Siri’s Second Act

Summary

WSJ Tech News Briefing – Episode Summary
Episode Title: Siri’s Second Act
Date: June 5, 2026
Host: Imani Moise
Guests: Rolf Winkler (WSJ Apple Reporter), Ben Cohen (WSJ Columnist)

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Episode Overview

This episode explores Apple's ambitious efforts to revitalize Siri and compete in the growing field of AI assistants, just days ahead of the 2026 Worldwide Developers Conference (WWDC). The show also examines a landmark AI breakthrough in mathematics, with OpenAI’s model solving an 80-year-old problem, and discusses the larger implications of AI’s evolution in hard sciences.

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Key Discussion Points & Insights

1. Apple’s “New Siri” and the AI Arms Race

[00:19 - 05:52]

Is Apple Too Late for AI Dominance?

• Apple has fallen behind industry leaders like Google and OpenAI in AI assistant technology, with Siri often considered outdated.
• Despite this, Apple retains a strong consumer base:
  • Rolf Winkler (01:51):

    “As dumb as Siri has been the last couple years, has anyone traded in their iPhone for an Android because it's got some better AI features that Google has come out with? … If Apple can finally create a Siri that is your guide to this AI world, this could flip.”

The Privacy Paradox

• Apple’s longstanding commitment to privacy distinguishes it from competitors but also creates AI development challenges:
  • Pro: Trusted by consumers, stores sensitive personal data locally.
  • Con: Limits data available for AI training, hampering rapid improvement.
  • Rolf Winkler (02:53):

    “Privacy is something they take so seriously internally, it can hamstring some of their engineers who need data to train AI models. … To train models to make good AI, you need data. And Apple doesn't have as much as you think it might because it doesn't see a lot of the data that it has.”

Economic Implications of AI on Smartphones

• AI agents may fundamentally change how we interact with apps and the economics of the app ecosystem:
  • If Siri becomes the central “AI agent,” it could serve as a gatekeeper, or “toll booth,” between users and app/service providers.
  • Rolf Winkler (04:08):

    “If they reengineer Siri … Apple will be the toll collector at the front of that on-ramp and could make quite a bit of money.”

Apple’s Partnership with Google: Gemini AI as Siri’s Brain

• Apple’s new Siri will be powered by Google’s Gemini AI model, a technical collaboration reminiscent of their current partnership on web search. This underscores Apple’s need to rapidly “catch up” in AI.
  • Rolf Winkler (05:13):

    “Apple desperately needs to modernize Siri, it can't on its own. … They need Google and Google Technology Gemini to really pull Siri into the future.”

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2. AI’s Mathematical Breakthrough: The Unit Distance Problem

[06:38 - 11:58]

What is the Unit Distance Problem?

• An 80-year-old mathematical conundrum: For n dots placed on a plane, how many pairs can be exactly one unit apart?
  • Ben Cohen (07:31):

    “At its core it's simply like if you imagine that you are staring on a sheet of paper and you put N … dots on a sheet of paper, how many … can be exactly one unit apart.”

How AI Cracked It

• OpenAI’s model synthesized knowledge from disparate mathematical domains—combinatorial geometry and algebraic number theory—to find a novel solution.
  • Solution is so complex it cannot be visualized conventionally.
  • Ben Cohen (08:30):

    “It required the AI to synthesize instead of specialize. … AI can use its access to all the mathematical information and knowledge in the history of humanity to spot connections that humans with our own eyes cannot see.”

The Process Behind the Proof

• The solution was generated autonomously, with no human suggestions or nudges.
  • The AI’s “chain of thought” is 75,000 words.
  • Initial reaction from OpenAI’s own mathematicians: disbelief—prompting thorough error-checking before external verification.
  • Ben Cohen (09:31):

    “It did it completely autonomously, no engineers or human intervention involved. … [The OpenAI researchers] thought it was, like, so impossible to believe that they kind of didn't believe it.”

Mathematicians’ Response

• Widespread astonishment and endorsement from respected (and typically skeptical) mathematicians.
  • Ben Cohen (10:41):

    “Everyone is super impressed. … When [nine prominent mathematicians] endorsed it, that’s when it got my attention.”

What This Means for AI’s Future

• AI is now demonstrating “creativity and intuition” in formal domains like mathematics—suggesting it could make significant advances in other fields.
  • Ben Cohen (11:21):

    “It is getting much smarter in very specific fields. … But this is also like a solution that required creativity and intuition and the things that we don't normally associate with AI. … It shows that AI is obviously getting smarter … in ways that maybe we wouldn't have expected or couldn't have imagined. And I think that is also terrifying and thrilling and all of the things all at once.”

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Notable Quotes & Memorable Moments

• Rolf Winkler (01:51):

  “If Apple can finally create a Siri that is your guide to this AI world, this could flip.”

• Rolf Winkler (04:08):

  “Apple has become a toll booth for the online world.”

• Ben Cohen (08:30):

  “AI can use its access to all the mathematical information and knowledge in the history of humanity to spot connections that humans with our own eyes cannot see.”

