In this episode, we dive into the world of generative AI with May Habib, co-founder of Writer, a platform transforming enterprise AI use. May shares her journey from Qordoba to Writer, emphasizing the impact of transformers in AI. We explore Writer's graph-based RAG approach, and their AI Studio for building custom applications. We also discuss Writer's Autonomous Action functionality, set to revolutionize AI workflows by enabling systems to act autonomously, highlighting AI's potential to accelerate product development and market entry with significant increases in capacity and capability. Writer Website - https://writer.com X/Twitter - https://x.com/get_writer May Habib LinkedIn - https://www.linkedin.com/in/may-habib X/Twitter - https://x.com/may_habib FIRSTMARK Website - https://firstmark.com X/Twitter - https://twitter.com/FirstMarkCap Matt Turck (Managing Director) LinkedIn - https://www.linkedin.com/in/turck/ X/Twitter - https://twitter.com/mattturck This session was recorded live at a recent Data Driven NYC, our in-person, monthly event series, hosted at Ramp's beautiful HQ. If you are ever in New York, you can join the upcoming events here: https://www.eventbrite.com/o/firstmark-capital-2215570183 (00:00) Intro (01:47) What is Writer? (02:52) Writer's founding story (06:54) Writer is a full-stack company. Why? (07:57) Writer's enterprise use cases (10:51) Knowledge Graph (17:59) Guardrails (20:17) AI Studio (23:16) Palmyra X 004 (27:18) Current state of the AI adoption in enterprises (28:57) Writer's sales approach (31:25) What May Habib is excited about in AI (33:14) Autonomous Action use cases
Nathan Benaich, founder and GP at VC firm Air Street Capital, publishes every year "State of AI", one of the most widely-read and comprehensive reports on all things AI across research, industry, and policy. In this episode, we sit down with Nathan to discuss some of the highlights of the 2024 edition of the report, including the "vibes" shift in the industry from existential risk concerns last year to the current monetization race, the financial success of the foundation model labs, how a generative AI app could top the Apple Store charts in 2025, and the challenges facing humanoid robotics. State of AI 2024 report: https://www.stateof.ai/2024-report-launch State of AI 2024 video: https://youtu.be/EVMbnPOuUl0 Air Street Capital Website - https://www.airstreet.com X/Twitter - https://x.com/airstreet Nathan Benaich LinkedIn - https://www.linkedin.com/in/nathanbenaich X/Twitter - https://x.com/nathanbenaich FirstMark Website - https://firstmark.com X/Twitter - https://twitter.com/FirstMarkCap Matt Turck (Managing Director) LinkedIn - https://www.linkedin.com/in/turck/ X/Twitter - https://twitter.com/mattturck (01:08) Who is Nathan Benaich? (04:57) "Vibe" shift in AI (09:13) Current state of the foundation models (22:01) AI companies vs. SaaS (23:31) AI consumer apps (25:49) AI applications from a VC's perspective (29:25) "You don't need to be an AI engineer to build an AI company" (30:46) AI in robotics (34:36) AI regulations in Europe (40:55) Predictions on the future of AI (49:30) Nathan Benaich's favorite sources of information
In this special episode of the MAD Podcast, Matt Turck and Aman Kabeer from FirstMark delve into the AI market from a venture investor perspective, in the final weeks of an incredibly packed and exciting 2024. They comment on their favorite news stories, such as OpenAI's record-breaking $6.6 billion funding round and the massive $200B investments in AI infrastructure by Meta, Google, and Amazon. They tackle the latest trends in funding and valuations in both public and private markets, debate the critical question of whether we're in an AI bubble, examine the current state of AI demand, the potential of scaling laws, and the future of AI-driven innovation. They then discuss where they see opportunities for startups and investors across AI hardware, compute, foundation models, AI tooling, and both consumer and enterprise AI applications. FIRSTMARK Website - https://firstmark.com X/Twitter - https://twitter.com/FirstMarkCap Matt Turck (Managing Director) LinkedIn - https://www.linkedin.com/in/turck/ X/Twitter - https://twitter.com/mattturck Aman Kabeer (Investor) LinkedIn - https://www.linkedin.com/in/aman-kabeer/ X/Twitter - https://x.com/AmanKabeer11 (00:00) Intro (02:20) The Year of Record-Breaking Evaluations and Investments (05:23) AI's Environmental Impact and Nuclear Revival (06:48) AI Valuations and Market Dynamics (17:01) Are We in an AI Bubble? (25:01) AI Progress and Demand (35:06) AI's Role in Consumer Applications (41:02) AI's Influence on SaaS and Business Models (50:55) AI's Role in Enterprise Transformation (01:04:00) The Future of AI: Apps and Agents
