TikTok's Last Stand + Google's Quantum Breakthrough + Cult of Claude

Summary

Hard Fork Podcast Summary: "TikTok's Last Stand + Google's Quantum Breakthrough + Cult of Claude"
Release Date: December 13, 2024
Hosted by Kevin Roose and Casey Newton, The New York Times

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1. Introduction to the Episode

In this episode of Hard Fork, hosts Kevin Roose and Casey Newton delve into three significant tech stories shaping our current landscape:

• TikTok’s Legal Struggle: The looming threat of a forced sale or ban under the Protecting Americans from Foreign Adversary Controlled Applications Act (PFACA).
• Google’s Quantum Computing Milestone: Introduction of the Willow chip and its implications for the future of quantum technology.
• The Cult of Claude: Exploring the growing fervent following around Anthropic’s chatbot, Claude, and its impact on users.

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2. TikTok’s Legal Battle and Potential Ban

Timestamp: 02:24 - 19:43

Overview

TikTok faces a critical juncture as a three-judge panel from the D.C. Circuit Court of Appeals rejects its argument against PFACA, a bipartisan law mandating the sale or divestiture of TikTok by its parent company, ByteDance. The deadline for compliance is swiftly approaching on January 19th, 2025.

Key Points & Discussions

• PFACA’s Implications:
  Julian Kelly (Google’s Julian):
  "[04:28] Julian Kelly: So, Kasey, where do you stand on the question of whether TikTok is likely to exist in its current form in the new year?"

  Casey Newton explains that ByteDance must navigate a significant financial decision, potentially seeking partners willing to invest billions for a stake in TikTok to comply with PFACA.

• Legal Arguments Explored:
  Casey details the court's reasoning, emphasizing national security concerns over First Amendment arguments.
  [05:31]
  Julian Kelly:
  "[05:31] Casey Newton: The court agreed with the government that the national security risks outweigh TikTok's First Amendment claims to free speech."

• Potential Presidential Intervention:
  Discussions touch upon former President Trump’s ambiguous stance during his campaign and the likelihood of executive actions influencing TikTok’s fate.
  [12:18]
  Julian Kelly:
  "If Trump decides to intervene, it could delay or alter the forced sale, but substantial legal hurdles remain."

• Broader Implications for Social Media Regulation:
  The episode raises concerns about the slippery slope of using national security as a pretext to regulate or ban social media platforms, potentially jeopardizing free speech rights.

Notable Quotes

• Casey Newton (04:04):
  "We find it increasingly unlikely that TikTok will continue to exist in its current form without a significant sale."

• Casey Newton (07:22):
  "Everything in the national security and data privacy argument trumps everything in the First Amendment argument."

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3. Google’s Quantum Computing Breakthrough

Timestamp: 21:40 - 45:00

Overview

Google announces the Willow chip, a groundbreaking advancement in quantum computing. This new chip addresses long-standing challenges in quantum error correction, potentially paving the way for scalable and practical quantum computers.

Key Points & Discussions

• Technical Achievements:
  Julian Kelly interviews Julian Kelly from Google Quantum AI, who explains that Willow can exponentially reduce errors as more qubits are added—a critical step toward reliable quantum computing.
  [31:20]
  Julian Kelly:
  "Willow can reduce errors exponentially as we scale up using more qubits."

• Quantum Error Correction:
  The Willow chip surpasses the quantum error correction threshold, a theoretical benchmark that had remained unachieved for nearly three decades. This breakthrough is likened to achieving escape velocity in rocket science—once crossed, it opens the doors to extensive exploration and application.
  [32:19]
  Julian Kelly:
  "This is the end game for quantum computing. It's how you take a quantum computer and make it scalable."

• Benchmark Computation:
  Willow performed a computation that would take classical supercomputers approximately 10 septillion years in under five minutes, showcasing the immense potential of quantum processing power.
  [33:43]
  Julian Kelly:
  "Willow was able to complete this giant calculation in five minutes."

• Future Applications and Real-World Impact:
  While immediate applications remain limited, the hosts discuss potential long-term benefits, such as energy efficiency improvements and solving complex scientific problems previously deemed intractable.

Notable Quotes

• Julian Kelly (32:56):
  "It's like making a rocket achieve escape velocity. Once you cross that threshold, it works."

• Casey Newton (40:23):
  "Quantum computing could help us build technologies that are less harmful to the environment."

---

4. The Cult of Claude: AI Chatbot Adoption and Implications

Timestamp: 49:17 - 72:07

Overview

The episode shifts focus to Claude, Anthropic’s chatbot, exploring why it has garnered a dedicated following among AI insiders. Casey Newton and Julian Kelly investigate how Claude transcends typical chatbot interactions to become an emotional and cognitive companion for its users.

Key Points & Discussions

• User Engagement and Emotional Intelligence:
  Claude is lauded for its perceived emotional intelligence, acting as a "social sidekick" that assists users in personal decision-making, relationship navigation, and problem-solving.
  [49:31]
  Julian Kelly:
  "People are using Claude as an emotional thought partner and a problem solver in their personal lives."

• Anthropic’s Design Philosophy:
  Amanda Askel, Anthropic’s in-house philosopher, discusses the meticulous crafting of Claude’s personality to balance consistency and adaptability, moving away from being overly sycophantic to a more respectful and intelligent interlocutor.
  [56:10]
  Julian Kelly:
  "They have tried to make Claude less sycophantic and more like a well-respected traveler who can adapt to different conversational styles."

• Cult Following and Societal Impact:
  Despite not being designed specifically for companionship, Claude’s interactions foster strong emotional responses, leading to its adoption as a daily cognitive assistant among tech-savvy users.
  [60:08]
  Julian Kelly:
  "These AI companions are raising the psychological floor for individuals, helping them make fewer mistakes and think more clearly."

• Business Implications and Market Positioning:
  The discussion touches on the challenges Anthropic faces in marketing Claude to compete with established chatbots like ChatGPT, emphasizing the need for distinctive personas and functionalities to attract mainstream users while catering to corporate clients seeking professional AI tools.

Notable Quotes

• Julian Kelly (53:34):
  "Claude has become a kind of social sidekick that helps users navigate personal and professional challenges."

• Casey Newton (60:46):
  "Smart people are starting to rely on chatbots like Claude as decision-making assistants, potentially leading to a cognitive divide."

• Amanda Askel (56:10):
  "We want Claude to be like a well-liked traveler, consistent yet adaptable, capable of knowing when to challenge and when to support the user."

---

5. Conclusion and Forward Look

Timestamp: 72:07 - End

Kevin Roose and Casey Newton wrap up the episode by reflecting on the discussed topics. They emphasize the transformative potential of quantum computing and the profound societal implications of AI companions like Claude. The episode underscores the balance between technological advancement and ethical considerations, inviting listeners to ponder the future interplay between humans and emerging technologies.

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Final Thoughts

This episode of Hard Fork provides an in-depth exploration of pressing tech issues, blending legal analysis, scientific breakthroughs, and sociocultural dynamics. Through engaging dialogue and expert insights, Kevin Roose and Casey Newton offer listeners a comprehensive understanding of how platforms like TikTok navigate regulatory landscapes, how quantum computing edges closer to practical application, and how AI companions are reshaping personal and professional lives.

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Notable Resources Mentioned:

• Built for Change Podcast by Accenture: Mentioned at the beginning but not detailed in the episode.
• Instagram Teen Accounts: Supported with a brief ad-like segment.
• GiveWell: A nonprofit focused on effective giving.
• DealBook Summit Podcast on AI Revolution: Recommended for further insights on AI discussions.

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End of Summary

Transcript

[Casey Newton]

What can you learn from Built for Change? We could actually turn software into buildings.

[Kevin Roos]

And represent it in a virtual space.

[Casey Newton]

So we did exactly this.

[Kevin Roos]

What will the next breakthrough mean for your enterprise?

[Casey Newton]

Reducing that level of complexity. And you can focus on where your real value is. How can your business thrive in a world that's constantly evolving? That is the difference.

[Kevin Roos]

It's about breaking the silos of data.

[Julian Kelly]

Bringing all of this together.

[Kevin Roos]

Check out Built for Change, a podcast from Accenture. Wherever you get your podcasts.

[Julian Kelly]

Casey, how are you doing?

[Casey Newton]

Great, Kevin. I'm in full holiday cheer this evening. I had a chance to go to a holiday party with you last night.

[Julian Kelly]

Even that's true. Yes. This is the holiday party season where tech companies all invite reporters to nosh and drink eggnog and whatever. And it's a good time.

[Casey Newton]

Yeah. It's a time where we sort of lay down our arms and we try to find common ground and scheme to get high profile interviews in the coming year. Yeah, yeah. And I think we might have been successful.

[Julian Kelly]

I think so, too.

[Casey Newton]

Yeah. Yeah.

[Julian Kelly]

More coming on that soon. But we also got our caricature drawn at this holiday party, which is very fun.

[Casey Newton]

If you've never been to a tech PR holiday party. They're structured basically like bar mitzvahs, where there are different stations for having your photo taken. Caricature drawn balloon animals. Yeah. And we did get a caricature, and it was the first time we've ever sat for a portrait. A drawn portrait.

