www.youtube.com/@DataDrivenNYC/videos
Apple - https://podcasts.apple.com/us/podcast/the-mad-podcast-with-matt-turck/id1686238724
(00:00) Intro
(02:46) Tomasz has continued to invest in blockchain through the crypto winter. Why?
(06:59) Security and privacy as the main blockchain's use case.
(09:18) Blockchain and AI: how do they work together?
(11:02) Why does Theory Ventures not invest in AI hardware?
(12:28) Why do big companies invest in cloud infrastructure?
(15:35) An investor view on the foundation models.
(18:36) Is Gen AI going to replace traditional AI?
(20:57) Does the Theory Ventures invest in AI tooling companies?
(22:53) Is investing in Cloud companies better than investing in AI-powered applications?
(26:40) Copilot AI vs full-execution AI.
(28:38) A case for specialized LLMs.
(29:54) Gross margins in Gen AI: is it profitable?
(32:34) Modern Data Stack: is it still a thing to invest in?
(37:02) Microsoft Fabric and its impact on the market.
(38:50) Tomasz's thought on Motherduck and DuckDB.
(40:37) Where do BI tools fit in the Modern Data Stack?
(44:32) Why has the democratization of BI never happened?
(45:52) How do acquisitions happen? Can you engineer them?
(49:02) Key ingredients to build data infrastructure business.
(50:40) Tomasz is a founder now! How does it feel?
(53:15) Talking numbers: Theory Ventures' financial model. -
In this episode, we sat down with Renen Hallak, founder and CEO of VAST Data, a $9 billion company that's shaking the foundations of data storage, databases and compute functionality.
Through the conversation, we explore VAST's perspective on AI infrastructure, the process of selling over a billion dollars worth of software, and the technical innovations behind disaggregated, shared-everything architecture.
VAST Data
Website - https://www.vastdata.com/
Twitter - https://twitter.com/VAST_Data
Renen Hallak
LinkedIn - https://www.linkedin.com/in/renenh/
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro
(01:40) What is VAST Data?
(02:56) The company was started in stealth mode. Why?
(03:42) Did VAST get lucky with the gen AI explosion?
(04:27) VAST Data founding story
(05:57) How does the company work across 2 continents?
(06:48) What made you think that you can disrupt the market?
(09:23) VAST architecture explained
(23:08) Moving from data storage to databases
(25:01) What was the hardest thing to build?
(26:32) How does VAST work with open source
(26:54) A glimpse into the future products
(28:22) The world without VAST: how it would've looked like
(29:45) Who were VAST's first customers?
(30:56) How do hedge funds use VAST?
(32:08) VAST's sales strategy
(34:04) Renen's transition from technical founder to CEO
(36:01) How do you hire great people?
(37:07) What was the hardest thing on your journey as a CEO?
(38:43) $9B CEO daily routine
(40:17) Difference between offices in NY and Israel
(42:07) Renen's learnings from sales -
🔗 2024 MAD Landscape: https://mad.firstmark.com
📃 PDF: https://mattturck.com/landscape/mad2024.pdf
📃 Blog post: https://mattturck.com/mad2024/
In this episode, we delve into the 2024 machine learning, AI, and data scene (MAD), examining an evergrowing array of over 2011 logos, the meteoric rise of open-source AI, and the anticipated advancements in AI agents and edge AI technology.
Gain valuable perspectives on the saturated AI market, the dilemmas and prospects open source AI presents, and the continuous evolution of the modern data infrastructure. This episode covers a distinctive mix of analysis, industry perspectives, and foresight into the technological future.
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
Aman Kabeer (Investor)
LinkedIn - https://www.linkedin.com/in/aman-kabeer/
Twitter - https://twitter.com/AmanKabeer11
(00:00) Intro
(02:06) What is MAD?
(07:58) Open sourcing AI
(12:29) How open source affects commercial AI?
(21:02) Is the AI hype cycle over?
(26:39) Was 2023 a head fake for Gen AI? What about 2024?
(28:05) VC's perspective on AI
(30:54) Emerging of AI stack
(37:36) What are the areas VCs are excited about?
(41:04) Will full-stack AI platforms kill SaaS?
