Startup Valuations, Biotech’s Crunch & AI’s Massive TAM | E2147
Today’s show:
It’s another blockbuster panel of insiders, as Alex sits down with Astasia Myers from Felicis, Matt Turck from First Mark Capital, and D.A. Wallach of Time BioVentures. AI is reshaping early-stage investing, with startups raising record-setting rounds adn chasing $100B+ markets. Meanwhile, biotech faces a “Great Depression” as public markets stay shut, putting added pressure on private capital. In healthcare, AI-powered virtual doctors promise to bring world-class medical advice to everyone, while fertility tech could revolutionize IVF by automating embryo handling and slashing costs. Hear our VC experts exclusive thoughts on these trends and much more!
Timestamps:
(2:21) The post-Q2 landscape and everyone’s immediate reactions
(05:00) Why biotech is in a “Great Depression,” even for AI companies!
(9:36) CLA - Get started with CLA's CPAs, consultants, and wealth advisors now at https://claconnect.com/tech(12:14) Overpriced vs. high-performing: Do high prices ALWAYS mean low expected returns and vice versa?
(14:50) Mega markets: how AI is different from past software shifts(18:58) Everyone’s companies are CRUSHING IT: why genAI has crazy tailwinds right now
(20:33) Sentry - New users get 3 months free of the Business plan (covers 150k errors). Go to http://sentry.io/twist and use code TWIST(21:46) Product-market fit and revenue durability in AI(24:29) Marketing and community development for early stage founders(25:14) AI advancements in humor, avatars, and healthcare(29:30) Public - Take your investing to the next level with Public. Build a multi-asset portfolio and earn 4.1% APY on your cash—with no fees or minimums. Start now at public.com/twist.(30:45) Healthcare innovation and AI foundation models(35:37) AI differentiation, OpenAI valuation, and infrastructure companies(43:08) User experience in LLMs and AI inference costs(51:21) AI healthcare applications and founding team trends(56:28) Hiring trends, burn rates, and outsourcing in biotech(1:01:51) Government investment in biotech and the European AI ecosystem(1:06:43) Academic founders and the Felicis Fellows program(1:09:10) Recent exits and the outlook for the upcoming quarters(1:12:27) Innovations in fertility treatments and prenatal testing(1:15:51) Summary of bullish trends and future outlook(1:16:14) Closing remarks and future check-in plans
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Mapping The Data Infrastructure Landscape As A Venture Capitalist
Summary
The data ecosystem has been building momentum for several years now. As a venture capital investor Matt Turck has been trying to keep track of the main trends and has compiled his findings into the MAD (ML, AI, and Data) landscape reports each year. In this episode he shares his experiences building those reports and the perspective he has gained from the exercise.
Announcements
Hello and welcome to the Data Engineering Podcast, the show about modern data management
Businesses that adapt well to change grow 3 times faster than the industry average. As your business adapts, so should your data. RudderStack Transformations lets you customize your event data in real-time with your own JavaScript or Python code. Join The RudderStack Transformation Challenge today for a chance to win a $1,000 cash prize just by submitting a Transformation to the open-source RudderStack Transformation library. Visit dataengineeringpodcast.com/rudderstack today to learn more
Your host is Tobias Macey and today I'm interviewing Matt Turck about his annual report on the Machine Learning, AI, & Data landscape and the insights around data infrastructure that he has gained in the process
Interview
Introduction
How did you get involved in the area of data management?
Can you describe what the MAD landscape report is and the story behind it?
At a high level, what is your goal in the compilation and maintenance of your landscape document?
What are your guidelines for what to include in the landscape?
As the data landscape matures, how have you seen that influence the types of projects/companies that are founded?
What are the product categories that were only viable when capital was plentiful and easy to obtain?
What are the product categories that you think will be swallowed by adjacent concerns, and which are likely to consolidate to remain competitive?
The rapid growth and proliferation of data tools helped establish the "Modern Data Stack" as a de-facto architectural paradigm. As we move into this phase of contraction, what are your predictions for how the "Modern Data Stack" will evolve?
Is there a different architectural paradigm that you see as growing to take its place?