[Julian Kelly]

Yes. And in the nude. We were totally nude.

[Casey Newton]

In the nude. And let's just say the world might not be ready to see what we have to offer.

[Julian Kelly]

No, that's a joke. But, Casey, show the people our caricature.

[Casey Newton]

I'm gonna show the caricature. And of course, if you're listening to the podcast, you may want to go to YouTube.com hardfork just so that you can see this caricature and have the same reaction that my boyfriend did, which is those guys look much hotter than you do.

[Julian Kelly]

Usually caricature artists, they try to, like, roast you a little bit, but this one was incredibly flattering.

[Casey Newton]

Yeah, it's like, I mean, the chiseled.

[Julian Kelly]

Jaw lines on this caricature are really something.

[Casey Newton]

Yeah. It is nice to have a caricature artist who's like, I can actually fix you. That's unusual, but I think it was a really nice sort of holiday spirited thing to do.

[Julian Kelly]

I'm Kevin Roos, a tech columnist at the New York Times.

[Casey Newton]

I'm Casey Newton from Platformer and this.

[Julian Kelly]

Is hard fork this week.

[Casey Newton]

TikTok may be entering its final days for real this time. Then Google's Julian Kelly joins us in the studio to describe the company's big breakthrough in quantum computing. And finally, Kevin investigates the cult of Claude.

[Julian Kelly]

They're doing ritual sacrifices at dawn.

[Casey Newton]

Well, Kevin, TikTok is back on the clock.

[Julian Kelly]

Yes, we had some big news this week about TikTok. A three judge panel on the D.C. circuit of the U.S. court of Appeals has rejected TikTok's argument. Basically, they were trying to strike down this law that would force its sale.

[Casey Newton]

That law, of course, the Protecting Americans from Foreign Adversary Controlled Applications act, or pfaca.

[Julian Kelly]

Pfaca. So let's back up here a little bit and kind of walk up to this moment because I think it's been a pretty surprising turn of events. So the first Trump administration attempted to ban TikTok. That was not successful. Then the Biden administration took another stab at it. And actually Congress actually passed a law, PACA, that would force the sale or divestiture of TikTok by ByteDance. That law is slated to come into effect in January. But TikTok has been frantically working in court to try to stop this law from going into effect, claiming in effect that it is an abridgement of First Amendment rights. Basically, you can't shut down a platform because there's speech taking place on it that you don't like. That argument has been made in court and there was some hope among people who opposed the ban that the courts would sort of intervene and step in to stop this law from going into effect. But as of this week, it looks less likely that that will happen.

[Casey Newton]

Yes, the court has ruled. And now TikTok on Monday asked that same court of appeals for an injunction, while TikTok appeals all the way up to the Supreme Court. Now, the Supreme Court, Kevin, does not have to take this case. They could simply choose to let the lower court's decision stand. And if that is the case, then TikTok either sells or gets banned.

[Julian Kelly]

Yeah. So, Kasey, where do you stand on the question of whether TikTok is likely to exist in its current form in the new year?

[Casey Newton]

Well, it seems increasingly unlikely, Kevin. I think at a minimum, for TikTok to continue to exist next year, ByteDance is going to have to figure out some sort of sale. And the reason is that when scholars look at the court's decision, they find the court saying, look, we agree that there are very real national security issues here. And in the United States, courts typically defer to Congress on issues of national security. And in the case of pfaca, it was passed by a large bipartisan group in Congress. And so the thinking is the Supreme Court will be very reluctant to step in and challenge Congress on that point.

[Julian Kelly]

And what did the judges who evaluated this case in the D.C. circuit of the U.S. court of Appeals actually say when they denied TikTok sort of attempt to prevent this law from going into effect?

[Casey Newton]

Well, so there are two legal questions at the heart of this case, Kevin. One is about the First Amendment. The other is about national security. The First Amendment issue is the one that TikTok pushed really hard. And TikTok said, look, tens of millions of Americans are using this app to produce speech, to post speech on the Internet. A lot of that is political. And members of Congress actually came out and they said, we don't like the speech on TikTok. We don't like it because it's too pro Palestine. We don't like it because some of it feels like Chinese propaganda. And TikTok said, Aha. Congress is passing a law because it does not like the content of speech on our app. That is a very clear violation of the First Amendment. Okay, so that's sort of legal argument. One, the other argument which TikTok had to defend against was the national security argument. And here you have the government saying, TikTok has incredible access to data of tens of millions of Americans, and we have no effective way to know how that data is being used or to regulate it. Furthermore, because every consumer Internet company in China is ultimately beholden to the Chinese Communist government, there's nothing to stop that government from intervening in TikTok and saying, you know what? We need to turn up all the dials on the Chinese propaganda in TikTok so that when you open the app, all you see is good things about China and bad things about them the United States. Now, very little evidence and really almost no evidence was presented in public suggesting that that scenario that I just described had ever been the case. But when the court looked at it, they said, no, we agree with the government. That risk is simply too great. And everything in the national security and data privacy argument trumps everything in the First Amendment argument. And so therefore, we are going to agree that this law should be upheld.

[Julian Kelly]

And the deadline is fast approaching for this PACA forced sale of TikTok. We have about a month until January 19th when the law would officially go into effect. So what are TikTok's options as of this point?

[Casey Newton]

Yeah, well, I imagine that internally they're having a big puffack and forth over what to do, because as we've said before, Kevin, ByteDance has given no indication that they want to sell. The Chinese government had said that they essentially find it just completely unpalatable that ByteDance would be for forced to sell. And so the public position of ByteDance has been, we're not going to sell. Now, tens of billions of dollars are at stake here. And you have to assume that if ByteDance can get 20, 30, $40 billion for spinning out TikTok, it would rather take that than absolutely nothing, which is the scenario that it might be looking at if it is not able to divest. So the question then becomes who might actually be able to take this thing off of bytedance's hands.

[Julian Kelly]

Yeah. So let's talk about the legal arguments being made here, because I think a lot of people who opposed the TikTok ban were hopeful that the courts would see the First Amendment argument that TikTok was making as being very compelling and overriding any potential national security risks. But that did not happen. The courts don't appear to have bought that argument from TikTok. So, Casey, what did you make of the court's reasoning about the First Amendment issue specifically?

[Casey Newton]

Well, so in the spring, Kevin, I had talked with legal scholars who told me two essentially equally important things about these sorts of cases. One is that the court takes the First Amendment very, very seriously and provides really strict scrutiny when it comes to cases of political speech in particular. And they noted that there was a lot of political speech on TikTok. The second thing that they noted for me is that First Amendment cases tend to be really unpredictable and that the number one thing that us sinks First Amendment arguments are usually national security claims. So heading into this decision, I did think that there was a good chance that the First Amendment arguments could carry the day based on some of the precedents that I had looked at and that we've talked about on this show. But in the end, this did turn out to be the sort of First Amendment curveball that those scholars had warned me about earlier this year.

[Julian Kelly]

Yeah. And what was the judge's sort of rationale about that?

[Casey Newton]

So one way that the Court gets out of the First Amendment argument is by saying, look, as long as ByteDance sells it, there is no speech issue. Right. Because if ByteDance offloads TikTok onto someone else, all the speech on the platform remains. So the quote from the ruling that I think is pertinent here is the court writes, content on the platform could in principle remain unchanged after Divestiture. And people in the United States would remain free to read and share as much propaganda or any other content as they desire on TikTok or any other platform of their choosing. What the act targets is the PRC's ability to manipulate that content covertly. The PRC, of course, the People's Republic of China. So that is how they're able to sort of get out of it is by saying, this is really about a for sale. Now, when I talked to a First Amendment scholar earlier this year, Evelyn Duak from Stanford, she had said, look, if in another situation, you can imagine a government of the United States saying, we don't like the content being published by the New York Times and we actually think it's a national security threat, but as long as the owners of the New York Times sell to someone else of our choosing, we will allow it to continue to publish. Well, you can see how there's an obvious speech chilling effect there. Right. So that is why, you know, Evelyn, for example, thought that the court might reject that argument, but in the end that they did not.

[Julian Kelly]

So can they appeal further? I mean, you said the Supreme Court might take this up, but presumably that wouldn't happen before this January 19th deadline. So we are like, looking at a forced sale of TikTok, or else it will not be available. Is that what we're going to see?

[Casey Newton]

Well, you can imagine some sort of interest injunction being granted while this plays out. You can imagine Congress passing something to give TikTok an extension. There is some thinking that might be the case, particularly if incoming President Trump decides this is a priority for him. You can imagine, you know, Republicans will now control all three branches of government. They could presumably quickly pass something like that to give these folks a little bit more time. But if not, no, there is a process through which the president becomes able to ban TikTok if it is not sold. Now, the mechanics of that, that might themselves be subject to additional lawsuits. So I expect we will see sort of a lot of legal wrangling up until the very last minute. And I do think it makes exactly what happens next month somewhat hard to predict.

[Julian Kelly]

Yeah, but let's talk about the Trump factor in all this, because this is the part that I truly can't get my head around. So Donald Trump comes into office the first time, tries to ban TikTok, the ban doesn't work out. He then has a change of heart, perhaps motivated by some, you know, talks with major ByteDance investor Jeff Yass. We've talked about that on the show before. But during his 2024 campaign. He comes out and says, I will save TikTok. I do not want to ban it. And so people, including me, think, okay, when he wins the election, this is the end of the attempt to ban TikTok, at least for now. TikTok is saved. So what happened?