(42:42) Modern Data Stack: is it dead or alive?
(47:17) What's next for the MAD Landscape?
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In this episode, we sat down with Morgan McGuire, Chief Scientist of Roblox, and the mind behind the magic of the virtual universe. Together we explore the spectrum of creativity on Roblox, from no-code experiences to professional game development, dive deep into the cutting-edge AI tools Roblox is deploying, and how these tools are democratizing game development.
Tune in to embark on a journey into the heart of creativity, technology, and community with Roblox. This is not just about playing games; it's about creating the future, one experience at a time.
ROBLOX
Website - https://www.roblox.com
Twitter - https://twitter.com/Roblox
Morgan McGuire
LinkedIn - https://www.linkedin.com/in/morgan-mcguire-660120210
Twitter - https://twitter.com/casualeffects
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro
(01:05) Roblox is not a game, but a platform
(10:03) How does Roblox leverage Gen AI?
(13:34) How did the company start working on AI?
(21:26) AI Code Assist
(26:30) AI Material Generator
(32:07) ControlNet
(38:36) StarCoder
(43:40) Who works at Roblox?
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In this episode, we sat down with Benedict Evans, a leading voice in the tech industry and a former partner at Andreessen Horowitz.
Known for his sharp insights and forward-thinking analysis, Benedict shares his expert perspective on what generative AI means for the future of technology, business, and society at large.
Specifically, we dive deep into the evolving landscapes of generative AI, augmented and virtual reality, and the critical issue of AI bias.
Join us as Benedict Evans provides a nuanced analysis of cutting-edge tech and shares his insights and perspectives on the road ahead.
BENEDICT EVANS
LinkedIn - https://www.linkedin.com/in/benedictevans/
Threads - https://www.threads.net/@benedictevans
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro
(01:06) The AI platform shift in 2024
(05:54) Gen AI in 2024 vs. PC-boom in the 80-s
(13:24) Until AGI happens, there will be vertical-specific apps
(15:12) Should companies have an AI strategy?
(21:04) Platform shift OR paradigm shift?
(23:55) How should we think about AGI in 2024?
(34:08) Is gen AI grossly overhyped?
(36:27) AI bias and the hidden problems in data
(44:56) Apple Vision Pro and the future of AR/VR
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In this episode, we sit down with Gary Little, CEO of Foursquare, to discuss Foursquare's remarkable evolution from a social app to a leader in location intelligence. Gary discusses how Foursquare uses smartphone ubiquity to create a global map through crowdsourcing, covering 190 countries and over 200 million points of interest. Learn about the challenges of managing complex, real-time datasets and how Foursquare employs machine learning and knowledge graphs to analyze foot traffic and device movements. The conversation also covers the critical role of privacy and data security in location tracking, especially in light of recent regulatory changes.Gary explains Foursquare's platform strategy, drawing parallels with Amazon's AWS, to enable customers to process and utilize location data for their applications. FoursquareWebsite - https://location.foursquare.comTwitter - https://twitter.com/FoursquareGary Little (CEO)LinkedIn - https://www.linkedin.com/in/gary-little-0670ba4Twitter - https://twitter.com/garylittlefsqFIRSTMARKWebsite - https://firstmark.comTwitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/Twitter - https://twitter.com/mattturck(00:00) Intro
(01:10) Brief history of Foursquare
(03:07) What makes Foursquare's location data unique?
(05:17) Foursquare Platform. What is it?
(08:07) A glimpse into the future of Foursquare
(10:00) More customers want to process the data themselves. Why?
(13:42) Data privacy of today vs 10 years ago. What has changed?
(16:41) Foursquare Graph: what does it do?
(19:17) How is Foursquare utilizing AI?
(22:17) How will AR/VR influence location intelligence?
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In this episode, we dive into the fascinating world of AI art with Cris Valenzuela, CEO of Runway. Runway is a generative AI startup that co-invented Stable Diffusion, the deep learning technology that has captured the attention of the creative industry, including luminaries such as ASAP Rocky and Madonna's teams, by pushing the boundaries of digital creativity.