How has your presentation and the types of information that you collate in the MAD landscape evolved since you first started it?~~
What are the most interesting, innovative, or unexpected product and positioning approaches that you have seen while tracking data infrastructure as a VC and maintainer of the MAD landscape?
What are the most interesting, unexpected, or challenging lessons that you have learned while working on the MAD landscape over the years?
What do you have planned for future iterations of the MAD landscape?
Contact Info
Website
@mattturck on Twitter
MAD Landscape Comments Email
Parting Question
From your perspective, what is the biggest gap in the tooling or technology for data management today?
Closing Announcements
Thank you for listening! Don't forget to check out our other shows. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning.
Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes.
If you've learned something or tried out a project from the show then tell us about it! Email hosts@dataengineeringpodcast.com) with your story.
To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers
Links
MAD Landscape
First Mark Capital
Bayesian Learning
AI Winter
Databricks
Cloud Native Landscape
LUMA Scape
Hadoop Ecosystem
Modern Data Stack
Reverse ETL
Generative AI
dbt
Transform
Podcast Episode
Snowflake IPO
Dataiku
Iceberg
Podcast Episode
Hudi
Podcast Episode
DuckDB
Podcast Episode
Trino
Y42
Podcast Episode
Mozart Data
Podcast Episode
Keboola
MPP Database
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
Sponsored By:
Rudderstack: 
Businesses that adapt well to change grow 3 times faster than the industry average. As your business adapts, so should your data. RudderStack Transformations lets you customize your event data in real-time with your own JavaScript or Python code. Join The RudderStack Transformation Challenge today for a chance to win a $1,000 cash prize just by submitting a Transformation to the open-source RudderStack Transformation library. Visit [RudderStack.com/DEP](https://rudderstack.com/dep) to learn more
Support Data Engineering Podcast
20VC: Is Big Data Still A Thing with Matt Turck, Managing Director at FirstMark Capital
Matt Turck is Managing Director of FirstMark Capital where he invests across a broad range of early-stage enterprise and consumer startups. Prior to FirstMark, he was a Managing Director at Bloomberg Ventures, the investment and incubation arm of Bloomberg LP. Previously, Matt was the co-founder of TripleHop Technologies, a venture-backed enterprise search software startup that was acquired by Oracle. Matt organizes two large monthly events, Data Driven NYC (focuses on Big Data and AI) and Hardwired NYC(focuses on IOT, AR/VR, drones). At Firstmark, Matt has made investments in the likes of Sketchfab, Sense 360 and the much loved X.ai with Amy Ingram as your personal secretary.
In Today's Episode You Will Learn: 1.) How did Matt make his way into the world of VC?
2.) What does big data really mean? With the cool kids in the data world moving on to obsessing over AI, is big data still a 'thing' in 2016?
3.) Why is now the time for big data? What has enabled big data to have sudden mass utility across a variety of applications?
4.) How does Matt view the integration of big data and AI? Is AI helping big data deliver it's promise?
5.) How can we combat the incumbency advantage of large companies owning the majority of datasets? How can startups access similar datasets?
Items Mentioned In Today's Episode:
Matt's Fave Blog: AVC, Chris Dixon, Brad Feld, Wait But Why
Matt's Most Recent Investment: Hyperscience
As always you can follow The Twenty Minute VC, Harry and Matt on Twitter here! If you would like to see a more colourful side to Harry with many a mojito session, you can follow him on Instagram here! The Twenty Minute VC is brought to you by Leesa, the Warby Parker or TOMS shoes of the mattress industry. Lees have done away with the terrible mattress showroom buying experience by creating a luxury premium foam mattress that is order completely online and ships for free to your doorstep. The 10 inch mattress comes in all sizes and is engineered with 3 unique foam layers for a universal, adaptive feel, including 2 inches of memory foam and 2 inches of a really cool latex foam called Avena, design to keep you cool. All Leesa mattresses are 100% US or UK made and for every 10 mattresses they sell, they donate one to a shelter. Go to Leesa.com/VC and enter the promo code VC75 to get $75 off!
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