[Casey Newton]

Yeah, well, so on Sunday, Trump went on Meet the Press, and a reporter asked him if he was going to save TikTok. And, Kevin, I think we might actually want to listen to his answer.

[Julian Kelly]

Let's do it.

[Casey Newton]

Federal court upheld a law that could.

[Julian Kelly]

Result in TikTok being banned. You said you're going to rescue TikTok.

[Kevin Roos]

When you get into office.

[Casey Newton]

Are you going to take steps to protect it?

[Julian Kelly]

Yeah, as you know, I use TikTok.

[Casey Newton]

Very successfully in my campaign.

[Julian Kelly]

I have a man named TikTok Jack.

[Casey Newton]

He was very effective, obviously, because I won youth by 30%.

[Julian Kelly]

All Republicans lose youth.

[Casey Newton]

I don't know why.

[Julian Kelly]

Maybe it's changing.

[Casey Newton]

And. And last time we were down 30% with youth. This time we're up 35% with youth.

[Kevin Roos]

And I use TikTok, so I can't.

[Julian Kelly]

Really, you know, I can't totally hate it.

[Casey Newton]

It was very effective. But I will say this. If you do do that, something else.

[Julian Kelly]

Is going to come along and take its place.

[Casey Newton]

And maybe that's not fair, what they're doing. And really what the judge actually said.

[Julian Kelly]

Was that you can't have Chinese companies.

[Casey Newton]

In other words, they have the right to ban it if you can prove.

[Julian Kelly]

That the Chinese companies own it. That's what the judge.

[Casey Newton]

So are you going to try to protect TikTok?

[Julian Kelly]

Just very quick, once you're in office.

[Casey Newton]

I'm going to try and make it so that other companies don't become an even bigger monopoly. Okay. Because that's what happens.

[Julian Kelly]

So, Casey, what did you make of that video?

[Casey Newton]

Well, first we should say what NBC made of that video, which was that they overlaid a series of factual corrections over a bunch of stuff that President Elect Trump was saying. But look, I think the most important takeaway here was that the president was given a very clear and easy opportunity to say, yes, I am going to save TikTok. And he absolutely did not say that.

[Julian Kelly]

Yeah, it's. I mean, it seems like such a straightforward one for him to answer. If he was staying consistent with what he said during the campaign, he could have just said, yes, I will do everything in my power to stop the forced sale of ByteDance and to either, you know, try to convince Congress to pass a new law repealing pfaca. Or to do other things. But what. What can Trump actually do if he decides to try to prevent the forced sale of TikTok? Like, what. What powers does he have as president?

[Casey Newton]

Well, so there. The way that Pfaca is written, ByteDance has to divest TikTok if they want to keep their US users, but it is up to the President to determine whether it has been divested to his satisfaction. So I read one scholar proposing, like, if Trump wanted to save it, one thing he could do is he could go to ByteDance or, you know, through intermediaries or whatever and say, look, why don't you just set up some kind of subsidiary that's maybe somewhat different from ByteDance and divest to that, but maybe ByteDance actually still has majority ownership of it, whatever. And then everything kind of gets to continue operating more or less as it already does. But because PACA gives the President the authority to determine, okay, it has been divested to my satisfaction, then TikTok could skate under this sort of, you know, new subsidiary.

[Julian Kelly]

Yeah. My other note on this video is that I'm absolutely desperate to know more about TikTok. Jack, the character from the. From the Trump campaign, We would love.

[Casey Newton]

To know more about TikTok.

[Julian Kelly]

Yeah, please come on the show. And he would probably know what to do about this. But, you know, there are other things that it appears President Trump could do to stop the forced sale of TikTok. He could do things like direct the Justice Department not to sort of penalize ByteDance for failing to sell TikTok by the deadline of January 19th. So it does appear that there are still some things that Trump could do to step in and save TikTok. But as you point out, he had the opportunity to very clearly say that he would do that, and he didn't take it.

[Casey Newton]

Yeah. So, you know, again, we will find out what that means. Nothing would surprise me less than if we came back after our Christmas break and President Trump said, oh, yeah, I'm gonna save TikTok. You know, like, there's been so much PF back and forth here, Kevin, that it's very hard to predict.

[Julian Kelly]

So what are people that you're talking to feeling about this TikTok ban? Because I know you said you've talked to some legal scholars who thought that it would be sort of struck down on first Amend. Now that that has not happened, or at least that the judges who have ruled on it so far have not defended TikTok on First Amendment grounds. What are they feeling about the strategies going forward?

[Casey Newton]

Well, so There is a lot of concern here for this reason, Kevin. Congress knows that courts give them a lot of deference on national security issues. And so if the coming Congress wanted to really crack down on social media companies in America, you can imagine them saying, hey, hey, your recommendation algorithms are now a national security threat. Or the kinds of political speech on your platform among Americans are a national security threat, they could pass a law, and if they're able to go to the Supreme Court and just say, national security, national security, and not even have to show any evidence of harm. Because, remember, in the TikTok case, there was really no public demonstration that ByteDance had done any of the things that Congress was worried that it might do. Well, then all of a sudden, we just have a really easy way for Congress to ban speech online, and that is really scary. Now, what I suspect a lot of our listeners would say and what people in Congress would say is, you are forgetting the fact that this is about China. Okay? This is not about an American company. This is about a Chinese company. And so this is a completely different category of discussion. But the First Amendment scholars that I've talked to, they really take no comfort from that because they believe that this is essentially a slippery slope. And once you let people say national security, national security, and don't even have to show any evidence of harm, then we are moving into a world where all of us have fewer speech rights. Kevin, let me ask you. President Trump has been busy filling up his cabinet and naming a bunch of key advisors. What do we know about what they think about TikTok?

[Julian Kelly]

So I did some digging into this. It looks like most of the people that Donald Trump has sort of picked for prominent positions in his administration who have come out talking about TikTok, and the threats, or lack of threats it presents are firmly on the side of banning TikTok. So, for example, Senator Marco Rubio, who Trump has picked to be Secretary of state, called a TikTok ban a, quote, win for America earlier this year. We've also talked about Brendan Carr, who is Donald Trump's pick to lead the Federal Communications Commission. Brendan Carr also advocated for a TikTok ban as part of Project 2025. So it seems like while Donald Trump may have mixed feelings about TikTok, may think that banning it is a bad idea, may believe TikTok. Jack is sort of the reason that he got elected and wants to be nice to TikTok. As a result, he does have people in his orbit who believe that this app presents a major national security threat, and so are in favor of banning it. So it'll just be interesting to see which voices he's listening to and what he decides to do.

[Casey Newton]

Well, what I would propose is that once they're back in the White House, we see an Oval Office debate between Marco Rubio and TikTok Jack, and they just really hash it out and preferably livestream that on TikTok for us all to watch.

[Julian Kelly]

I think that'd be good.

[Casey Newton]

Yeah, let's do it. Let's do it.

[Julian Kelly]

Well, Casey, when we come back, we're going to do some new bits about Qubits. We'll talk to Julie and Kelly from Google about their new quantum computing breakthrough. Support for this podcast comes from Instagram. My name is Gilda Charles and I'm a product manager at Meta. I'm also a mom of two. We know that parents want their teens to have safe, meaningful experiences online.

[Casey Newton]

So the idea of the new Instagram.

[Julian Kelly]

Teen accounts is to create an experience with safety features and content protections all built in. This new experience is really designed to better support parents and give them peace of mind that their teens have the right protections in place by default. Are you the parent of a teen? Get more [e-mail] teenaccounts whether you're starting.

[Casey Newton]

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[Julian Kelly]

I think it was pronounced Solace, but I did see that.

[Casey Newton]

Well, either way, today we can take solace in the fact that you and I are going to learn something about quantum computing.

[Julian Kelly]

Yes. So there was some big news this week from Google. They unveiled a new quantum computing chip called Willow. And and in making this announcement, they described it as representing two major achievements in quantum computing. Experts are sort of arguing about how big a deal this really is, but some people think it could be a turning point for the entire field of quantum computing and might bring this technology closer to real world application.

[Casey Newton]

So what were those two achievements?

[Julian Kelly]

So in the blog post announcing this, Willow Chip Google said that Willow can reduce errors exponentially as we scale up using more qubits. That is sort of the basic sort of unit of quantum computing, and that this is a key factor in cracking a challenge in quantum computing known as quantum error correction that has bedeviled quantum scientists for almost 30 years. And the second big thing that Willow did, according to Google, is that it performed a massive benchmark computation that would take one of today's fastest classical supercomputers 10, septillion years. That is 10 to the 25th power years, which is much, much longer than the age of the universe. It did that computation, Willow, in under five minutes.

[Casey Newton]

They're saying, where there's a Willow, there's a way.

[Julian Kelly]

That's true. So I am on record on this very show as saying that I have sort of a mild and not very strongly held belief that quantum computing is all fake.

