Luis von Ahn

Founder & CEO, Duolingo · 1 appearance on the record.

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

founderexecutivescientistacademicengineer

Luis von Ahn is the co-founder and CEO of Duolingo. He is also known for inventing CAPTCHA and founding reCAPTCHA, and was previously a computer science professor.

8statements → 3claims → 2claims resolved → 3.88/5average certainty → 2.25/5average debate potential → 1said about them ↓

1 supported 1 partly supported 0 contradicted 1 not checkable as stated how the 3 claims stand · each chip opens the sources

3 assertions · 2 opinions · 2 insights · 1 disclosure · every statement was checked. The predictions and assertions are the 3 claims: statements the public record can support or contradict. 2 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 Luis 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

von Ahn: reCAPTCHA digitized 2 to 3 million books annually

“There are a hundred million books that needed to be digitized. That was the total number of books that has ever been written, you know, before the digital era was one hundred million. At the pace that we were going, we were able to digitize about two to three …”

Luis von Ahn Jan 2, 2019 ▶ 15:45 a16z Podcast | The Taxonomy of Collective Knowledge

Expressed certainty vs assessment result

none yet certainty 1

none yet certainty 2

50% certainty 3

100% certainty 4

none yet certainty 5

weighted support: a fully supported claim counts one, a partly supported claim counts half. Each filled bar is clickable and opens exactly those claims; "none yet" means nothing said at that certainty level has resolved yet

What they said8 What others said1 Episodes1

Everything Luis von Ahn said on the a16z Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Insight

Luis von Ahn: Paying crowdsourced workers is ineffective due to spam

“I have found that paying people is not so good. Then you really have to spend a lot of effort trying to stop people who are just there to, you know, get your money.”

Luis von Ahn Jan 2, 2019 ▶ 17:42 a16z Podcast | The Taxonomy of Collective Knowledge

Opinion

Luis von Ahn: Many AI systems are just fancy ontologies

“A lot of the things that are quote unquote called AI or artificial intelligence, a lot of times are just fancy ontologies.”

Luis von Ahn Jan 2, 2019 ▶ 1:08 a16z Podcast | The Taxonomy of Collective Knowledge

Assertion Not checkable as stated

Luis von Ahn: Deep learning requires vast human-entered ground truth data

“The other way in which humans are needed here is to create the ground truth. All of these deep learning or deep AI algorithms need A ton of ground truth in order to get very accurate. It has to be entered by humans.”

Luis von Ahn Jan 2, 2019 ▶ 4:54 a16z Podcast | The Taxonomy of Collective Knowledge

Assertion Partly supported

von Ahn: In 2017, humans still beat AI at basic image recognition

“Computers are better at playing Go than humans are, but humans are still better at recognizing whether a picture has a cat or not.”

Luis von Ahn Jan 2, 2019 ▶ 22:27 a16z Podcast | The Taxonomy of Collective Knowledge

Opinion

Luis von Ahn: Most of the legal system is extremely inconsistent

“Most of our legal system is extremely inconsistent.”

Luis von Ahn Jan 2, 2019 ▶ 13:02 a16z Podcast | The Taxonomy of Collective Knowledge

Assertion Supported

von Ahn: reCAPTCHA digitized 2 to 3 million books annually

Luis von Ahn Jan 2, 2019 ▶ 15:45 a16z Podcast | The Taxonomy of Collective Knowledge

Disclosure

reCAPTCHA required 10 matching user responses to establish ground truth text

“And the way we got the ground truth here is, is simply by having, you know, 10 different people agree with each other. So if you gave the same word to 10 different people and they all agreed that we consider that ground truth that to a very large extent that w…”

Luis von Ahn Jan 2, 2019 ▶ 6:48 a16z Podcast | The Taxonomy of Collective Knowledge

Insight

von Ahn: Profiling crowdsourced contributor accuracy enables precision with only 3-4 human checks

“When you're doing things that are very large scale and you don't have very many humans, you may have a thousand humans or 10,000 humans. And if you need to label millions of things. You can't afford to start giving, you know, the same thing to all 10,000 human…”

Luis von Ahn Jan 2, 2019 ▶ 15:08 a16z Podcast | The Taxonomy of Collective Knowledge

The other half of the tape: Luis von Ahn's own voice is left out of every number here. 1 statement on the record names them. every mention, with the transcript →

Statements about Luis von Ahn, by other people (1)

Assertion Not checkable as stated

Komarneni: Duolingo inspired HumanDX's gamified clinical case interface

“Louise had actually his work on Duolingo and really kind of this idea of creating these micro interactions that almost have this gamified structure was really a major inspiration also for the way that we built HumanDX to be these brief interactions where you c…”

Jay Komarneni Jan 2, 2019 ▶ 20:05 a16z Podcast | The Taxonomy of Collective Knowledge

Appearances (1)