Daniel Svonava

Superlinked

superlinked.com makes it easier to turn data into vector embeddings

Co-Founder & CEO

creable.io

creable.com is the world's biggest influencer database (300M creators)

Advisory Board Member

Tater Games

tatergames.com is a data-driven game studio

Board Member

Primeflow

primeflow.com built tools for super-connectors and their network-driven business

Founder & CTO

Google

2016 - 2018
Tech-lead for YouTube Reservation Ads forecasting (Can a reservation be booked or not?) and pricing (How much should we charge for it?).

2015
Tech-lead for YouTube Video Ads traffic prediction and cross-Google Ads reach prediction, enabling ad buying in Adwords and DBM.
Focus on making Google Ads useful for Brand advertisers.

2013 - 2014
Within YouTube monetization I'm constantly switching between being an analyst who organizes and makes sense of data, builds prototype visualizations and spreads around the insights to help decision making and product design and being an engineer who uses these insights to build useful production systems.

Senior Software Engineer

47pixels

We were a software startup in the Story-telling space. Major products:
47posters - B2B SaaS for Print Service Providers launched in 7 countries
memoarc - B2C storytelling photogallery
dofsome - B2C minimalistic, high-quality photo hosting.
Reach out to me for a complete portfolio.

Co-Founder

Exploratory large-scale information mining from unstructured data. Patent granted.

Software Engineering Intern

IBM Research

Joined the Information analytics group within the Mathematics and Computer Science department again to continue my work on matrix reordering and co-clustering remotely via IBM SK.

Research Internship

Joined the Information analytics group within the Mathematics and Computer Science department. Co-authored a research paper involving graph theory, clustering and visualization. Worked on a web-based marketing intelligence tool employing data-mining techniques and back-end infrastructure optimization.

"Great Minds" Research Internship

Slovak University of Technology

The course is called Development of effective algorithms and programs. I prepared problem statements and solutions for assignments and competitions. I also set problems for ProFIIT, national programming competition for High school students.

Teaching assistant

Vector Compute @ Superlinked | xYouTube

➡️ Building a compute framework for turning data into vector embeddings.
🤗 Connect your data infrastructure to your vector database with Superlinked.

Join our product preview:
📋 Try it out in a Python notebook with no dependencies.
↗️ Design the perfect vectors for your retrieval use-case.
🔧 Mix and match streaming, batch, structured and unstructured data.
🚀 Launch to production with your favorite Vector Database.

➡️ Let's sort out information retrieval across your organization!
.
.
.
.
Previous:

Daniel is a Senior Software Engineer at Google, where he tech-leads, designs and builds forecasting & pricing systems for ads worth billions of dollars. These are distributed systems that run on thousands of machines, process terabytes of data per query and combine Machine Learning modeling with game-like simulation of tens of thousands ad campaigns - all happening in real-time to enable thousands of concurrent users of buying tools like AdWords and DBM.

Daniel wields a rare combination of deep technical skills, a user-centric drive and an ability to align multiple teams towards a common goal - launching and landing high quality cutting edge products.

Daniel co-founded a tech startup that brought machine vision to the consumer photo space 10 years ago, he was an invited speaker at an ML dev conference in Zurich and speaks at startup events regularly. He holds multiple patents with Google, is published in a peer-reviewed ML journal from his time at IBM Research and is a Google Code Jam on-site finalist.

On weekends he flies, climbs, skis and bikes in the Alps, see: http://instagram.com/mountain.supo

Tomasz Tunguz

Theory Ventures

Student of startups, author of tomtunguz.com, investor, & partner to founders.

General Partner

Redpoint Ventures

Privileged to support the journey of early stage SaaS, data and infrastructure founders. Worked with Looker ($2.6b M&A), MotherDuck, Mysten Labs (SUI), Monte Carlo, Omni, Chorus ($575m to ZI), Expensify (IPO), ThredUp (IPO), Kustomer ($1b sale to META), & others.

Managing Director

Winning with Data

I co-authored Winning with Data with Looker CEO Frank Bien.  Winning with Data: Transform Your Culture, Empower Your People, and Shape the Future explores  the cultural changes big data brings to business, and shows you how to adapt your organization to leverage data to maximum effect.

Co-Author

Google, Inc.

Managing AdSense for Social Networks including the $900M MySpace deal.
Managed AdSense International including product launches in Greece, Israel, Thailand, Indonesia and Bulgaria

Product Manager

Appian Corporation

Architected, developed and deployed systems for the US Government serving DHS

Engineer

Student of Startups
Backer of 9 unicorns
Author of http://tomtunguz.com 
Subscribe https://ttunguz.kit.com/ef0a779b9c

Founder

Private equity firms have emerged as the newest distribution channel for AI startups.

While public companies have decreased from 6,639 in 2000 to 3,550 in 2024, PE-owned companies in the US have grown from 1,950 to 14,300. The rate of growth continues to accelerate.

The crossover happened in 2009, when PE inventory overtook public company counts for the first time. By 2024, PE-backed companies outnumber public firms by roughly 4:1.

The shift is driven by the massive expansion of PE ownership across corporate America.

That’s not to say the sizes of PE-owned companies are the same as publics. In fact, they are smaller.

The point isn’t that startups previously focused on public companies. Rather, the data reveals the immense scale of private equity portfolios.

(second image)

Data Sources : CRSP, Wilshire 5000, PitchBook, American Investment Council, Citizens Bank.

The mid-market profile of these PE-owned companies suits AI startups’ desires for faster sales cycles.

Plus, the profit motive of private equity aligns perfectly with AI startups’ capacity to cut costs & drive efficiency. PE firms acquire companies to improve margins & operational performance before exit.

AI tools that reduce headcount, automate processes, or accelerate workflows deliver exactly what PE operating partners need.

A private equity firm owning 25 companies proves value in one or two before rolling out to the entire portfolio. Control enables rapid deployment. This creates an efficient channel for AI startups to demonstrate value & cross-sell.

PE firms gain operational leverage while AI startups access more than 14,000 motivated buyers. This new go-to-market motion redefines how AI software reaches the market, bypassing the traditional enterprise sales grind in favor of networks that can deploy at scale.

taplio

The Battle

Daniel Svonava

Tomasz Tunguz

Followers

Posts

Engagements

Likes

Performance ScoreTomasz Tunguz's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Daniel Svonava

Tomasz Tunguz

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Tomasz Tunguz's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreTomasz Tunguz's LinkedIn Performance