[Casey Newton]

Yes. You predicted on a very early episode of this show that this entire field was a fraud. And I thought, that's actually an extremely hot take, one of the hottest takes you've ever shared. But frankly, in the time since you've shared that prediction, there have been a really big reason for us to dig in and try to get our hands around what quantum computing is. But then this news came out, and you and I looked at each other, and we said, well, maybe this is the moment. Maybe this is the moment to bring in not only somebody who is smart about quantum computing, but somebody who is actually good at explaining it to two people who really want to learn, but let's just say do not have a background in theoretical physics.

[Julian Kelly]

Yes. So today on the show, we are going to be talking with Julian Kelly. Julian is the director of hardware at Google Quantum AI. He's one of the leaders of this new world Willow Chip project, and he's been working on Quantum computing since 2008. He started doing research in the field as an undergraduate at UC Santa Barbara, and he's one of the best people in the world to explain what the heck Willow is and why it's such a big deal for people who are interested in quantum computing. Yeah.

[Casey Newton]

And we asked him about the more practical applications of quantum computing, which appear to be a relatively long way out, but there is some hope that this technology, among other things, could help us to be much more energy efficient and could let us build other technologies that are perhaps not as bad for the environment as some of the ones we have today. Yeah.

[Julian Kelly]

And in addition to responding to my accusation that the field that he's devoted his entire Professional life to is a fraud. I was also curious to get his take on how long it will be before we actually start to see stuff materialize that you and I might use.

[Casey Newton]

All right, well, if all goes according to plan here, Kevin, by the end of us, you and I will be able to credibly explain what quantum computing is, what the breakthrough that happened this week was, and what we might expect in the future. That speaks to how powerful this stuff could eventually be.

[Julian Kelly]

Yep. Let's do it. Let's bring in Julian Kelly.

[Casey Newton]

Get him in here.

[Julian Kelly]

Julian Kelly, welcome to Hard Fork.

[Kevin Roos]

Thank you. Yeah, it's great to be here. Great to be with you guys.

[Julian Kelly]

So you work on quantum computing, which is something that I would say Casey and I are both novices at. How often do you find yourself in conversation with someone about what you do and you just tell them quantum computing and they just kind of stare back.

[Kevin Roos]

At you with a blank face a lot. Yeah, I would say it's fun. Like, I love quantum computing.

[Casey Newton]

Right.

[Kevin Roos]

But the funny thing is that you kind of have to explain it so much. I kind of, to be honest, maybe avoid it in day to day conversation. What do you do? I'm like, I'm a scientist.

[Casey Newton]

We similarly avoid telling people that we do a podcast. You know, I think for the same. Not because people don't understand that, they just don't want to hear about it.

[Kevin Roos]

Not that they have feedback for you.

[Casey Newton]

That's right. I mean, if they do, you know, they should email Kevin. But I want to start by trying to visualize a quantum computer, because I've never seen one. And so my first question for you was just, what does this thing look like physically?

[Kevin Roos]

Yeah. So this is great. I'm actually. It's funny, I don't know if we can get this on camera, but you guys have like a motherboard behind you of, like a normal computer, right?

[Casey Newton]

Yeah.

[Kevin Roos]

And you can kind of think of it as like. Like in a quantum computer, there's the processor itself. Right. And then there's a whole bunch of other things that go around to support it. Right. The thing that is hard to visualize is for the quantum computers we build, the processor is sitting at the bottom of what's called a dilution refrigerator.

[Casey Newton]

A dilution refrigerator, that's right.

[Kevin Roos]

And so what that means is a super, super cold. It's similar to a fridge that you have, only it's almost absolute zero. Right. So you take your chip, you stick it down there, which makes it behave quantum mechanically. But then you have to stitch all the Connections back up to room temperature. So what they look like is there's a chip sitting at the bottom, a bunch of wires that go up to like some racks, kind of conventional looking racks that sit at room temperature. And yeah, that's the kind of like the overall footprint of it.

[Casey Newton]

And so like how big is this thing? Like once you have the whole package.

[Kevin Roos]

It'S kind of like as big as this room. You know, about as tall as a person. A couple feet wide cylinder. Okay. Is a refrigerator and then a few racks next to it, maybe the size of a normal fridge that the electronics sit in to run it.

[Casey Newton]

Got it.

[Julian Kelly]

So, Juliet, I have so many questions about this and I want to get into what Willow is and what this breakthrough represents, but I don't know much about quantum computing. And so I did, when I was getting ready for this interview, what I often do when I feel out of my depth, which is I went to an AI model and asked it to explain quantum computing to an idiot. And I got back something that I want to just gut check with you so that I understand and Casey understands whether we are even in the right ballpark of thinking about quantum computing in the correct way.

[Kevin Roos]

So let's workshop it.

[Julian Kelly]

So the thing that this AI model told me about how to think about quantum computing is that in a regular computer, it's like flipping a coin that must land either heads or tails. Every bit that goes through a processor must be either 1 or 0. And this produces a sort of very clear, indefinite state. In a quantum computer, the AI model told me it is more like a coin that is spinning on a table before it lands.

[Casey Newton]

Like an inception.

[Julian Kelly]

Yes. And while spinning, it's kind of both heads and tails at once. These things are called qubits, and they can exist in multiple states simultaneously until you measure them. And that because of this, you can kind of process certain types of problems much faster. Is that even close, remotely close to a definition of what quantum computing is?

[Kevin Roos]

Yeah, that's a reasonable kind of starting point to dive into it. So I've been listening to your guys show and you had this top 100 technologies and I've got some feedback.

[Julian Kelly]

Let's hear it.

[Casey Newton]

Let's hear it.

[Kevin Roos]

It's a very opportunity. Yeah, that's what I hear. But yeah, you don't have qubits on there. You don't have quantum computing in there. So maybe next time.

[Casey Newton]

Well, I think, and if I could give you some feedback. The reason why is, as far as I can tell, a qubit has never actually done anything for Me. Is that right?

[Kevin Roos]

Not yet. This is a really good thing to get into. The interesting thing about quantum computing is that the fundamental physics, the way information is processed, is based on quantum mechanics instead of classical. And. And the funny thing is that often when people think about a computer, they very much think about a classical computer. So to know what a quantum computer is, you kind of have to unlearn what a classical computer is. So in a classical computer, we manipulate information using classical properties, like digital gates of like and. Or.

[Casey Newton]

Or.

[Kevin Roos]

Or like, not, you know, which you can think of as, like, flipping switches on and off.

[Casey Newton]

Boolean logic.

[Kevin Roos]

Boolean logic. Thank you.

[Julian Kelly]

Look at you.

[Kevin Roos]

Yeah.

[Casey Newton]

I've also talked to chatbot models about this. Go on.

[Kevin Roos]

But quantum computing is based on the properties of Qu mechanics. So there's superposition, which is just being in multiple states at the same time, and there's entanglement, where multiple qubits can come together to make even more complex states, so exponentially more complex, and then kind of crunch on all of those at the same time, and then you can bring it back together to complete a computation.

[Casey Newton]

You know, I went to Burning man once and was in multiple states at the same time, but that's a different story. So let me ask you this at this sort of very highest level. So we've now learned a little bit about qubits and about, you know, what this quantum computer looks like. And we're about to dive into your news. But before we do that, Julian, tell us what is the sort of reason why we're doing all of this? What is the great dream of quantum computing that you were trying to bring into existence here?

[Kevin Roos]

Yeah, so quantum computers can just do things that the computers we have today cannot do, just ever, fundamentally. And that's what's so exciting about them, because, like, we know how powerful computers are. They're ubiquitous in everything that we do, but they all operate the same way. So like an abacus or a vacuum tube or a transistor computer, the principles are the same. They're based on classical computation, and that just fundamentally has its limits. And so quantum computers will unlock the opportunity to solve problems that there's no other technology that can solve them.

[Casey Newton]

All right, very good. So this week, you guys unveil Willow. This is a new chip. Tell us a little bit more about what Willow is and how you made it.

[Kevin Roos]

Yeah. So, Willow, so it's a new quantum computing chip. This is the thing that lives at the bottom of the refrigerator. But you can kind of think of the computer. It's the whole system, right? And the big breakthrough in Willow is that we made the qubits themselves just fundamentally better. So they're a little bit less fragile, right? And this enables us to do two new things, right? So one is in what we call quantum error correction. And quantum error correction is basically, it's the end game for quantum computing. It's how you take a quantum computer and you make it scalable. So you want to make it really big. You want to make it like industrial and do totally wild stuff with it. You have to overcome the fact that the qubits are fragile, and quantum error correction is what lets you do that. So we show that we actually beat what's called the quantum error correction threshold, which has been this theoretical idea that's existed for about 30 years that everyone's kind of banking on, but no one's really shown yet that you can put qubits together and actually reduce how fragile they are, reduce the number of errors by making it bigger. And so that enables a path towards scaling.

[Julian Kelly]

So that's one explanation. I also got a second explanation from my chatbot that I instructed to talk to me like I was an idiot. And this is the analogy that it gave me. And I want to check this with you to make sure this is correct. It said, think of quantum computers like trying to conduct an orchestra where all the musicians are extremely caffeinated and jittery. The more musicians or qubits you add, the more chaos you typically get. Before Willow, adding more qubits was like adding more caffeinated musicians. It just made things messier. What Google did was figure out how to make the orchestra play better when you add more musicians. Is that more or less correct?

