The MAD Podcast: Machine Learning, AI & Data with Matt Turck

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" -

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

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

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.

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.

(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

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

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?

Last week, we sat down with Alex Rinke (https://twitter.com/alexanderrinke), Co-founder & Co-CEO of Celonis, to explore how AI and automation are transforming business operations at large enterprises.

Celonis is the pioneer of "process mining" - the technology that uses graph databases, AI, and automation to analyze processes, find inefficiencies and their root causes, and solve them.

Most recently valued at $13B, Celonis is one of the most valuable startups globally. But Alexander and his two co-founders started Celonis while still in college on a $15,000 budget.

In this conversation, we talked about the early days of Celonis, how Alex acquired his first enterprise clients without inside industry connections, how Celonis navigates go-to-market for a product with an expansive scope, and much more.

CELONIS

Website - https://www.celonis.com

Twitter - https://twitter.com/Celonis

Alex Rinke (Co-Founder & Co-CEO):

Twitter: https://twitter.com/alexanderrinke

LinkedIn: https://www.linkedin.com/in/alexander-rinke-10733061/

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

00:00 - Intro

02:02 - What is Process Mining?

05:20 - How Celonis got started

07:42 - “We had our first prototype in three weeks”

09:36 - Pivotal partnership with ACP

12:12 - How did Celonis find product-market-people fit?

14:14 - Penetrating the global market

16:19 - Technical deep dive into the Celonis’ product

19:29 - Celonis finds process gaps completely automatically

21:15 - Who is the average user of Celonis inside companies?

22:11 - How Celonis uses Generative AI

24:54 - Acquisition of Symbio

25:56 - How to keep the fire of innovation inside the team?

27:49 - How to bring a very horizontal product to market?

32:24 - Scaling yourself as a leader

34:15 - Glimpse into the future of Celonis

35:37 - Outro

We are so excited today to be joined by Brandon Duderstadt, CEO + Cofounder, and Zach Nussbaum, Machine Learning Engineer, from Nomic AI. They discuss how Nomic AI is building tools like Atlas + GPT4all that enable everyone to interact with AI scale datasets and run models on consumer computers - and - stay tuned for an exciting announcement about their newest product release later in the podcast.

Thanks for joining us for the first episode of Season 2 of the MAD Podcast. We will be back to our regular weekly schedule with new conversations with leaders in the Machine Learning, AI and data landscape. If you like this show, you can find the video recording of this episode -- along with many, many more -- on the Data Driven NYC channel on YouTube.

NOMIC AI

www.nomic.ai

twitter.com/nomic_ai

www.linkedin.com/in/bstadt/

www.linkedin.com/in/zach-nussbaum/

FIRSTMARK

firstmark.com

twitter.com/FirstMarkCap

Matt Turck (Managing Director)

www.linkedin.com/in/turck/

twitter.com/mattturck

Data Driven NYC YouTube Channel

FirstMark Capital Eventbrite

0:46 - What is Nomic AI & how it got started

5:57 - Building GPT4ALL

7:23 - Running LLMs on a personal computer

16:00 - Nomic Atlas

21:33 - Launching Nomic Embed

28:10 The Importance of Data in AI

31:10 - Benchmarking LLMs

32:56 - The Future of Nomic AI

36: 22 - Building an AI Startup in New York

39:10 - Nomic AI is hiring

Today, we’re thrilled to be joined by Eiso Kant, CTO + Co-Founder of Poolside, the buzzy new AI tool for software development. Eiso and Matt talk about Poolside’s foundational model, the critical role of data quality in AI, the importance of controlling all levels of the stack and the merits of building a global AI company out of Europe, and more. 

Thank you to everyone who has joined us for Season 1 of the MAD Podcast. We will be taking a short break for the winter holidays and will be back with an exciting new lineup of great speakers for Season 2 on Wednesdays in January. If you like this show, you can find the video recording of this episode -- along with many more -- on the Data Driven NYC channel on YouTube. Important links are in the show notes below.

Data Driven NYC YouTube Channel

FirstMark Capital Eventbrite

twitter.com/eisokant

poolside.ai

twitter.com/mattturck

linktr.ee/mattturck

Show Notes:

[00:38:00] Introducing Eiso Kant, Co-founder and CTO of the AI startup, Poolside;

[00:39:16] Eiso's Background; his journey, from starting as a young programmer to founding several companies, including Source{d}, a pioneer in applying deep learning to software source code;

[00:40:33] Formation of Poolside; the collaboration between Eiso and his co-founder, Jason Warner, who was previously the CTO of GitHub and VC with Redpoint Ventures;

[00:42:14] Poolside's Vision and potential to improve software development;

[00:47:17] Narrowing Vision to Product Development; the importance of sequence in a company's growth, focusing on AI pair programming assistants as a start, moving towards a more autonomous future;

[00:50:32] Initial Product Focus, user base, and approach to providing a vertically integrated AI stack for developers;

[00:53:05] Reinforcement Learning from Code Execution Feedback;

[01:02:29] Data Handling and Synthetic Data Generation; the importance of data quality and Poolside's strategy for generating and refining training data;

[01:12:05] Engineering Behind Poolside's AI; the challenges and strategies Poolside is adopting, including building a team of strong engineers and creating a scalable architecture from scratch;

[01:16:52] Choosing Europe as a Base for Poolside;

[01:20:22] Poolside's Future Plans; the roadmap for Poolside, including launching products and APIs, exploring enterprise solutions, and creating a sustainable revenue-generating business;