Computing Power

topic on 4 shows · 5 statements across 5 episodes

the Startup Ideas Podcast Capital Allocators the a16z Podcast 20VC

5 statements about Computing Power, every show

STARTUP IDEAS Assertion Partly supported
Ball: Persistent Metaverse Requires a 1,000x Increase in Computing Power
“In strict technical terms, the general consensus advocated by folks at Intel and Meta is a thousand factor increase in computing power. We are up about a hundred since 2000. So we need a thousand on top of that.”
Matthew Ball Jul 14, 2022 ▶ 32:45 The Metaverse & How It Will Change the World with Matthew Ball
20VC Opinion
Howard Marks: Tech automation threatens long-term employment for manual laborers
“Longer term, I worry about employment, mainly because of the stuff Bill does. You know, his companies are replacing labor with computing power, to over-exaggerate. I worry about where people whose main asset is a strong back are going to get jobs in the longer…”
Howard Marks Jan 4, 2021 ▶ 13:55 20VC: Bill Gurley and Howard Marks: What Happened In 2020? What Can We Expect Looking Forward to 2021?
Fontana: The 2013 Convergence That Sparked the Neural Network Revolution
“That was a really interesting time, 2013, 14, because that's when this neural network revolution started, and that is, we were finally at the point where we'd had some research breakthroughs into how neural networks work. We had enough data to feed these, like…”
Ash Fontana Oct 28, 2019 ▶ 18:56 Ash Fontana – Investing in Artificial Intelligence at Zetta Ventures (First Meeting, EP.11)
a16z Insight
Turetsky: Advanced computing power compensates for physical hardware defects in robotics
“Computing power will make up for a lot of hardware defects. So if you have a underpowered Unreliable manipulator, but lots of good computing power. You can make that manipulator do amazing things, right?”
Dave Turetsky Jan 2, 2019 ▶ 32:28 a16z Podcast | The IQ and EQ of Robots
a16z Insight
Boneh: Faster computers help cryptographic defenders more than they help attackers
“And the reason is because as computers get faster we can you know, end, end user machines can actually handle larger and larger numbers. But if you just make the number, like, twice as big, Factoring it is not twice as hard. Factoring it becomes exponentially …”
Dan Boneh Jan 2, 2019 ▶ 29:24 a16z Podcast | Crypto, Security, CS, Quantum Computing, and More with Our New Professor-in-Residence

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