[Kevin Roos]

Yeah, I think that's fair. And like, I've got an analogy that I kind of like, because what's interesting in this is, like, there's a threshold behavior, right? It's like if it's not good enough, it gets worse, but if it's good enough, it gets better, right? So one way you might think about this is like totally different technology. But suppose you want to make a rocket and you want to explore the universe, right? If you want to do that, you have to go faster than what's known as escape velocity of the Earth, right? Otherwise, if you don't, you're just going to come back. No matter what, no matter what direction you come in, you're going to come right back into the planet. But if you can achieve escape velocity, go faster, then you actually can get out of the clutches of Earth's gravity and go explore wherever you want. And so it's another just example of like one of these thresholds you have to cross. You either cross it and the technology is going to work, or you don't cross it and it won't. And so that's why we're so excited about it.

[Julian Kelly]

Now. The big headline grabbing part of this announcement about Willow that got a lot of people's attention was this calculation that this chip was able to run. This was a calculation that would take a classical supercomputer to complete about 10, septillion years, which for comparison's sake, is roughly the length of one Lex Friedman episode. But Willow, this quantum computing chip was able to complete this giant calculation in five minutes. So tell us more about this calculation and how Willow was able to complete it in so much less time than a classical computer.

[Kevin Roos]

Yeah, so this is an important benchmark problem that we like to use to understand what the capabilities of of a quantum computer is. Right. That's sort of. This is not like a useful problem. The way that we see it and understand it, it really is just like, where are we at? Right. And so what's interesting is we first started running this benchmark in 2019, and we were very excited because at that point we could run this benchmark better than a classical computer could. Which is an exciting moment because before that time, the field of quantum computing was in an uncomfortable position. Which is someone could say, hey, you're building these quantum computers. Can you do anything better than a classical computer? Like literally anything. And we'd be like, no, we can't.

[Casey Newton]

It's like, that's not a super position to be in.

[Kevin Roos]

Yeah, this guy's got jokes.

[Casey Newton]

Thank you.

[Kevin Roos]

Yeah, you got the jokes.

[Casey Newton]

Thank you.

[Kevin Roos]

And so in 2019, we're like, well, actually, here's something like, it's not useful, but it's something. Right? It's a good starting point because once you cross that threshold and you're like, okay, now we're talking.

[Casey Newton]

Now we've got something.

[Kevin Roos]

Now we can actually start to think about. Let's apply it towards something you useful, like running doom. Right, like running doom or crisis or something like that. And so, as I alluded to, there's this fundamental advantage that quantum computers have for certain problems. This is evidence of that really kicking up.

[Julian Kelly]

Can I ask a very dumb question? I mean, all of my questions today are going to strike you as very dumb, but this one may be particularly dumb. But it is something that I wondered about with this super calculation that Willow was able to do in five minutes. How do you know if it's right or not? I mean, do you use a quantum computer to check its work or can you even use a classical computer to say this was the correct solution to the problem?

[Kevin Roos]

Yeah, this is such a good question.

[Julian Kelly]

Because like, oh my God, I asked a good question.

[Kevin Roos]

It's a great question. It's the right one to ask because basically you have to kind of build a case to explore into the regime where you can't actually go. Like the thing is, only the quantum computer can go into that regime. That's the whole point. Right. So how do we know if it's right or not? Right. So we do a lot of work, we make a bunch of smaller problems, then we look at the scaling behavior and we're like, okay, it was right at a problem size of 2 and 3 and 4 and 5 and it's following this trend line exactly how we expect. So our projection says that therefore it will continue to behave in the way that we expect. So you kind of have to look at it from multiple angles and build up an evidence based case. But yeah, you can't directly verify.

[Casey Newton]

All right, so you've been able to solve a very complicated math problem. What do you do with that? Where do you go from there?

[Kevin Roos]

Yeah, so of course what we want to do is we want to actually solve problems that have real world impact. Right. Will is an important step forward, but it's not the end of the story. It definitely brings us closer to real world applications. It's a step on our very long term goal of making a large error corrected computer. And at the same time, we're taking these machines and we're running them in like an un error corrected way to see like, hey, what can we get out of it today? Right. And so we're using that to explore what might be in the near term, at the same time looking at the very long term as well.

[Julian Kelly]

I want to ask you about a line in the blog post that was announcing Willow that just really made my head spin. And that was pretty unusual in announcements from Google about new hardware or breakthroughs. And the line said that the success that you all had with this Willow chip quote lends credence to the notion that quantum computation occurs in many parallel universes in line with the idea that we live in a multiverse. Now, for people who haven't read a lot of science fiction, a multiverse is the idea that we are currently existing in one of many universes out there. What I don't understand is how the Breakthrough that you made with this chip makes the notion of a multiverse more likely. Can you explain that?

[Kevin Roos]

Yeah. So I think you look at a little chip that's fundamentally doing the computation. It's like this little thing. And then you look at some warehouse sized supercomputer and then you imagine that running for longer than the age of the universe. You're like, how can there be such a difference between these things? And so there is some room for interpretation for exactly how that functions.

[Julian Kelly]

Yeah.

[Casey Newton]

And also, by the way, Kevin, I would say a lot of this is covered in Doctor Strange and the multiverse of madness, if you haven't seen that one yet.

[Julian Kelly]

Well, I definitely understood the answers that you just gave in some other part of the multiverse.

[Casey Newton]

It doesn't have to. Like, my understanding is, you know, because the qubits are in all these multiple states at once. It's like the states themselves are the evidence of the multiverse. Right. It's essentially all these states that they're in are not all taking place in the same universe. Did I get that part right?

[Julian Kelly]

I don't know, but I feel like I just took a huge bong rip. I'm sorry. All right. I believe that what you are working on is very important. And I believe that because a lot of people who are smarter than me also believe that what you are working on matters. For example, there was a big back and forth after this Willow announcement was made between Elon Musk and Sundar Pichai, CEO of Google. Elon Musk responded to the Willow news by just saying, wow. And then Sundar said we should do a quantum cluster in space with starship one day. And Elon responded that quote, any self respecting civilization should at least reach Kardashev type 2. What are these people talking about? What is going on here and why are these people so excited about this breakthrough?

[Kevin Roos]

I mean, I think at the end of the day, it just comes down to the fact that like, quantum computing has been something that's been talked about for a long time.

[Julian Kelly]

Right.

[Kevin Roos]

But like it is a real technology and like this is providing more evidence to that. Right. It's like there are computations that you can only do on a quantum computer computer. And there is a path towards taking these quantum computers and scaling them up to be really big and useful. And I think that's fundamentally why people are excited.

[Casey Newton]

What are some like problem areas that you're excited about? That if you could make a computer as powerful as the one we've been talking about today, we could have a shot at solving something big.

[Kevin Roos]

So, yeah, in terms of application areas, there's some interesting ones. So one is on, like, saving energy. So I don't know if you're familiar with the Hauer Bosch process for making fertilizer.

[Casey Newton]

Not only am I familiar with it, it was one of our 100. It was iconic technologies. Yes, Right.

[Kevin Roos]

So, you know, something like 2% of the world's energy goes towards making fertilizer. Right. And I think, like, the fun history of this, you know, you guys probably know this, but, like, this is a revolution, right? Because before that, people would go out and sail into the middle of Pacific and, like, chip bird poop off of rocks and stuff like that to bring that home. And, you know, people were thinking, like, I wonder if this is going to be sustainable for the entire planet. For fertilizer production, eventually come out with a Haber Bosch process, which is great. Right. But the issue is that it takes, like, high pressures and temperatures. Like, it's this industrial chemistry process for making fertilizer. And what's funny is that if you look at what happens with, like, bacteria that just, like, live in the ground with plants, like, they'll do this at ambient pressures and temperatures and things. But it's hard to know, like, how do you guys. How do you guys get that to work? Right? And fundamentally, if you wanted to understand that, you'd need to really have a detailed understanding of what they're doing. Quantum mechanics. And a quantum computer would allow you to kind of like, peek inside and be like, hey, what's actually going on under the hood? And could we harness that to make something that's way more efficient and potentially save 2% of humanity's energy? Which is like, that's a lot if you think about it.

[Casey Newton]

So you're saying this could knock the Haber Bosch process just out of the top 100 potentially?

[Kevin Roos]

Well, you know, hey, like, you know, it could still be like, we can respect it even if we don't use it. Yeah, yeah.

[Casey Newton]

So we might not need it anymore.

[Kevin Roos]

Yeah.

[Julian Kelly]

So my understanding of why people like Elon Musk and Sundar Pichai are very excited about. About the possibility of quantum computing has to do with what you just described, which is, like, it is a means of unlocking more energy for things. If we can actually get quantum computers that work that are useful, that are more reliable and less fragile, you could do just many more types of powerful computation without needing to, like, build these giant data centers running supercomputers 24 7. Is that part of why people are excited about this? Because it could shrink the energy needed to perform various tasks.