• Ben Cohen (11:21):

  “It shows that AI is obviously getting smarter. … It is also getting smarter in ways that maybe we wouldn’t have expected or couldn’t have imagined. And I think that is also terrifying and thrilling and all of the things all at once.”

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Timestamps for Important Segments

• 00:19 – 05:52: Apple, Siri’s overhaul, and the AI arms race (with Rolf Winkler)
• 06:38 – 11:58: AI’s breakthrough in math: unit distance problem and its implications (with Ben Cohen)

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Overall Tone & Style

• The episode balances a mix of expert analysis and accessible explanation, blending tech industry commentary with light, conversational language. Imani Moise keeps the tone informative yet lively, making even the discussion of dense math problems approachable for a general audience.

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This summary provides a clear overview and highlights the major insights and moments from the June 5, 2026 episode of WSJ’s Tech News Briefing.

Transcript

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[Imani Moise]

welcome to Tech News Briefing. It's Friday, June 5th. I'm Imani Moiz for the Wall Street Journal. Apple is preparing to unveil a new Siri, but will it be enough to catch up in the race for AI Domina? We're breaking down the company's latest strategy ahead of its worldwide Developers conference next week and whether investors will buy it then. An AI model has solved a math problem that's puzzled some of the world's brightest minds for 80 years. We'll dive into why the breakthrough has some experts rethinking what AI is capable of. But first, for decades, Apple has been synonymous with innovation in Silicon Valley. But when it comes to AI, the company is starting to look old school. While rivals like Google and challengers like OpenAI have spent the past few years racing to build smarter chatbots and AI assistants, Siri has become something of a punchline. Uh huh, Nobody was talking to you, Siri. But that may be about to change. Apple is making the case that their chatbot can change the way consumers interact with AI. Kind of like how the iPhone changed how we interact with the Internet. We'll get a clearer picture of that strategy on Monday during the WWDC keynote, where Apple is expected to introduce a new version of Siri built on top of Google's Gemini AI model. WSJ Apple reporter Rolf Winkler joins me now to explain. Apple is behind in this AI arms race, but the company says it still has a path forward to winning in the AI space. How is that possible?

[Rolf Winkler]

That's what's fascinating about this. As far behind as Apple is in AI, there's an argument that is made by Wall street analysts by some people who've left Apple. Why? Because we all still use iPhones. If OpenAI wants to reach people with ChatGPT, it has to go through Apple. All of these companies long term still today have to go through Apple. As dumb as Siri is has been the last couple years, has anyone traded in their iPhone for an Android because it's got some better AI features that Google has come out with? There's certainly no mass defections. So if Apple can finally create a Siri that is your guide to this AI world, this could flip.

[Imani Moise]

If you have an iPhone, Apple probably knows a lot about you. And having an AI agent that can access all of the personal information in your phone. Probably sounds exciting to some people and horrifying to others. How does that feature mesh with Apple's stance on data privacy?

[Rolf Winkler]

Well, this is where it may be an advantage and a handicap. The advantage is Apple is known for its stance on privacy. It's not selling your information to advertisers, for instance, the way Google and Facebook do. That's not Apple's business model. In fact, privacy is something they take so seriously internally, it can hamstring some of their engineers who need data to train AI models. The information you have, you're sharing with your iPhone and only with your iPhone. And even Apple doesn't see it. So it's an advantage for Apple because they have this trust with their consumers already. We already give all our information to the iPhone. What if it could use all these things on the device without sending it to the cloud in a way that brings AI to us? A smartphone becomes your smart assistant in a way that it isn't yet. But as I mentioned, it cuts both ways because to train models to make good AI, you need data. And Apple doesn't have as much as you think it might because it doesn't see a lot of the data that it has. So this is a perpetual struggle.

[Imani Moise]

If AI agents become the primary way people interact with apps, how does that change the economics of smartphones?

[Rolf Winkler]

Apple has become a toll booth for the online world. Right when you want to download an app and sign up for a subscription, Apple takes a cut. When you do a search in the Safari browser, Apple gets a ton of money from Google. The point is Apple has the consumers, they use its device, which means if you want to reach them, you got to go through Apple and they take their cut. Now, in an AI powered world, if we abstract the apps away, if what the smartphone is is just the chatbot, or if it's somebody we're just talking to and we say, hey, Siri, book me a car going home. Maybe you're not opening the Uber app, but you're certainly using the Uber service. Uber's gonna have to pay to reach those customers in a different way potentially. So you can see how if they re engineer Siri, if it is the smart assistant that basically is the on ramp to this AI enabled world, Apple will be the toll collector at the front of that on ramp and could make quite a bit of money.

[Imani Moise]

And what about Google? How does their partnership with Apple work?

[Rolf Winkler]

Google's an interesting case. Google is going to, just like they work with Apple in search, they're going to work with Apple on AI. So this new Siri that's powered by Google, Google is the back end. As much as Apple desperately needs to modernize Siri, it can't on its own. It just doesn't have the capability. So they need Google and Google Technology Gemini to really pull Siri into the future. Maybe over time they'll have their own solution, but in the meantime they just got to have something and so Google's going to work with them. The economics of that are yet to be determined, but you could see them working together maybe for a long time, maybe the way they do.