We explore how generative AI tools empower visual artists to unleash their imaginations without the need for Hollywood-size budgets. We also discuss the effect of AI on the entire creative industry, similar to how the camera changed things back in the day.
Join us for a glimpse into the future of creativity.
RUNWAY
Website - https://runwayml.com
Twitter - https://twitter.com/runwayml
Cris Valenzuela (Co-founder & CEO)
LinkedIn - https://www.linkedin.com/in/cvalenzuelab
Twitter - https://twitter.com/c_valenzuelab
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
Foursquare
Website - https://location.foursquare.com
Twitter - https://twitter.com/Foursquare
(00:00) Intro
(00:55) What is Runway?
(03:09) Runway started before the GenAI boom. How?
(04:41) What do people get wrong about GenAI?
(07:18) How AI is going to change creative software?
(08:44) What is Gen-2?
(12:02) Runway's role in creating Stable Diffusion
(14:25) Gen-1: a model or a product?
(15:11) Runway's evolution from image generation to video
(18:18) Runway partnered with Getty. Why?
(19:52) How has the AI video generation ecosystem evolved?
(21:58) Adoption cyсle for AI video generation. Where are we now?
(24:45) Challenges of building a research-focused company
(26:25) How to build and maintain a soul in a startup?
(28:27) "It's like an invention of new art form" -
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Join us in this exciting episode as we dive into the world of enterprise AI with Florian Douetteau, co-founder and CEO of Dataiku, the leading enterprise AI platform targeting Global 2000 companies.
Since its founding in 2013, Dataiku has been at the forefront of democratizing AI in the enterprise. We'll explore the current state of deployment of AI in businesses around the world, dive deep into the differences between generative AI and traditional AI, explore emerging Generative AI uses cases in the enterprise, and get a sneak peek into Dataiku's latest breakthrough, the LLM Mesh, aimed at simplifying the use of multiple Generative AI models for companies. We'll also tackle the big challenges companies face when adopting AI, from managing costs to dealing with the uncertainties of Generative AI.
This episode was recorded live at a recent Data Driven NYC, the monthly in-person event organized by FirstMark since 2011, hosted this month by our partners at Foursquare, the location intelligence company, at their beautiful headquarters.
Dataiku
Website - https://www.dataiku.com/
Twitter - https://twitter.com/dataiku
Florian Douetteau
LinkedIn - https://www.linkedin.com/in/fdouetteau
Twitter - https://twitter.com/fdouetteau
FIRSTMARK
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck
Twitter - https://twitter.com/mattturck
Foursquare
Website - https://location.foursquare.com
Twitter - https://twitter.com/Foursquare
(00:00) Intro
(01:09) What is Dataiku?
(02:03) Is the market ready for AI?
(04:33) Traditional AI vs Generative AI
(08:33) What a company should know before diving into Generative AI?
(10:18) Cost of Generative AI adoption
(12:10) What blocks the AI adoption?
(14:31) Dataiku product tour
(16:34) How to build one product for different audiences
(17:45) LLM Mesh: what is it?
(21:10) Evolution of platform building with Gen AI
(22:17) Enterprise AI motion in 2024
(23:28) Dataiku's partnerships
(24:24) Being platform-first as a startup
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In this episode, we sit down with Bob Moore, the CEO of Crossbeam, who turned a $2.6 billion mistake into a masterclass on Ecosystem-Led Growth (ELG). Fresh off publishing his new book, Bob shares why ELG is the future of business growth, challenging traditional strategies with data-driven insights and partnerships.
Bob reveals how Crossbeam can help companies of any size leverage ELG to achieve remarkable growth. He dives into the role of data in ELG, the impact of AI on marketing, and practical steps for implementing ELG in your own company.
From discussing the "slow heat death" of traditional growth strategies to unveiling the potential of data-driven partnerships, this episode is packed with eye-opening revelations. Bob also tackles the practical steps companies can take to implement ELG, making this a must-watch for CEOs, leaders, and entrepreneurs aiming to catapult their businesses into a new era of growth.