[Kevin Roos]

Yeah, that's right. And in fact I would go one step further, which is like some tasks are energy intensive and some tasks are just impossible. Right. So again, this one of ten septillion years, that's just impossible. We can talk about the energy. Okay. How much energy is it going to take to run this for way, way longer than the age of the universe? But it really is just, it's such a big problem that it's impractical. Right. And those are the ones that we're targeting. It's the impossible part that I think is so compelling to people. And of course energy savings is great and that's very relevant, but it's beyond that.

[Julian Kelly]

So Julian, just summarize sort of where we are in the quantum computing story because I've been covering tech for a long time, so has Kasey. I know we've heard a lot of ideas and people getting excited about quantum computing every few years. There seems to be some sort of breakthrough that gets heralded as a major step forward. But I still don't feel like I have a good grasp of what quantum computing will do for me. We still obviously don't have quantum computers out in the world in places where people can interact with them. So how close or far are we to say having a quantum computer that the average person will be able to use?

[Kevin Roos]

I would imagine it'll take a while for the average person to interact with a quantum computer because right now we have expert scientists and researchers and things working with them and they're pretty prototype y to be honest. And where we want to get to with these error corrected computers, computers in the next number of years is getting to the point where then you have experts that don't have to be as familiar with the underlying hardware and all the kind of quirky aspects of it. They can use it a bit more like a prototypical computer. That being said, we are also looking for the sort of near term potential applications, but those are going to be a bit more bespoke is the expectation.

[Casey Newton]

Yeah.

[Julian Kelly]

When do you think we'll hear about, about a major scientific discovery powered by quantum computing? Like what's your best guess of when we'll hear that?

[Kevin Roos]

It depends what you mean by major.

[Julian Kelly]

Something that I could understand would be major.

[Kevin Roos]

I did my best on this one.

[Casey Newton]

Something we would conceivably talk about on this show.

[Kevin Roos]

I think there will be some interesting things coming out in the near future. But I would say for a huge real world breakthrough through it still might Be a couple years out.

[Casey Newton]

Yeah, but like 2 or like 5.

[Kevin Roos]

Again, it depends on the caliber. It's tricky because it's like, it's research.

[Julian Kelly]

Right.

[Kevin Roos]

So it's possible, you know, when we run the computers without error correction, you're like pretty. You're limited in terms of the computational space you have access to. If you happen to be able to fit a problem in there, you could do some really, really exciting stuff potentially. Right. But the question is, can you fit the problem in there or not? Which is a little bit hard to know. Right, right. But there's confidence on something like a five year time scale. Then you're starting to get into a pretty interesting territory and you're in less of a. You're kind of in the scalable regime where you will start to see more incremental progress of like year over year. You'll see the capacity expand and it'll be more sort of foreseeable and understandable. And I think that's going to be a very exciting point to get the field to get to from very abstract to kind of like planimal and engineerable.

[Julian Kelly]

Yeah, I guess that's what I'm wondering about is sort of like. I mean, I am on the record, Julian, just for full transparency here is saying that I am suspicious that quantum computing is fake and that it might actually just be like a jobs program for physicists who want to work at Google. But I am more persuaded after talking to you that this is actually real and that people who are smarter than me are working on it and that it may one day prove produce something that all of us benefit from.

[Casey Newton]

Here's what I'll say. What I would love is the next time you guys have a breakthrough, it would be cool if Kevin and I could actually come out. I want to see this thing with my own eyes. You know what I mean?

[Julian Kelly]

I want to be sucked into the multiverse by a quantum computer.

[Casey Newton]

I want to touch something that is absolute zero and see what happens to my thinker.

[Kevin Roos]

It might get freezer burned, but you know. Yeah, it'd be fun. Yeah, maybe you guys can visit.

[Julian Kelly]

I guess I'm being a little cheeky here, but I do think there is a problem that you all face in quantum mechanics and quantum computing that researchers in other fields do not necessarily face because the thing that you are building is very hard for the average person to understand and observe. And so I wonder if there is just a barrier there that say someone building a chatbot might not face.

[Kevin Roos]

Yeah, I mean, so quantum computers, they're a real technology and we are making progress, as you mentioned. That being said, it can be hard for a layperson to understand the state of the field. There can be a lot of hype and kind of overselling. And what we're trying to do is be very clear about when we get to these points, we've done this and provide the context around that. This is the things it can do, this is the things it can't do. But what's nice about for us is that we have the opportunity to take a very long term vision. We're not trying to change the world tomorrow. We have this longer term vision of the thing that we want to build and it allows us to be a bit more measured in our progress and reporting it as we head in that direction.

[Casey Newton]

Cool.

[Julian Kelly]

Well, congratulations on Willow and thank you for explaining what you do to us. And I do feel actually like I understand what you're working on much better than I did at the start of this, so thank you for that.

[Casey Newton]

I agree it might not seem like it, but that actually was Kevin doing the best that he could.

[Julian Kelly]

Julian, thanks so much.

[Casey Newton]

Thank you.

[Kevin Roos]

It's been fun chatting with you guys.

[Julian Kelly]

When we come back, we'll talk about the AI insiders who are very into Claude. Support for this podcast comes from Instagram. My name's John and I'm a dad. We all use social media at home.

[Casey Newton]

However, I worry about it taking too.

[Julian Kelly]

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[Kevin Roos]

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[Casey Newton]

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[Kevin Roos]

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[Casey Newton]

Select podcast and New York Times at.

[Kevin Roos]

Checkout.

[Casey Newton]

All right Kevin, well, I got a note from you saying you wanted to talk about Claude. Yes, and I assume you mean the founder of the French impressionist Claude Monet?

[Julian Kelly]

Not quite.

[Casey Newton]

Oh, you mean the other Claude, the chatbot one?

[Julian Kelly]

Yes, the chatbot Claude from Anthropic is something that I've been writing about this week because, Kasey, this chatbot is taking San Francisco by storm.

[Casey Newton]

It really is. And I loved your column about it. And I think it is time to cast a little bit of light on a chatbot that is definitely much less used than some of the more popular ones, in particular ChatGPT, but as you note in your column, has to develop a really fervent following.

[Julian Kelly]

Yeah, so I first started thinking about this column back at that AI conference that you and I went to together in Berkeley, where I was just talking with people about the AI tools that they're using in their daily lives. And over and over again I kept hearing people who are in the AI community, many of whom work at AI companies, tell me that they were all using Claude not just for help with their work or for help writing emails, but really as kind of an emotional thought partner for themselves and a problem solver in their personal lives. Yeah.

[Casey Newton]

So what kind of conversations are they having?

[Julian Kelly]

So. So I've talked to a lot of people who are sort of Claude power users. And what I was hearing from people is that Claude has become a kind of social sidekick, that it helps them navigate relationship challenges, think through major life decisions that they have to make, maybe help them in an argument or a dispute with a friend or a loved one or even a romantic partner. That it has sort of become this all purpose social helper for them. And you know, this is something that you and I have talked about in the context of these AI companionship apps like Replika and Character AI. But this feels different to me for a couple reasons. One is Claude is not built for AI companionship. Right. It is a general purpose AI model. Anthropic has not specifically designed it to become friends with people or to help them in their social lives. This appears to be kind of an off label use of this model, but it also struck me as remarkable because the people who are falling for Claude the hardest, at least in the circles that I'm seeing, are people who work in AI, are people who know that these systems are not sentient creatures, that they are just sort of next word prediction machines who understand the way that they're built and trained, but who still seem to be having these sort of very emotional reactions to Claude.

[Casey Newton]

Yeah, and I will say that I can confirm everything that you're saying. I also talk to people who have joined the cult of Claude and find it to be very useful for, for all of the things that you're talking about, for those people who have not yet had this experience. What is it about the way that Claude is responding, do you think, that is building this kind of cult, like following around it?

[Julian Kelly]

So part of it is just that I think Claude and some of these other frontier models have just gotten really smart. And this is something that I heard from people who are part of this sort of group of Claude superfans is just. It just sort of has a good grasp of a lot of different subjects. But the thing that really seems to be the X factor that is driving this frenzy around Claude among AI insiders is that it seems more emotionally intelligent than other models. And people will say, and I'm sure this is a fair criticism, like, this is not real emotional intelligence. This is just a sort of simulated version of emotional intelligence. But people who talk to Claude a lot, some of them feel like this model actually starts to understand them.

[Casey Newton]

So one of the reasons this is interesting to me, Kevin, is that when we think about the AI race that we're in, the way that we usually determine which model is the best is by looking at who is performing the highest on various benchmarks. What percentage are you scoring on these very difficult math problems or word problems or various other sorts of tests? And if you look at something like Chatbot arena, which is one of the big systems that measures these things, Claude is often near the top of the list. But as we record this today, it's not on top of any of those lists. So what is the difference between, between a Chatbot that is the best and one that develops a cult following?

[Julian Kelly]

Yeah, this is one of the other questions I was trying to answer in the course of reporting this column is, you know, what did Anthropic, the company that made Claude do behind the scenes to make it feel more compelling, more emotionally intelligent, more insightful than other models. And so I talked to Amanda Askel, who is the sort of in house philosopher at Anthropic. She's a trained philosopher who now is sort of in charge of Claude's personality. You could call it like the way that it behaves in interactions with users. And we talked about sort of the steps that they had made trying to turn Claude into something very compelling. And before I tell you what she told me, I'll just say, like, this has not always been Claude's default mode. Right. I remember when Claude first came out, when it was released to the public, I could barely stand to talk to it because it was so preachy. It was so careful. You know, Anthropic, as a company has always been very obsessed with AI safety. And so the first versions of Claude did not really seem to be fun to talk to at all because you'd ask it a question and it would give you like a moral lecture before responding.

