Signal App’s Unusual Kind of Endorsement

Summary

WSJ Tech News Briefing: Signal App’s Unusual Kind of Endorsement
Presented by The Wall Street Journal
Release Date: March 26, 2025

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Introduction

In the March 26, 2025 episode of WSJ Tech News Briefing, host Victoria Craig delves into two prominent topics shaping the tech landscape: the rising prominence of the Signal messaging app among high-profile users, including senior White House officials, and Ford's innovative integration of artificial intelligence (AI) to expedite its car manufacturing process. This comprehensive episode provides insights into the security features of Signal and explores how AI is revolutionizing automotive engineering.

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Signal App: The Messaging Choice for High-Stakes Communication

Surge in Popularity and Controversial Endorsement

Victoria Craig opens the discussion by highlighting Signal's skyrocketing interest on mobile app stores following a report by The Atlantic that revealed senior White House officials used Signal to coordinate military operations, specifically plans to launch airstrikes in Yemen. This revelation has stirred controversy over the app’s adoption for sensitive government communications.

Understanding Signal’s Encryption

To demystify Signal for listeners unfamiliar with the app, Craig introduces WSJ tech reporter Sam Schechner, who converses with Moxie Marlinspike, the founder of Signal. Marlinspike explains:

“Signal is a chat app that works on your phone or your computer. It’s end-to-end encrypted, making it very popular with journalists, privacy-conscious individuals, and intelligence officials on their personal devices.” (01:50)

Marlinspike further elaborates on encryption:

“End-to-end encryption means your message is scrambled so only the recipient can read it. Even if intercepted, it remains gibberish.” (02:24)

He emphasizes the robustness of Signal's encryption algorithm, noting:

“They publish it as open source, and security experts say it has yet to be broken.” (03:16)

Security and Vulnerabilities

Schechner raises concerns about the safety of using Signal for sensitive communications, especially among government officials. Marlinspike responds:

“The algorithm itself is safe, as evidenced by WhatsApp using the same encryption. However, the vulnerability lies in the endpoints—your phone.” (03:35)

He clarifies that while Signal secures message content during transit, the device itself remains a potential weak point if compromised.

Signal’s Ownership and Data Privacy

Addressing ownership, Marlinspike states:

“Signal is owned by the Signal Technology Foundation, a nonprofit funded by grants and donations. This ensures they’re not looking to monetize user data.” (05:09)

He highlights Signal's commitment to privacy by retaining minimal metadata:

“We only provide the date an account was created and the last time it was used. No information on message content or communication patterns.” (06:33)

This approach significantly mitigates data exposure risks, even under governmental subpoenas.

Conclusion on Signal’s Credibility

Victoria Craig summarizes the segment by underscoring Signal's strong encryption and minimal data retention policies, making it a trusted choice for individuals and officials prioritizing secure communication.

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Ford's AI Revolution: Accelerating Car Manufacturing

Current Car Manufacturing Process

Transitioning from digital security, Craig introduces a segment on Ford's adoption of AI to streamline its car manufacturing. She contrasts the traditional process involving life-size clay models and extensive stress testing with AI-driven advancements.

AI in Design and Modeling

Reporter Isabel Bousquet sheds light on how AI is transforming the design phase:

“AI engines can take a 2D sketch and generate a 3D model, allowing designers to tweak elements like the roof and windows without the need for physical clay sculpting.” (08:27)

This innovation accelerates the initial design phase, although Ford still values the tactile feedback from clay models.

AI in Stress Testing

The integration of AI extends to engineering, where predictive models replace time-consuming physical stress tests:

“A single stress test run used to take 15 hours, but now an AI model can predict the outcomes in just 10 seconds.” (08:26)

This dramatic reduction in testing time enhances efficiency, enabling faster iterations and boosting competitiveness against rapid-developing Chinese automakers.

AI Platforms and Technology Partners

Ford leverages a variety of AI platforms to power these advancements:

“They’re using OpenAI, Google, Anthropic, Meta’s Llama, and the Deep SEQ model. Open source models like Deep SEQ are favored for their customization capabilities.” (09:56)

These platforms offer Ford the flexibility to tailor AI tools to their specific manufacturing needs.

Cost Management and Infrastructure Strategy

Addressing the financial aspect, Bousquet explains Ford’s strategy to manage the high costs of AI infrastructure:

“Ford is building its own data centers and purchasing Nvidia’s GPUs to avoid reliance on cloud providers, ensuring stable costs and immediate access to necessary computational power.” (10:17)

This in-house approach not only controls expenses but also grants Ford greater autonomy over its technological resources.