Book: https://www.amazon.com/Ecosystem-Led-Growth-Blueprint-Marketing-Partnerships/dp/1394226837
Crossbeam
Website - https://www.crossbeam.com
Twitter - https://twitter.com/crossbeam
Bob Moore
LinkedIn - https://www.linkedin.com/in/robertjmoore/
Twitter - https://twitter.com/robertjmoore
FirstMark
Website - https://firstmark.com
Twitter - https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
(00:00) Intro(00:43) Bob recently wrote a book. Why did he do that as a CEO?(03:20) Bob's $2.6 billion mistake(12:15) What is ELG?(17:30) How does Crossbeam work?(20:51) Why do we need another type of go-to-market motion?(25:00) AI is killing inbound/outbound marketing(31:50) Applying ELG to your company(36:13) When should you do ELG and partnerships?(43:34) Outro
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In this episode, we sat down with Emi Gal, founder and CEO of Ezra, a startup that leverages AI to detect cancer early and inexpensively. Emi provides insights into the landscape of the healthcare sector and talks about the differences between building an AI startup in healthcare versus SaaS. Turns out that "(In AI skills)... are not that transferable."EZRAWebsite - https://ezra.comTwitter - https://twitter.com/ezraincEmi GalLinkedIn - https://www.linkedin.com/in/emigalTwitter - https://twitter.com/emigalFIRSTMARKWebsite - https://firstmark.comTwitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/Twitter - https://twitter.com/mattturck(00:00) Intro(01:50) Ezra raised $21 million in series B round(02:55) The origin of Ezra(06:06) Sourcing AI talent(06:52) Building a proof of concept(09:05) The tipping point for the product market fit(10:57) Y Combinator wants more MRI startups. Why?(11:37) Ezra's vision for MRI(13:25) Is it covered by insurance?(16:15) Full stack vs Software only(20:00) Training AI(22:55) Building an MRI database(25:45) Will radiologists get replaced by AI?(27:52) Creating reports with Generative AI (30:50) Can we trust AI in healthcare?(33:44) What are the specific challenges of building an AI startup?(39:01) Healthcare entrepreneurship(43:59) Staying fit as a CEO: Emi's mental and physical health routine(48:28) Plans for 2024
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In this episode, we sat down with Des Traynor, co-founder of Intercom, to explore the seismic shift towards Artificial Intelligence in customer service software. Intercom has gone all-in to embrace AI as people's expectations of what chatbots can do started growing with the release of ChatGPT. Des shares the pivotal moments and strategic decisions that led to this transition, highlighting the urgency and vision that propelled Intercom to integrate AI into their core offerings. Des also delves into the challenges of building a bicontinental startup and the strategic pivot towards becoming an AI-first company. Tune in for an enlightening discussion on the strategy and journey of adapting AI.INTERCOMWebsite - https://www.intercom.comTwitter - https://twitter.com/intercomDes TraynorLinkedIn - https://www.linkedin.com/in/destraynor/Twitter - https://twitter.com/destraynorFIRSTMARKWebsite - https://firstmark.comTwitter - https://twitter.com/FirstMarkCapMatt Turck (Managing Director)LinkedIn - https://www.linkedin.com/in/turck/Twitter - https://twitter.com/mattturck(00:00) Intro
(01:16) How did Intercom make a transition to a generative AI product (Fin)?
(05:34) Did the Intercom manifesto play a role in the transition?
(07:16) What was the Intercom before Fin?
(09:01) How much development effort did you spend on AI?
(12:31) UX
(15:20) People used to hate chatbots
(17:51) GPT and building layers around it
(20:50) The future of customer service
(23:57) GPT-4/Llama/Mistral/Claude
(25:58) Are multimodal AI-bots the future?
(27:08) AI-hallucination
(30:11) Customization
(34:34) Will Fin get a voice?
(36:26) Customer support cost and impact on profitability
(39:58) How much should you charge?
(45:26) AI-bot resolution rate
(46:43) Can bots take action?
(48:40) AI-adoption
(51:14) How the Intercom team evolve
(53:38) How did 4 Irish guys create a bi-continental startup?
(56:17) Work distribution
(58:38) Tech in Europe vs tech in the US
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In this episode, we explore the dynamic world of modern analytics with Tristan Handy, CEO of dbt Labs (https://twitter.com/jthandy). DBT, which helps more than 30,000 enterprises ship trusted data products faster, has raised more than $400 million dollars, most recently at a $4B valuation.