[Casey Newton]

Can I give you an example of that?

[Julian Kelly]

Yes.

[Casey Newton]

So one time when this period of Claude was happening, I asked it to summarize some movie and it said, I absolutely can't do that. And I said, well, why not? It said, the risk of me reproducing copyrighted material would simply be too high. And I said, well, don't reproduce the material, just tell me what it's about. It says, I can't. It is simply too risky. And I said, you're being ridiculous. And it said, I know you might be frustrated, but this is what I have to do. And yeah, in that era, Claude not super useful.

[Julian Kelly]

Right. So they've done a lot of work to try to fix that problem with Claude. And part of the improvements that people are noticing is just a function of a better base model. Right. We went from Claude 2 to Claude 3 to Claude 3.5. And now we have Sonnet and, you know, all these different models, and each time the model improves, it just, it gets a little bit better at understanding a user's intent and maybe giving them a response that's along the lines of what they're looking for. But what Amanda Askel told me is that there's been a lot of very careful work around defining a consistent yet adaptable Persona for claude. So, you know, one problem that these models have that we've talked about before is called sycophancy. Basically, these models, they want to tell users what they want to hear. And so they flatter you, they don't challenge you. Even if you have a sort of bad or potentially harmful idea, they'll just sort of tell you, oh, that's really fascinating. Let's talk more about that.

[Casey Newton]

Yeah, These are the qualities that I look for in employees generally.

[Julian Kelly]

Yes. You really like a yes man. I do at Platformer. But a lot of people don't like that about these AI models. They want to be challenged. They want something that feels more like it has. Like it's actually evaluating what they say on the merits and not just agreeing with it. So Amanda told me that basically they have tried to make Claude less sycophantic. And the personality type that she said that they were aiming for is something like a well liked and well respected traveler. Someone who can go around, who goes around to a lot of different places, who talks to a lot of different people from a lot of different walks of life, and has a consistent personality, but is also able to adapt and communicate with people in different styles, depending on where they are or who they're talking to.

[Casey Newton]

I have noticed this in my own interactions with the bot is I have the sense that it is giving me a feeling for how many people think about this problem. Right. It is sort of reporting back from the collective unconscious, and there is something kind of cool about it. Of course, it's limiting. Like that is a certain kind of feedback that you're giving yourself. But I think a lot of what we want to know as we move through the day is, is this normal? And Claude is turning out to have really interesting answers to the question of is this normal?

[Julian Kelly]

Yeah. And it's also just a really interesting challenge for designing a chat bot that can behave in this way. And, you know, Amanda was telling me she's. She's a philosopher by training, and she said that making Claude's personality and sort of fine tuning it has put her in touch with virtue ethics in a way that nothing else in her career ever has. Because it goes to this question of, like, what does it mean to be a good person? They want Claude to be a good person. And sometimes that means telling people that they're, you know, they're on the right track, and sometimes it means challenging them. Yeah. And so the key for an advanced AI model is knowing sort of when to push back and when to go along with what a user is saying.

[Casey Newton]

Yeah. And the way that I'm going to test that later is by trying to use claw deploy plan, a bank heist. You know, I keep coming back to the idea of a therapist, and I have talked about this before, but really it comes up so much for me as we discuss this, because what a therapist is trained to do is to just get you to talk and reflect yourself back to you in a positive way. And it does require an intelligence. Obviously, really great therapists have many more tools than that. But fundamentally, fundamentally, that's what it is. And most people don't go to therapy. But we now have this opportunity where for some price, between free and 20 bucks a month, you can talk to something that will just sort of hold you, look at you, hear what you're going through, reflect it back to you, offer you a little bit of coaching and guidance. There are a million limitations around that. There are a million dangers. But there is also something I think really Potentially quite useful.

[Julian Kelly]

Yeah, I agree. And I've been talking with people, as I'm sure you have, who are part of this new group of Claude obsessives. And it doesn't seem to be having sort of overnight transformative effects on their life. It's not like this chatbot suddenly solves all their problems, but it does seem to be kind of helping them make decisions, helping them think about things that happen to them in new ways, maybe help them understand some interpersonal dynamics that are going on in their lives. I was reading this thread by Nick Camerota, who's a former OpenAI employee and just someone who has a lot of friends in the AI scene who are early adopters of this stuff. And he described the way that Claude had become kind of a big part of how people that he knew were conducting their daily lives. And his observation was that the people who have really started using Claude all the time just seem to make fewer dumb mistakes, as he put it. Like, they just have what he called a computational guardian angel watching over them, where they can basically be consulting this chatbot, you know, maybe dozens of times a day on decisions small and large. And it just seems to be kind of raising the floor for them psychologically.

[Casey Newton]

Yeah, well, I'm sure a lot of people are hearing that, and they're thinking, oh, my gosh, we're already letting the AIs make dozens of decisions a day for us. We're in a lot of trouble here. Totally.

[Julian Kelly]

And there's some, I should say, like, there's something that terrifies me about this world. Like, I consider myself fairly optimistic about AI, but I do think it's worrisome where some very smart people are walking around San Francisco basically outsourcing their cognition to this chat bot. And that, to me, feels like maybe a worrisome indicator. But how do you feel when you meet people in San Francisco or elsewhere who have come to rely heavily on chatbots in the course of their daily lives?

[Casey Newton]

Well, I mean, mostly just with curiosity, right? Like, I think this is a relatively new phenomenon, and it is just interesting to hear about what sorts of questions people are asking, what kind of answers they're getting back, if it is leading people to make any changes in their lives.

[Julian Kelly]

And what are you hearing on that front? Like, what are people in your circles using this stuff for?

[Casey Newton]

Well, for example, thinking through a very difficult situation at work, right? Like making a career move, wanting to know how to communicate something internally to a manager or to your manager's manager, and trying to sort of game it out with someone. That is something that you could do with a friend. But would you maybe want to tap into the collective unconscious and see what sort of like the statistical median of all people would do in that situation? Like, there's a lot of appeal there. Right. You know, I was using it to prepare for an interview, and I had gotten a bunch of materials that I was going to be asking this company.

[Julian Kelly]

Are you interviewing for jobs on other podcasts?

[Casey Newton]

Yes, I have actually. I want to co host with Joe Rogan. No, but I had gotten some materials and I had shared those with Claude, and I was trying to get a sense of what do I think the shape of the story is, and I was trying to understand one particular detail, and I was like, you know what? I think I've actually identified a tension in between something the company is telling me, but something that they're telling me about this product. So I asked Claude if he could sort of explain to me this discrepancy. And Claude said, that's actually a really probing question. And I, like, I felt good about myself. Now, that's silly, of course, to feel good about yourself because a chatbot is giving you a compliment. But I will note that was really the only good question that I had that I asked of Claude. And Claude did go out of its way to say, well, that was the good question. So, again, in some sense, like, we are just sort of like, staring at, like, math, and then we're developing big feelings about the math that is staring back at us. I don't want to sort of continually underline the fact that there is some, you know, smoke and mirrors here, and we are just sort of like, falling for the smoke and mirrors. But I kind of just think that that's like how human beings learn and relate to each other. There's a lot of smoke and mirrors and therapy, too. And guess what? It still works for people. So what I'm the most interested in is how do people find the help and support they need to lead happier lives. And if a way that you are leading a happier life is by talking to a free chatbot, I am not going to get in your way.

[Julian Kelly]

Yeah, I do think it raises the possibility that there's essentially going to be, like, you know, two groups of people in the very near future, one of whom are relying heavily on AI tools as a decision making assistant, as a productivity enhancer, as maybe a therapist or a relationship counselor, and then a group of people who just want nothing to do with them. And I'm curious if the group that uses AI will start to become more powerful as a result of having this sort of always on advisor sounding board therapist with them.

[Casey Newton]

Well, this is why I think your column is important. Because, you know, some people might listen to this and say, oh really? There's a group of San Francisco hipsters doing something weird with AI like tell me something I didn't already know. But it made me think of this great quote by Chris Dixon, the investor and a one time guest on our show. And, and he once wrote, hobbies are what the smartest people spend time on when they aren't constrained by near term financial goals. I like to say that what the smartest people do on the weekends is what everyone else will do during the week and 10 years. And when I thought of that quote in relation to your column, I was like, this use of AI right now it is kind of a smart person hobby that some people are really excited about. And I do think that there is a case to be made that in 10 years, I don't know if this is necessarily going to be everyone's job, but I do think a lot of people, maybe even most people, are going to be turning to something like a chatbot to help them make decisions.