[Imani Moise]

In Search that was WSJ reporter Rolf Winkler. Will you use the new Siri? If you're a listener on Spotify, leave us a comment with what you'll outsource to an AI assistant and and what you won't Coming up, A problem that has stumped the greatest mathematicians in the world for nearly a century has a solution at last. How AI finally cracked it. That's after the break.

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[Imani Moise]

AI may have finally won over one of academia's most proof hungry groups, mathematicians. Just a few weeks ago, an OpenAI model solved a problem that has confounded researchers for more than 80 years. It's known as the unit distance problem. And don't worry, we're not about to turn this into a math podcast. What's important to know is that some experts are calling this the first genuine AI breakthrough in advanced mathematics and evidence that AI may be capable of making discoveries on its own. Wall Street Journal columnist Ben Cohen joins me now to explain how we got here and what it tells us about where AI might go next. I like numbers as much as the next finance nerd, but the equations at the top of your story did make my eyes glaze over a little bit. For those of us who haven't thought about algebra since college, how would you explain the unit distance problem? Like how complex is it?

[Ben Cohen]

The actual problem is not really all that difficult. In fact, it is known as like the best known and the simplest to explain problem in high level math. At its core it's simply like if you imagine that you are staring on a sheet of paper and you put N as in any number of dots n number of dots on a sheet of paper, how many how many pairs of those dots can be exactly one unit apart. And OpenAI's model found an arrangement that actually does much better. And it's more complicated to explain than just, like, a sheet of paper and a grid. In fact, it's so complicated that it can't really be visualized on a sheet of paper or on any of our screens. And it is also so complicated that mathematicians who spend their time thinking about this stuff couldn't come up with it for 80 years. But the important thing to know is that an AI model did come up with it, and it was a little bit more complex than what the question sounds like.

[Imani Moise]

So what did humans miss when trying to solve this problem?

[Ben Cohen]

It's a really good question, in part because the answer applies far beyond math to fields that AI is coming for next. This is, like, a really highly counterintuitive solution to this problem. It required the AI to synthesize instead of specialize. And so AI can use its access to all the mathematical information and knowledge in the history of humanity to spot connections that humans with our own eyes cannot see. And so this particular problem required both combinatorial geometry and algebraic number theory, neither of which I know anything about, but the AI knows everything about it. So by synthesizing those two fields, it was able to come up with this solution that mere humans were not.

[Imani Moise]

And how did the model come up with this answer? Was there an engineer prompting it to think of it from different angles, or did it do it more independently?

[Ben Cohen]

It did it completely autonomously, no engineers or human intervention involved. OpenAI says. So you can actually read, if you're curious, the entire chain of thought of this model. I should warn you that it's about 75,000 words, which is about the length of the first Harry Potter book. So it's not exactly like easy reading, but you can see exactly how the model thought about this problem and every false start and path that it went down before it finally came up with this solution. So finally it comes up with this solution, and it flags it to the humans. And the humans at OpenAI who took a look, many of whom are like trained mathematicians themselves who work for schools and are currently on leave working for OpenAI, they thought it was, like, so impossible to believe that they kind of didn't believe it. They went looking for errors and they tried to hunt down the mistakes in this proof, and only when they couldn't find one did they show it to external mathematicians for proper verification. So it really says something that it was so surprising and kind of so inconceivable that even the people who had sort of set these models loose on this exact problem, couldn't quite believe it themselves.

[Imani Moise]

So what has the response or reaction been like within the mathematics community?

[Ben Cohen]

Everyone is super impressed. And these are people who are not easily impressed. I mean, I should say that, like I've written a bunch of columns about mathematicians in the past few years and these are people who are like severely allergic to hype. They require proof for basically everything in life, much less like claims about novel breakthroughs. And they would kind of rather like eat their calculators than vouch for shoddy work. So I was really surprised when this paper and proof came out. OpenAI included remarks from nine prominent mathematicians, like really big names in the field. And when they endorsed it, that's when it got my attention.

[Imani Moise]

Last question. What does this say about where AI is headed?

[Ben Cohen]

It is getting much smarter in very specific fields. Math has lent itself to being AI ified. I think almost like coding has. It is logical and it's discreet and it's exactly the sort of thing that AI is really good at. But this is also like a solution that require creativity and intuition and the things that we don't normally associate with AI. So I think it shows that AI is obviously getting smarter. We all know that it's also getting smarter in ways that maybe we wouldn't have expected or couldn't have imagined. And I think that is also terrifying and thrilling and all of the things all at once.

[Imani Moise]

That was WSJ columnist Ben Cohen. And that's it for Tech News Briefing. If you're a listener on Spotify, be sure to leave us a comment. Today's show was produced by Julie Chang. I'm your host, Imani Moise. Jessica Fenton and Mike Lavalle wrote our theme music. Our supervising producer is Katie Ferguson. Our development producer is Aisha Al Muslim. And Chris Sinsley is deputy editor of audio for the Wall Street Journal. We'll be back later this morning with TNB Tech Minute. Thanks for listening.

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