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Prasad Akella

Operating Partner, ReX Capital · 1 appearance on the record.

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founderexecutiveengineerinvestorakellas.org ↗

Prasad Akella is an Operating Partner at ReX Capital and a deep tech advisor. He previously pioneered collaborative robots at General Motors and founded the AI manufacturing platform Drishti.

8statements → 5claims → 2claims resolved → 3.75/5average certainty → 2/5average debate potential →

0 supported 1 partly supported 1 contradicted 1 not yet assessed 2 not checkable as stated how the 5 claims stand · each chip opens the sources

2 predictions · 3 assertions · 3 insights · every statement was checked. The predictions and assertions are the 5 claims: statements the public record can support or contradict. 2 are resolved, 1 is not yet assessed, and 2 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 Prasad argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable contradicted claim

Assertion Contradicted
Akella: The Ford F-150 truck has one trillion possible build combinations
“So if you take the most popular truck in America, it's the F one 50, the Ford F one 50. It turns out there are a trillion build combinations of that vehicle. Right? So, you have different engines, you have different seats, you have different radios, you know, …”
Prasad Akella Jan 2, 2019 ▶ 6:35 a16z Podcast | Automation + Work, Human + Machine

How they sound: speaking style how? →

263 words/min while actually speaking · 2.2 um and uh per 1k words

No argument clarity score for Prasad Akella: no usable question→answer exchanges 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 2,243 words across 1 episode, but every recording we have of Prasad Akella is the aired feed, and an editor cleaned that audio before release. Some of the hesitation was cut before we ever heard it, so read these as floors: the true rates are at least this high. These are measurements of speaking style, not scores. How it's measured →

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

Prediction Open · timeframe Nov 2068
Akella: Total factory job replacement by robots is multiple lifetimes away
“So if you do this math and you take the three forty million, roughly divided by six jobs per, you're looking at sixty million robots before you can wipe out all of mankind in any production facility. It ain't gonna happen in my lifetime. I don't see it happeni…”
Prasad Akella Jan 2, 2019 ▶ 14:01 a16z Podcast | Automation + Work, Human + Machine
Insight
Akella: Hiding AI features from users drives greater product adoption
“And by actually hiding AI, you actually drive greater usage. And I would argue that good AI company does is to hide it.”
Prasad Akella Jan 2, 2019 ▶ 18:58 a16z Podcast | Automation + Work, Human + Machine
Assertion Partly supported
Akella: General Motors team created the collaborative robot category
“We created an entire category called collaborative robots.”
Prasad Akella Jan 2, 2019 ▶ 1:43 a16z Podcast | Automation + Work, Human + Machine
Insight
Akella: Data-driven programming is the biggest technology shift in 25 years
“It's really data that's driving programming now. It's not logic. And that I think is the single biggest change that I've seen happen over the last 25 years.”
Prasad Akella Jan 2, 2019 ▶ 4:57 a16z Podcast | Automation + Work, Human + Machine
Prediction Not checkable as stated
Akella: Human workers will remain essential in factories for the long haul
“I really think that's where people and machines on the floor continue, and I think people are here for the long haul.”
Prasad Akella Jan 2, 2019 ▶ 7:46 a16z Podcast | Automation + Work, Human + Machine
Insight
Akella: Model generalization is the primary bottleneck to scaling AI
“I think the central challenge in front of us is how do you actually get these models to generalize across broader swaths of industry? So when we solve a problem today, we look at it in a much narrower context, we solve it, and we look for how much of that can …”
Prasad Akella Jan 2, 2019 ▶ 21:23 a16z Podcast | Automation + Work, Human + Machine
Assertion Contradicted
Akella: The Ford F-150 truck has one trillion possible build combinations
“So if you take the most popular truck in America, it's the F one 50, the Ford F one 50. It turns out there are a trillion build combinations of that vehicle. Right? So, you have different engines, you have different seats, you have different radios, you know, …”
Prasad Akella Jan 2, 2019 ▶ 6:35 a16z Podcast | Automation + Work, Human + Machine
Assertion Not checkable as stated
Akella: Industrial engineers spend 30 percent of their time collecting data
“The bulk of the population just spends, according to our customers, 30% of their time just getting data.”
Prasad Akella Jan 2, 2019 ▶ 11:36 a16z Podcast | Automation + Work, Human + Machine

Appearances (1)

EpisodeDateSpeaking time
a16z Podcast | Automation + Work, Human + Machine Jan 2, 2019 10m
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