Dave Burgess

Head of Data Engineering, Pinterest · 1 appearance on the record.

computed by AI from the episodes · how this works → · full disclaimer →

14statements → 9claims → 2claims resolved → 4.21/5average certainty → 1.43/5average debate potential → 4.4/5argument clarity · the sources →

1 supported 0 partly supported 1 contradicted 7 not checkable as stated how the 9 claims stand · each chip opens the sources

9 assertions · 1 opinion · 4 disclosures · every statement was checked. The predictions and assertions are the 9 claims: statements the public record can support or contradict. 2 are resolved, and 7 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Dave argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported

Yahoo used ML and behavioral targeting in ads over 15 years ago

“We were doing machine learning and behavioral targeting back 15 years ago, more than 15 years ago in advertising.”

Dave Burgess Apr 5, 2021 ▶ 2:46 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Their most notable contradicted claim

Assertion Contradicted

Apache Kafka was built on prior engineering work at Yahoo

“Things like Kafka eventually came out of LinkedIn that was based on work that we had been doing at Yahoo”

Dave Burgess Apr 5, 2021 ▶ 2:38 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Argument clarity: do they answer the question? how? →

4.4 / 5 directness 4.7 · coherence 4.7 · precision 4.5 · compression 3.9

answered every one of 11 assessed questions directly

This is a score against a rubric. It is not a rank. Every host question → answer exchange is scored with names hidden on directness, coherence, precision and compression, 1–5 each, on meaning alone: disfluencies are ignored, and only raw unedited episodes count. This is the score that measures thought. Every scored exchange, scores shown → · The rubric and its checks →

How they sound: speaking style how? →

241 words/min while actually speaking · 41.2 um and uh per 1k words

Measured by listening to the audio itself: 4,222 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

What they said14 Episodes1

Everything Dave Burgess said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Opinion

Pinterest visual search beats Google and Bing in head-to-head tests

“You'll find that Pinterest is usually the one that comes out of top.”

Dave Burgess Apr 5, 2021 ▶ 13:06 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Assertion Contradicted

Apache Kafka was built on prior engineering work at Yahoo

“Things like Kafka eventually came out of LinkedIn that was based on work that we had been doing at Yahoo”

Dave Burgess Apr 5, 2021 ▶ 2:38 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Assertion Not checkable as stated

Pinterest stores more than 400 petabytes of data

“We have more than 400 petabytes of data.”

Dave Burgess Apr 5, 2021 ▶ 8:59 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Disclosure

Pinterest manages open-source data tech in-house to limit downtime

“Yeah, we do. I mean, we're fortunate to have the number of engineers to do that, and one of the reasons why we work directly either with the open source community or the companies that are also working on that is that we want Pinterest to be up all the time, a…”

Dave Burgess Apr 5, 2021 ▶ 20:29 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Disclosure

Pinterest embeds machine learning engineers directly within product teams

“With machine learning is actually distributed everywhere. We have Many, many machine learning engineers and many, many use cases. And those mission machine learning engineers are embedded within each organization.”

Dave Burgess Apr 5, 2021 ▶ 22:50 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Disclosure

Pinterest wants non-coding data scientists to deploy ML models to production

“And to get to a point where we can have people that are data scientists that don't even code, that can just build models and be able to deploy those to production. So that's really what we want to get to within Pinterest as well.”

Dave Burgess Apr 5, 2021 ▶ 24:22 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Assertion Supported

Yahoo used ML and behavioral targeting in ads over 15 years ago

“We were doing machine learning and behavioral targeting back 15 years ago, more than 15 years ago in advertising.”

Dave Burgess Apr 5, 2021 ▶ 2:46 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Assertion Not checkable as stated

Pinterest runs about 1,000 parallel A/B experiments at any time

“And so we have about a thousand experiments running in parallel at any point of time.”

Dave Burgess Apr 5, 2021 ▶ 12:15 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Assertion Not checkable as stated

Pinterest deploys machine learning across roughly 80 distinct use cases

“So we have about 80 different use cases of machine learning.”

Dave Burgess Apr 5, 2021 ▶ 12:26 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Assertion Not checkable as stated

Pinterest platform deploys ML models across thousands of servers within hours

“So we, what we can do is within a few hours, you could do create a model, train a model, and then deploy it to our production service with thousands and thousands of servers by using this MLflow repository.”

Dave Burgess Apr 5, 2021 ▶ 16:30 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Assertion Not checkable as stated

Pinterest uses 50 machine learning models in its pin safety pipeline

“And so, there's a, that whole pipeline has got like about 50 different machine learning models in itself.”

Dave Burgess Apr 5, 2021 ▶ 19:01 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Assertion Not checkable as stated

Pinterest reduced maintenance costs, latency, and infrastructure expenses by migrating to Druid

“And so we decided to migrate that to Druid. And so the maintenance cost has gone way down. The latency has gone way down. The actual cost of running the infrastructure way down. So really, really happy.”

Dave Burgess Apr 5, 2021 ▶ 27:25 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Assertion Not checkable as stated

Pinterest operates over 2,000 production workflows on Apache Airflow

“We're still using the APIs for the existing system so that we could migrate, but we have over 2000 workflows running in production.”

Dave Burgess Apr 5, 2021 ▶ 29:30 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Disclosure

Burgess outlines Pinterest's online serving and batch data engineering stack

“So data engineering at Pinterest comprises the serving part, all the online systems. So that includes the online databases like MySQL and key value stores like RocksDB and HBase, and also includes Druid platform. So we have our online systems. We also have all…”

Dave Burgess Apr 5, 2021 ▶ 22:07 Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner, FirstMark)

Appearances (1)

Episode	Date	Speaking time
Fireside Chat: Dave Burgess (Head of Data Engineering, Pinterest) w/ Matt Turck (Partner,	Apr 5, 2021	22m

Dave Burgess

The record, in short

Their most notable supported claim

Their most notable contradicted claim

Argument clarity: do they answer the question? how? →

How they sound: speaking style how? →

Appearances (1)

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