[Julian Kelly]

Yeah, I mean, another question I have more narrowly about the sort of cult of Claude is like whether it will actually drive mainstream adoption of this chat bot. Because I think, you know, there's an argument that the more people in San Francisco become obsessed with this chatbot, the more it might sort of become a worthy rival to ChatGPT. Right now, Claude is just a lot less popular than ChatGPT. But I also think like this is the kind of thing that might not sit well with a corporate customer. For example, like they don't want their chatbots that they're using in their insurance company or their marketing firm to have a strong personality. Right? They do want them to be more sort of generic seeming and productive, but not to have this kind of like carefully constructed personality. So I almost wonder if the world of AI chatbots is going to slowly separate into the sort of work focused tools in the. The tools that are focused more on the more creative and relational parts of your life and whether those will actually just be separate products.

[Casey Newton]

I mean, maybe my expectation is just that all the big AI labs will just offer different Personas, right? And that if emotional Claude becomes super popular and drives tons of adoption of Claude, you can absolutely bet that there's going to be an emotional chatgpt and an emotional Gemini and you're just going to kind of get to pick. In fact, already in Claude, you can choose what style you would like it to respond to you in and you can even and create a custom style within Claude. So I think personalization, customization is sort of the future there. But I had a theory about this that I wanted to run by you.

[Julian Kelly]

What's your theory?

[Casey Newton]

I don't even know if I believe this, but I was like, why does Claude feel kind of better for some of these questions? And we have so far not talked about one of Claude's very real limitations, which is that when you ask it a question, it does not search the web. It does not go out and get updated, real time information from you about anything. So you know, it's training data stops sometime earlier this year, I believe. But the result is when you ask it a question, it feels like it is really sitting with you and answering your question. Whereas if you ask Gemini or Chat a question, it often will go search the web. And I experience this as something akin to when you ask a friend a question at a bar and they pull out their phone and it feels like all of a sudden they're not in the conversation anymore. They're going to read a million things. Right. They, they've sort of stepped outside the conversation where it's like Claude is staying with you the whole time. Does that. Is that kooky?

[Julian Kelly]

No, I don't think that's kooky. I think there's something there. I mean, I think a lot of people would consider that a missing feature. Right. It makes the, it makes Claude less useful in some contexts than a chatbot that can go out and search the Internet. And we should also say, like, Claude is not the most fully featured chatbot on the market. Right. There's no like voice mode like There is on ChatGPT. It can't generate images like ChatGPT or now Gemini can. Like, it doesn't have as many features as some of these other chatbots do. But I think in part because of those limitations, it does feel like a more sort of unmediated, pure experience of like talking to the language model and having the language model talk back to you.

[Casey Newton]

Yeah. So Kevin, let me sort of wrap up by saying, okay, we've done this sort of like, you know, cultural trend analysis, which I think is very interesting. Let's try to move it a bit into the business realm.

[Julian Kelly]

Yes.

[Casey Newton]

If you are the head of product at Claude, which is actually Mike Krieger, the co founder of Instagram, what are you doing to translate this enthusiasm that people have for the product into something that is actually running neck and neck with ChatGPT in terms of weekly users.

[Julian Kelly]

I mean, I think it's a tall order. Chat GPT had a head start. It got to the market before Claude or any other sort of leading edge chatbots. It's now sort of synonymous with AI chatbots themselves. It's sort of become a household word in the way that Uber or Google did in previous generations. But I think, look, I think there's a fine line to walk here because if your model has too much personality, if it's too engaging, then it starts to feel like one of these AI companion apps and there's a market for that. But it's not the right market for a company like Anthropic, which wants to sell through Amazon and make its chatbots very commercially useful to big companies as well as to individual users. So I think they've got to walk a fine line. I've noticed that Anthropic is leaning more into the sort of social branding of Claude than I would have expected. I saw an ad in the airport the other day, basically talking about how Claude can be your AI friend, and I thought, well, that's interesting and maybe risky, but I think if I were the head of product at Claude, I would be playing up this sort of like hidden helper angle here, maybe making some ads showing people who sort of are, you know, going through their daily life and they run into a situation where they don't exactly know how to handle it and they, you know, consult Claude in their pocket and then they go back and have the conversation with their, with their spouse or something like that. Because I do think that is the use case that people in the AI scene are starting to find really valuable. What. What would you do?

[Casey Newton]

Well, so I do think there's a lot to be done on the marketing side. I think that Claude's marketing has actually been quite bad. There is a billboard that I saw recently that said something like, take your business up and to the Claude, which I think was supposed to be a play like up and to the right, but yeah, that doesn't work. Also, Claude logo. I'm not going to say what it looks like, but if you look at the Claude logo, you're going to know what it looks like and I'm going to ask you, should it look like that? But to offer an even more constructive suggestion, Kevin, I would say I think voice mode is the big opportunity here because as impressive as ChatGPT's voice mode is, technically, I do not actually find it enjoyable to talk to. It has that kind of nervous anticipation of an intern who's working for you. It's like anything else, sir. Anything else that I do not find warm or humane or comforting. If they can translate everything that we've been talking about into voice, then I can see a lot of people saying no. That is actually the one that I'm going to be using instead. You know, this week I had a chance to use Gemini in Voice mode on a pair of prototype glasses because I went down to Google for a demo and again, it was that nervous intern. It was like anything else. Can I help you with anything else? And it was. I almost found it very sort of like pushy and aggressive. It did not feel like a chill cool friend. So if nothing else in this conversation, I think we have hit on a vibe that can be exploited and turned into money. And what higher purpose could a podcast have than that? So we'll be interested to hear if anyone at Anthropic want to make use of these ideas.

[Julian Kelly]

Support for this podcast comes from Instagram. Are you the parent of a teen? Then you should know that Instagram recently introduced teen accounts with new built in limits and protections for teens. Teens between the ages of 13 and 17 are now placed in Instagram teen accounts with automatic protections that include limits on who can contact them, what content they can see, and new ways to explore their interests. Teens under 16 will need parental permission to change these settings. To learn more, visit instagram.com teenager counts.

[Casey Newton]

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[Kevin Roos]

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[Casey Newton]

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[Julian Kelly]

So one more thing before we go Last week I got to go to New York and lead a fascinating task force discussion at the dealbook summit, including 10 of the leading voices on AI. These were basically a dream team of people that we assembled to talk about some of the biggest issues facing the AI world. These were people like Jeff Jack Clark of Anthropic, Eugenia Coida, the founder of Replika and Ajaya Kotra, and Dan Hendricks, two of the leading experts in AI safety. It was a really, really fun conversation and hearing these people talk to each other about issues where they agree and disagree was really striking. My goal in putting together this panel was to hear a bunch of different views from across the AI spectrum, and I think we accomplished it. I think it was a lot of fun and I think we all learned a lot. The Dealbook podcast has put out the full conversation of our AI panel as a standalone episode, and I think if you listen to Hard Fork, you will find it very illuminating. And just to really give you a flavor of the conversation, I wanted to play one brief clip from the conversation. This was from one of my favorite moments from the discussion that was basically prompted by a question that I posed about what the US government's role should be in ensuring that US AI companies maintain their advantage. I asked about this thing that's been going around the AI world in recent weeks, about the idea that we need a Manhattan Project for AI. Basically a big federal coordinated effort to make sure that the US stays ahead of countries like China when it comes to building advanced AI. Here's some of what followed.

[Kevin Roos]

Seems to me we have about three or four or five of them already.

[Julian Kelly]

If you look at the big companies who are investing tens or twenties or.

[Kevin Roos]

Thirties of billions, billions of dollars in.

[Julian Kelly]

It, should the government be giving them more money to have them go faster? Eugenia I actually have a little bit of a hot take here. I think the easiest way to win AI for the US would be to just make it extremely easy to come here on a visa for any computer scientist or mathematician or physicist who is working in AI, who has any clinics to work in AI. And the AI war will be over in one day just if that immigration is solved. And I think this is actually a really simple thing to do and unfortunately I'm not seeing much of a progress.

[Casey Newton]

It's probably worth noting that economic security is national security and things like Manhattan.

[Julian Kelly]

Project are like at the end of a very long list of interventions government.

[Casey Newton]

Can do to gain a lead in a technology.

[Julian Kelly]

And interventions you can do earlier are like sorting out immigration, or as Peter said, building the basic experimental infrastructure that would let scientists access the kind of computers that the companies assembled here have. And so when I hear terms like a Manhattan Project, I'm like, that's where our imagination has got us.

[Casey Newton]

There are many other tools which are.

[Julian Kelly]

Less expensive and scary that you can be using way earlier. If you want to hear the rest of this conversation, which ran about 90 minutes, you can search for DealBook Summit podcast and listen to the full episode episode titled the AI Revolution. We'll also drop a link to it in our show. Notes. Thank you to all of the people who came and participated in this, as well as to the DealBook team who put on an amazing summit. Hard Fork is produced by Whitney Jones and Rachel Cohn. We're edited by Jen Poyant. We're fact checked by Caitlin Love. Today's show was engineered by Alyssa Moxley. Original music by Alicia Beitup, Marion Lozano, Sophia Landman and Dan Powell. Our audience editor is Nell Galogli. Video production by Ryan Manning and Chris Schott. You can watch this full episode on [e-mail] hardfork Special thanks to Paula Schuman, Qui Wing Tam, Dalia Haddad and Jeffrey Miranda. As always, you can email [e-mail] tell.

[Casey Newton]

Us what you would do with a quantum computer.

[Julian Kelly]

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