Before he founded Modal, Erik Bernhardsson created Spotify's music recommendation system. Today he's bringing a consumer app approach to radically simplifying developer experience for data and AI projects on the Modal platform. In this episode, we dive into the broader AI compute landscape, discussing the roles of hyperscalers, GPU clouds, inference platforms, and the emergence of alternative AI cloud providers. Erik gives us a product tour of the Modal platform, provides insights into the AI industry's shift from training to inference as the primary use case, and speculates on the future of AI-native consumer applications. Learn about Modal's commitment to fast feedback loops, their cloud maximalist approach, their dedication to building a product that developers truly love, as well as founder lessons Erik learned along the way. Erik's blog: https://erikbern.com "It's hard to write code for humans": https://erikbern.com/2024/09/27/its-hard-to-write-code-for-humans Modal Website - https://modal.com Twitter - https://x.com/modal_labs Erik Bernhardsson LinkedIn - https://www.linkedin.com/in/erikbern Twitter - https://x.com/bernhardsson 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 (01:35) What is Modal? (02:18) Current state of AI compute space (09:54) Erik's path to starting Modal (13:57) Core elements of the Modal platform (28:52) Is serverless the right level of abstraction for AI compute? (33:35) Balancing costs: GPU vendor fees vs. customer pricing (37:56) Designing products for humans (42:43) Modal's early go-to-market motion (45:32) Managing early engineering team (48:26) The only correct way to add a new function to the company (50:07) Building company in NYC (52:05) Modal's roadmap (54:04) Erik's predictions on AI
A founding engineer on Google BigQuery and now at the helm of MotherDuck, Jordan Tigani challenges the decade-long dominance of Big Data and introduces a compelling alternative that could change how companies handle data. Jordan discusses why Big Data technologies are an overkill for most companies, how MotherDuck and DuckDB offer fast analytical queries, and lessons learned as a technical founder building his first startup. Watch the episode with Tomasz Tunguz: https://youtu.be/gU6dGmZzmvI Website - https://motherduck.com Twitter - https://x.com/motherduck Jordan Tigani LinkedIn - https://www.linkedin.com/in/jordantigani Twitter - https://x.com/jrdntgn 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 the Small Data? (06:56) Marketing strategy of MotherDuck (08:39) Processing Small Data with Big Data stack (15:30) DuckDB (17:21) Creation of DuckDB (18:48) Founding story of MotherDuck (24:08) MotherDuck's community (25:25) MotherDuck of today ($100M raised) (33:15) Why MotherDuck and DuckDB are so fast? (39:08) The limitations and the future of MotherDuck's platform (39:49) Small Models (42:37) Small Data and the Modern Data Stack (46:47) Making things simpler with a shift from Big Data to Small Data (50:04) Jordan Tigani's entrepreneurial journey (58:31) Outro
With a $4.5B valuation, 5M AI builders and 1M public AI models, Hugging Face has emerged as the key collaboration platform for AI, and the heart of the global open source AI community. In this episode of The MAD Podcast, we sit down with Clément Delangue, its co-founder and CEO, and delve deep into Hugging Face's journey from a fun chatbot to a central hub for AI innovation, the impact of open-source AI and the importance of community-driven development, and discuss the shift from text to other AI modalities like audio, video, chemistry, and biology. We also cover the evolution of Hugging Face's business model, and the different approach to company culture that the founders have implemented over the years. Hugging Face Website - https://huggingface.co Twitter - https://x.com/huggingface Clem Delangue LinkedIn - https://www.linkedin.com/in/clementdelangue Twitter - https://x.com/clemdelangue 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 (01:46) Miami vs. New York vs. San Francisco (03:25) Current state of open source AI (11:12) Government regulation of AI (13:18) What is open source AI? (15:21) Open source AI: China vs U.S. (18:32) LLMs vs. SLMs (22:01) Are commercial LLMs just 'Training Wheels' for enterprises? (24:26) Software 2.0: built with AI (28:03) Hugging Face founding story (37:03) Are there any competitors? (44:06) Most interesting models on Hugging Face (50:35) Shifting focus in enterprise solutions (55:06) Bloom & Idefix (58:44) The culture of Hugging Face (01:04:44) The future of Hugging Face
This episode is a captivating conversation with Richard Socher, serial entrepreneur, investor, and AI researcher. Richard elaborates on why he likens the impact of AI to the Industrial Revolution, the Enlightenment, and the Renaissance, discusses important current issues in AI, such as scaling laws and agents, provides a behind-the-scenes tour of YOU.com and its evolving business model, and finally describes his current investment strategy in AI startups. You.com Website - https://you.com/business Twitter - https://x.com/youdotcom Richard Socher LinkedIn - https://www.linkedin.com/in/richardsocher Twitter - https://x.com/richardsocher 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 (02:00) "AI era is the Industrial Revolution, Renaissance, and the Enlightenment combined" (07:49) Top-performers in the Age of AI (11:15) Comeback of the Renaissance Person (13:05) People tried to stop Richard from doing deep learning research. Why? (14:34) Jevons paradox of intelligence (17:08) Scaling Laws in Deep Learning (23:23) Can Deep Learning and Rule-Based AI coexist? (25:42) Post-transformers AI Architecture (28:20) Achieving AGI and ASI (36:43) AI for everyday tasks: how far is it? (44:50) AI Agents (55:45) Evolution of You.com (01:02:11) Technical side of You.com (01:06:46) Is AI getting cheaper? (01:13:05) What is AIX Ventures? (01:16:36) VC landscape of 2024 (01:24:31) Research vs Entrepreneurship (01:26:12) OpenAI’s transformation and its impact on the industry
