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

Something You Should Know
The Real and False Promises of AI & What They Really Ate at the First Thanksgiving

And it should be common sense that we can't really predict the future, or at least not with anything close to perfect accuracy. And yet a lot of companies are telling us to suspend our common sense because AI, right? And that's what we're trying to push back on.

Something You Should Know
The Real and False Promises of AI & What They Really Ate at the First Thanksgiving

And it should be common sense that we can't really predict the future, or at least not with anything close to perfect accuracy. And yet a lot of companies are telling us to suspend our common sense because AI, right? And that's what we're trying to push back on.

Something You Should Know
The Real and False Promises of AI & What They Really Ate at the First Thanksgiving

And it should be common sense that we can't really predict the future, or at least not with anything close to perfect accuracy. And yet a lot of companies are telling us to suspend our common sense because AI, right? And that's what we're trying to push back on.

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

we're not going to have too many more cycles, possibly zero more cycles of a model that's almost an order of magnitude bigger in terms of the number of parameters than what came before and thereby more powerful. And I think a reason for that is data becoming a bottleneck. These models are already trained on essentially all of the data that companies can get their hands on.

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

we're not going to have too many more cycles, possibly zero more cycles of a model that's almost an order of magnitude bigger in terms of the number of parameters than what came before and thereby more powerful. And I think a reason for that is data becoming a bottleneck. These models are already trained on essentially all of the data that companies can get their hands on.

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

we're not going to have too many more cycles, possibly zero more cycles of a model that's almost an order of magnitude bigger in terms of the number of parameters than what came before and thereby more powerful. And I think a reason for that is data becoming a bottleneck. These models are already trained on essentially all of the data that companies can get their hands on.

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 while data is becoming a bottleneck, I think more compute still helps, but maybe not as much as it used to.

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 while data is becoming a bottleneck, I think more compute still helps, but maybe not as much as it used to.

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 while data is becoming a bottleneck, I think more compute still helps, but maybe not as much as it used to.

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'm super excited for this conversation.

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'm super excited for this conversation.

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'm super excited for this conversation.

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

Sure. So, I'm a professor of computer science, and I would say I do three things. One is technical AI research, and another is understanding the societal effects of AI, and the third is advising policymakers.

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

Sure. So, I'm a professor of computer science, and I would say I do three things. One is technical AI research, and another is understanding the societal effects of AI, and the third is advising policymakers.

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

Sure. So, I'm a professor of computer science, and I would say I do three things. One is technical AI research, and another is understanding the societal effects of AI, and the third is advising policymakers.

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 spent years of my time on this. I really believed that decentralization could have tremendous societal impacts. How is this going to make society better? It was not the money angle. But by around 2018, I had started to get really disillusioned. And that was because of a couple of main things.

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 spent years of my time on this. I really believed that decentralization could have tremendous societal impacts. How is this going to make society better? It was not the money angle. But by around 2018, I had started to get really disillusioned. And that was because of a couple of main things.

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 spent years of my time on this. I really believed that decentralization could have tremendous societal impacts. How is this going to make society better? It was not the money angle. But by around 2018, I had started to get really disillusioned. And that was because of a couple of main things.

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

One is, in a lot of cases where I had thought crypto or blockchain was going to be the solution, I realized that that was not the case. While there is potential for crypto to help the world's unbanked, the tech is not the real bottleneck there. And the other part of it was just a philosophical aspect of this community.

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

One is, in a lot of cases where I had thought crypto or blockchain was going to be the solution, I realized that that was not the case. While there is potential for crypto to help the world's unbanked, the tech is not the real bottleneck there. And the other part of it was just a philosophical aspect of this community.