Carly Taylor

Field CTO for Gaming, Databricks · 1 appearance on the record.

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

engineerscientistfounderexecutiveLinkedIn ↗rebeldatascience.com ↗

Carly Taylor is the Field CTO for Gaming at Databricks and the founder of Rebel Data Science. She previously engineered machine learning and security models for Activision's Call of Duty franchise.

10statements → 1claims → 0claims resolved → 3.5/5average certainty → 2.4/5average debate potential → 4.2/5argument clarity · the sources →

1 not checkable as stated how the 1 claim stands · each chip opens the sources

1 assertion · 2 opinions · 7 insights · every statement was checked. The predictions and assertion are the 1 claim: statements the public record can support or contradict. 0 are resolved, and 1 names 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 Carly argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

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

4.2 / 5 directness 4.2 · coherence 4.6 · precision 3.9 · compression 3.9

redirected or did not address 3 of 12 assessed questions (25%). Watch them ▸

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? →

238 words/min while actually speaking · 15.2 um and uh per 1k words

Measured by listening to the audio itself: 5,323 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 said10 Episodes1

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

Insight

Taylor: Community building provides more startup growth leverage than marginal technical improvements

“Sometimes you can over index on the technical and getting maybe, you know, your platform to be five percent more fast or supported on one more browser might not 10 X you the way that spending that time building a community would.”

Carly Taylor Sep 14, 2023 ▶ 21:59 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Opinion

Taylor: Data science and AI startups should prioritize LinkedIn over Twitter

“Twitter might get you more impressions, I think. And you might get your message out wider. So I don't think it has to be an either or, but if I was going to spend a lot of my time, especially if I was a data science or AI startup, I would learn where my audien…”

Carly Taylor Sep 14, 2023 ▶ 28:22 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Insight

Taylor: Model observability is the most important focus for data scientists

“I harp on observability a lot because I think it's, like, probably the most important thing a data scientist can focus on”

Carly Taylor Sep 14, 2023 ▶ 31:04 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Opinion

Taylor: Healthcare lags eight years in tech, creating massive upside for ML

“I think that health care is historically like eight years behind everyone else, but there's also a very massive upside there right now for people who are going to be using machine learning and data science to solve problems.”

Carly Taylor Sep 14, 2023 ▶ 36:49 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Insight

Taylor: Security machine learning must hyper-focus on outliers instead of discarding them

“There's a tenant of machine learning where like you just throw out the outliers because they're going to mess up your distribution and you kind of don't want to deal with them. For security, what you do is you find the outliers and you hyper focus on them beca…”

Carly Taylor Sep 14, 2023 ▶ 7:49 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Insight

Taylor: Deploying machine learning models fundamentally alters the targeted adversarial problems

“And it's something that I think traditional machine learning hasn't really been agile enough to deal with. Right. Like the act of doing machine learning is fundamentally changing the problem you're trying to solve.”

Carly Taylor Sep 14, 2023 ▶ 9:37 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Insight

Taylor: GenAI in games introduces new capabilities rather than replacing human jobs

“It's no one's Full-time job to make an NPC, like say your name. It's just a functionality we've never had. So you're not really replacing anything people were doing. You're just making something that didn't exist exist.”

Carly Taylor Sep 14, 2023 ▶ 11:43 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Insight

Carly Taylor: Centralized data teams lose domain depth, embedded teams lose standards

“As soon as you centralize something, you will inevitably lose the deep expertise you can get from embedding, but as soon as you embed everyone, you lose that, like, you know, Center of excellence where everyone comes together and you set standards for your dat…”

Carly Taylor Sep 14, 2023 ▶ 15:53 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Assertion Not checkable as stated

Carly Taylor: Gaming data teams have better diversity than core programming roles

“I see more representation in, in data teams than I do for something, let's say like the, I don't know, hardware level programming. You know, which has just historically been, like, a lot of these, like, deep nitty-gritty computer science fields have been, like…”

Carly Taylor Sep 14, 2023 ▶ 17:38 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Insight

Taylor: Startups without ready data must prioritize hiring a cloud data engineer

“If you don't have your data ready yet, you can't skip the data engineering piece of this, and I'd say you probably need someone who's going to be like your cloud data engineer. Like you just have to have those basics covered”

Carly Taylor Sep 14, 2023 ▶ 34:09 From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI

Appearances (1)

Episode	Date	Speaking time
From Xbox to Databricks: Carly Taylor’s Rebel Path in Data Science & Gaming AI	Sep 14, 2023	25m

Carly Taylor

The record, in short

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

How they sound: speaking style how? →

Appearances (1)

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