In this episode, we sit down with Tobie Morgan Hitchcock, the founder of SurrealDB, to dive deep into the evolving world of databases and the future of data storage, querying, and real-time analytics. SurrealDB isn’t just another database — it’s a multi-model database that merges document, graph, and time-series data, making it easier for developers to consolidate their backend without sacrificing performance. You'll learn how SurrealDB separates storage from compute for scalability, its innovative take on graph databases, and the radical decision to rewrite the entire platform in Rust. Tobie also shares how SurrealDB is designed to handle real-time analytics and integrate AI/ML models directly inside the database. If you're curious about the future of databases, this episode is packed with insights you won’t want to miss. SurrealDB Website - https://surrealdb.com Twitter - https://x.com/SurrealDB Tobie Morgan Hitchcock: LinkedIn - https://www.linkedin.com/in/tobiemorganhitchcock Twitter - https://x.com/tobiemh 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(02:03) What is SurrealDB?(02:53) How did SurrealDB get started?(09:10) The Challenges of Building a Database from Scratch(10:36) Why SurrealDB Chose Rust(12:54) A Deep Dive into SurrealDB’s Unique Features(19:30) Why Now?(26:32) What Sets SurrealDB Apart from Other Databases(30:01) SurrealDB’s Role in the Future of AI and Machine Learning(32:45) Why Developers Are Choosing SurrealDB(36:14) What’s New in SurrealDB 2.0?(40:10) SurrealDB Cloud: Scalability Meets Simplicity(42:21) How SurrealDB Fits into the Competitive Database Landscape(45:37) Early Lessons from Building SurrealDB(48:34) Co-Founding SurrealDB with His Brother
In this episode, we dive deep into the story of how Datadog evolved from a single product to a multi-billion dollar observability platform with its co-founder, Olivier Pomel. Olivier shares exclusive insights on Datadog's unique approach to product development—why they avoid the "Apple approach" of building in secret and instead work closely with customers from day one. You’ll hear about the early days when Paul Graham of Y Combinator turned down Datadog, questioning their lack of a first product. Olivier also reveals the strategies behind their iterative product launches and why they insist on charging early to ensure they’re delivering real value. The second half of the conversation is focused on all things AI and data at Datadog - the company's initial reluctance to use AI in its products, how Generative AI changed everything, and Datadog's current AI efforts including Watchdog, Bits AI and Toto, their new time series foundational model. We close the episode by asking Olivier about his thoughts on the topic du jour: founder mode! ▶️ Listen to 2020 Data Driven NYC episode with Oliver Pomel: https://www.youtube.com/watch?v=oXKEFHeEvMs DATADOG Website - https://www.datadoghq.com Twitter - https://x.com/datadoghq Olivier Pomel LinkedIn - https://www.linkedin.com/in/olivierpomel Twitter - https://x.com/oliveur 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
In this episode, we sit down with Ali Dasdan, CTO of ZoomInfo, a titan in the B2B sector, who harnesses vast datasets and advanced AI to redefine sales and marketing for over 35,000 global customers with $21.2 billion in annualized revenue. We delve deep into ZoomInfo's AI initiatives, including their transformative 'Copilot,' explore sophisticated data management, and discuss their dual platforms catering to internal and customer-facing needs. ZoomInfo Website - https://www.zoominfo.com Twitter - https://x.com/zoominfo Ali Dasdan LinkedIn - https://www.linkedin.com/in/dasdan Twitter - https://x.com/alidasdan 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 (02:03) What is ZoomInfo (04:47) Data as service (06:15) Ali Dasdan's story (07:31) Organization of ZoomInfo (10:48) ZoomInfo Data Platform (21:02) Lessons from building a data platform (23:19) AI application at ZoomInfo (27:58) ZoomInfo's Copilot (37:43) ZoomInfo AI toolstack (39:30) Working with small vs. big companies in the AI business (43:39) Using data and AI for internal productivity
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
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
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
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?
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.
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. AIRTABLE Website - https://www.airtable.com/ Twitter - https://x.com/airtable Howie Liu LinkedIn - https://www.linkedin.com/in/howieliu/ Twitter - https://x.com/howietl 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(02:40) 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/FirstMarkCap Matt Turck (Managing Director) LinkedIn - https://www.linkedin.com/in/turck/ Twitter - https://twitter.com/mattturck LISTEN 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?