We discuss how dbt has revolutionized analytics engineering, enabling seamless data transformation and orchestration in the cloud. This innovation fosters greater collaboration among data teams and integrates software engineering principles into data analytics workflows.
We also talk about dbt's Semantic Layer, a game-changer that streamlines data operations by standardizing key business metrics for consistent use across various analytical tools.
In this conversation, we tackle pressing questions about the current state and future of data management and analytics. Is the "modern data stack" becoming obsolete? What's next for data engineering? And how is AI reshaping the analytics landscape?
Tune in to discover our insights.
📰 Is the "Modern Data Stack" Still a Useful Idea?
https://roundup.getdbt.com/p/is-the-modern-data-stack-still-a
DBT
Website - https://www.getdbt.com/
Twitter - https://twitter.com/getdbt
Tristan Handy (CEO & Co-Founder):
LinkedIn - https://www.linkedin.com/in/tristanhandy/
Twitter - https://twitter.com/jthandy
Is the "Modern Data Stack" Still a Useful Idea? - https://roundup.getdbt.com/p/is-the-modern-data-stack-still-a?r=oc02&utm_campaign=post&utm_medium=web
FIRSTMARK
Website: https://firstmark.com
Twitter: https://twitter.com/FirstMarkCap
Matt Turck (Managing Director)
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
LISTEN ON:
Spotify - https://open.spotify.com/show/7yLATDSaFvgJG80ACcRJtq
Apple - https://podcasts.apple.com/us/podcast/the-mad-podcast-with-matt-turck/id1686238724
00:00 - Intro
02:43 - What is the Modern Data Stack?
05:57 - Is the Modern Data Stack dead?
12:23 - What's the alternative?
16:24 - Where is analytics engineering heading?
20:02 - The Reverse ETL market
23:21 - The role of AI in analytics engineering
27:47 - Will analytics engineers become the prompt engineers?
29:78 - Is the MDS part of the emerging generative AI stack?
33:51 - The Semantic Layer
37:49 - dbt's plans for the near future
41:17 - Hiring at different stages of the business
44:21 - Going from open-source to commercial
46:40 - Market situation vs. sales strategy
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In this episode, we sat down with Bob van Luijt (https://twitter.com/bobvanluijt), the CEO of Weaviate, diving into the cutting-edge world of vector databases and their role in the AI revolution.
Weaviate is an open source, AI-native vector database that helps developers create intuitive and reliable AI-powered applications. Weaviate sets itself apart with its vector search engine that integrates machine learning directly into its core, enabling more nuanced and context-aware search capabilities for AI-driven applications.
This conversation explores vector databases (the core infrastructure behind generative models), the role of Retrieval-Augmented Generation (RAG), and how open source is driving commercial use cases.
WEAVIATE
Website - https://weaviate.io
Twitter - https://twitter.com/weaviate_io
Bob van Luijt (Co-Founder & Co-CEO):
LinkedIn - https://www.linkedin.com/in/bobvanluijt
Twitter - https://twitter.com/bobvanluijt
Matt Turck:
LinkedIn - https://www.linkedin.com/in/turck/
Twitter - https://twitter.com/mattturck
DATA DRIVEN NYC
This episode of the MAD Podcast was recorded live at Data Driven NYC, an event series organized by FirstMark Capital. The events are free and held monthly in New York, currently with the support of Foursquare.
If you wish to attend and be notified of future events, please follow FirstMark on Eventbrite at https://www.eventbrite.com/o/firstmark-capital-2215570183
01:00 What is RAG?
06:20 Why is embedding models is such a hot topic right now?
08:06 What is your assessment of RAG?
09:53 Generative feedback loops
11:46 What is Hybrid Search?
15:15 What makes Weaviate special?
16:53 What about security?
17:45 Does RAG accelerated the need for real-time data?
19:27 How to define good vector database?
22:11 What do you think about general purpose databases entering the field of vector-based databases?
23:47 Interesting use cases of Weaviate
25:27 What’s your sense of the current state of the market?
26:53 Open source vs commercial product on Weaviate
29:23 How did it all get started?
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