Menu
Sign In Search Podcasts Libraries Charts People & Topics Add Podcast API Blog Pricing

Arvind Narayanan

๐Ÿ‘ค Speaker
607 total appearances

Appearances Over Time

Podcast Appearances

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

But I'm very skeptical that these new kinds of learning are going to get to a point anytime soon where they're going to become the default way in which people learn.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

But I'm very skeptical that these new kinds of learning are going to get to a point anytime soon where they're going to become the default way in which people learn.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

But I'm very skeptical that these new kinds of learning are going to get to a point anytime soon where they're going to become the default way in which people learn.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

I think for now, they are very much overblown. My favorite example of the thing you said of technology creating jobs is bank tellers. When ATMs became a thing, it would have been reasonable to assume that bank tellers were just going to go away. But in fact, the number of tellers increased. And the reason for that is that it became much cheaper for banks to open regional branches.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

I think for now, they are very much overblown. My favorite example of the thing you said of technology creating jobs is bank tellers. When ATMs became a thing, it would have been reasonable to assume that bank tellers were just going to go away. But in fact, the number of tellers increased. And the reason for that is that it became much cheaper for banks to open regional branches.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

I think for now, they are very much overblown. My favorite example of the thing you said of technology creating jobs is bank tellers. When ATMs became a thing, it would have been reasonable to assume that bank tellers were just going to go away. But in fact, the number of tellers increased. And the reason for that is that it became much cheaper for banks to open regional branches.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

And once they did open those regional branches, they did need humans for some of the things that you couldn't do with an ATM. And, you know, the more abstract way of saying that is, as economists would put it, jobs are bundles of tasks, and AI automates tasks, not jobs.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

And once they did open those regional branches, they did need humans for some of the things that you couldn't do with an ATM. And, you know, the more abstract way of saying that is, as economists would put it, jobs are bundles of tasks, and AI automates tasks, not jobs.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

And once they did open those regional branches, they did need humans for some of the things that you couldn't do with an ATM. And, you know, the more abstract way of saying that is, as economists would put it, jobs are bundles of tasks, and AI automates tasks, not jobs.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

So if there are, you know, 20 different tasks that comprise a job, the odds that AI is going to be able to automate all 20 of them are pretty low. And so there are some occupations certainly that have already been affected a lot by AI like translation or stock photography. But for most jobs out there, I don't think we're anywhere close to that.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

So if there are, you know, 20 different tasks that comprise a job, the odds that AI is going to be able to automate all 20 of them are pretty low. And so there are some occupations certainly that have already been affected a lot by AI like translation or stock photography. But for most jobs out there, I don't think we're anywhere close to that.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

So if there are, you know, 20 different tasks that comprise a job, the odds that AI is going to be able to automate all 20 of them are pretty low. And so there are some occupations certainly that have already been affected a lot by AI like translation or stock photography. But for most jobs out there, I don't think we're anywhere close to that.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

So I think it's a good question to ask. I think it's a bit of a category error there. I mean, a nuclear weapon is an actual weapon. AI is not a weapon. AI is something that, you know, might enable adversaries to do certain things more effectively. For example, find vulnerabilities, cybersecurity vulnerabilities in critical infrastructure, right?

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

So I think it's a good question to ask. I think it's a bit of a category error there. I mean, a nuclear weapon is an actual weapon. AI is not a weapon. AI is something that, you know, might enable adversaries to do certain things more effectively. For example, find vulnerabilities, cybersecurity vulnerabilities in critical infrastructure, right?

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

So I think it's a good question to ask. I think it's a bit of a category error there. I mean, a nuclear weapon is an actual weapon. AI is not a weapon. AI is something that, you know, might enable adversaries to do certain things more effectively. For example, find vulnerabilities, cybersecurity vulnerabilities in critical infrastructure, right?

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

So that's one way in which AI could be used on the quote unquote battlefield. So that being the case, I think it would be a big mistake to view it analogously to a weapon and to argue that it should be closed up for a couple of reasons. First of all, it's not going to work at all. So I think we have close to state of the art AI models that can already run on people's personal devices.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

So that's one way in which AI could be used on the quote unquote battlefield. So that being the case, I think it would be a big mistake to view it analogously to a weapon and to argue that it should be closed up for a couple of reasons. First of all, it's not going to work at all. So I think we have close to state of the art AI models that can already run on people's personal devices.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

So that's one way in which AI could be used on the quote unquote battlefield. So that being the case, I think it would be a big mistake to view it analogously to a weapon and to argue that it should be closed up for a couple of reasons. First of all, it's not going to work at all. So I think we have close to state of the art AI models that can already run on people's personal devices.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

And I think that trend is only going to accelerate. We talked earlier about Moore's law, and it still continues to apply to these models. And even if one country decides that models should be closed, the odds of getting every country to enact that kind of rule are just vanishingly small.

The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton

And I think that trend is only going to accelerate. We talked earlier about Moore's law, and it still continues to apply to these models. And even if one country decides that models should be closed, the odds of getting every country to enact that kind of rule are just vanishingly small.