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Bradford Cross

Founder & CEO, Alpha City · 1 appearance on the record.

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

founderinvestorexecutiveauthor@bradfordcross ↗LinkedIn ↗bradfordcross.substack.com ↗

Cross is an artificial intelligence technologist and investor who co-founded venture capital firm Data Collective (DCVC) and founded startups including FlightCaster, Prismatic, and HealthMode. He previously served as founder and CEO of anti-money laundering platform Merlon Intelligence and now focuses on charter cities and governance innovation.

11statements → 7claims → 1claims resolved → 3.64/5average certainty → 2.82/5average debate potential → 1said about them ↓

0 supported 1 partly supported 0 contradicted 6 not checkable as stated how the 7 claims stand · each chip opens the sources

5 predictions · 2 assertions · 1 opinion · 3 insights · every statement was checked. The predictions and assertions are the 7 claims: statements the public record can support or contradict. 1 is resolved, and 6 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 Bradford argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

How they sound: speaking style how? →

229 words/min while actually speaking · 22.3 um and uh per 1k words

No argument clarity score for Bradford Cross: only 1 usable question→answer exchange on raw tape (a fair score needs 8+). We do not score a sample that small. Roundtable and news formats yield far fewer direct exchanges than interviews.

Measured by listening to the audio itself: 5,549 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 →

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

Prediction Not checkable as stated
Investors funding AI startups without scientific competency will lose money
“So I think as, insofar as that continues to happen, Those people are gonna lose a lot of money.”
Bradford Cross Sep 28, 2017 ▶ 15:01 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Prediction Not checkable as stated
Big tech companies will lose massive amounts of money on ML APIs
“I do not think that these numbers are going to be good for these machine learning APIs. And I think those bigger companies are going to lose a massive amount of money over the next several years.”
Bradford Cross Sep 28, 2017 ▶ 17:44 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Prediction Not checkable as stated
Silicon Valley will see few consumer tech wins before a major correction
“I don't expect to see very many consumer success stories coming from Silicon Valley right now, until we have a major correction.”
Bradford Cross Sep 28, 2017 ▶ 8:27 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Prediction Not checkable as stated
Most companies cannot adopt machine learning due to limited talent pools
“I think actually most companies will not be able to use, ah, machine learning. Even though deep learning may be commodity within the machine learning community is still way too small to be commodity overall.”
Bradford Cross Sep 28, 2017 ▶ 12:35 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Assertion Not checkable as stated
Top machine learning talent is heavily concentrated at Google and Facebook
“Almost all of the really smart machine learning people are in less than 10 companies in the world. They're actually in less than five, right? In fact, they're mostly all at Google and Facebook.”
Bradford Cross Sep 28, 2017 ▶ 19:21 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Opinion
Twitter's Magic Pony acquisition marked the peak of AI talent premiums
“But I think that's, you know, that was the sort of tailing off of the, for me, the Twitter Magic Pony deal was kind of the, ah, the tail end of this absurd, extraordinary premium on, on deep learning, and then now, more and more, it's becoming just part of the…”
Bradford Cross Sep 28, 2017 ▶ 11:32 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Insight
Capable engineering teams prefer open-source tools over buying machine learning APIs
“If a team knows what they're doing, then they tend to use open source and cobble it together themselves.”
Bradford Cross Sep 28, 2017 ▶ 16:16 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Insight
Startups building low-level tagging APIs lack defensibility and ability to scale
“If you're doing a low-level tagging API, I really, really worry about your defensibility and the ability to scale that business.”
Bradford Cross Sep 28, 2017 ▶ 18:36 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Insight
AI startups targeting traditional industries must build full-stack applications for adoption
“So you've got to kind of come all the way up to spoon feeding them the solution, or else I worry a lot about getting adoption for machine learning applications.”
Bradford Cross Sep 28, 2017 ▶ 23:57 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Assertion Partly supported
JPMorgan Chase and Citi each spend $2B to $4B annually on compliance
“The big ones, like JPMorgan Chase, Citi, et cetera, have 10,000 plus analysts working on this every year. They're spending two to four billion dollars a year on compliance.”
Bradford Cross Sep 28, 2017 ▶ 3:10 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)
Prediction Not checkable as stated
Standalone chatbots will eventually be absorbed into broader software platforms
“What'll happen is they end up getting folded into systems that really meet the more basic human needs.”
Bradford Cross Sep 28, 2017 ▶ 9:08 AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Data Driven)

The other half of the tape: Bradford Cross's own voice is left out of every number here. Other people bring the name up 1 time in 1 episode on the MAD Podcast. every mention, with the transcript →

Who brings them up most Matt Turck 1

Every mention by year

tap a year for its mentions
0011112017episodesmentions
0112017episodes it came up in
000.50.5112017episodesmentions per episode
2017 1 mention in 1 episode

Appearances (1)

EpisodeDateSpeaking time
AI Startup Predictions // Bradford Cross - A fireside chat with Matt Turck (FirstMark's Da Sep 28, 2017 28m
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