Conclusion on AI’s Impact at Ford

Victoria Craig concludes by highlighting how Ford’s strategic use of AI in both design and stress testing significantly reduces development time and costs, positioning the company to better compete in the fast-paced automotive market.

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Wrap-Up

In this episode, WSJ Tech News Briefing provides a deep dive into the security prowess of the Signal app and its controversial endorsement by White House officials. It further explores Ford’s cutting-edge use of AI to revolutionize car manufacturing processes. These discussions underscore the critical intersections of technology, security, and innovation shaping today's digital and industrial landscapes.

Produced by Jess Jupiter with supervising producer Emily Martosi. For more insights, stay tuned for the next edition of Tech News Briefing with TNB Tech Minute.

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Notable Quotes with Attributions:

• Moxie Marlinspike on Signal Encryption:
  “End-to-end encryption means your message is scrambled so only the recipient can read it. Even if intercepted, it remains gibberish.” (02:24)

• Moxie Marlinspike on Signal’s Safety:
  “They publish it as open source, and security experts say it has yet to be broken.” (03:16)

• Moxie Marlinspike on Data Privacy:
  “We only provide the date an account was created and the last time it was used. No information on message content or communication patterns.” (06:33)

• Isabel Bousquet on AI in Car Design:
  “AI engines can take a 2D sketch and generate a 3D model, allowing designers to tweak elements like the roof and windows without the need for physical clay sculpting.” (08:27)

• Isabel Bousquet on AI in Stress Testing:
  “A single stress test run used to take 15 hours, but now an AI model can predict the outcomes in just 10 seconds.” (08:26)

• Isabel Bousquet on AI Platforms:
  “They’re using OpenAI, Google, Anthropic, Meta’s Llama, and the Deep SEQ model. Open source models like Deep SEQ are favored for their customization capabilities.” (09:56)

• Isabel Bousquet on AI Infrastructure Strategy:
  “Ford is building its own data centers and purchasing Nvidia’s GPUs to avoid reliance on cloud providers, ensuring stable costs and immediate access to necessary computational power.” (10:17)

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This detailed summary encapsulates the key discussions and insights from the episode, providing a comprehensive overview for listeners and readers alike.

Transcript

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[Victoria Craig]

Welcome to Tech News briefing. It's Wednesday, March 26th. I'm Victoria Craig for the Wall Street Journal. Signal is the app for spies, journalists and apparently senior White House officials. What is it and is your data safe there? Then putting a car through a round of stress testing takes Ford about 15 hours. An AI trained prediction model though, takes just 10 seconds. We'll chat car making in the age of Artificial Intelligence first, if it's good enough for the White House, is it good enough for me? That seems to be the question many people are asking about the messaging app Signal. Interest has skyrocketed on mobile app stores since the Atlantic reported. Senior White House officials discussed plans on Signal to launch airstrikes in Yemen. Controversy has swirled around administration officials decision to use the app for military operations discussions. But if you're confused about what exactly Signal is and how secure it can be, WSJ tech reporter Sam Schechner has.

[Sam Schechner]

The answers for listeners who have never used it before, who have never heard of Signal until today. What is it used for?

[Moxie Marlinspike]

Signal is a chat app that works on your phone or your computer. Actually they have a desktop app. It's kind of like WhatsApp or iMessage. And it's encrypted. It's end to end encrypted. And so it's very popular with journalists like me for talking to, but also people who are privacy conscious, including intelligence officials on their personal devices. I can vouch from personal experience use Signal too.

[Victoria Craig]

And we'll get to the intelligence aspect of this, but just explain. First, for people who aren't necessarily familiar, what does encrypted messaging mean exactly?

[Moxie Marlinspike]

That's a great question because there's things it means and there's things it doesn't mean. What they use is something called end to end encryption. So it's encrypting your message in transit. So when you type something into the app on your phone, obviously you can see it. It's not encrypted. And then what the app does is it scrambles it in such a way that it can only be read by the other person's phone. And that scrambled message transfers along the Internet in that scrambled way, so that if somebody were to intercept it, which is easy to do on the Internet, it's gibberish. There's nothing to see. And that keeps your message private until it gets to the other person's phone, which unscrambles it. The way that signal scrambles your messages is pretty robust. They publish it as open source, and security experts say it has yet to be broken.

[Victoria Craig]

That's pretty incredible when you think about.

[Sam Schechner]

It, because so many messaging apps have been hacked before consumer data is all over the Internet. How do we know that, especially given the sensitivity of the discussions among these government officials, these top government officials, government officials at the White House. How do we know that it's safe?

[Victoria Craig]

Is it vulnerable to hacking?

[Moxie Marlinspike]

Signal? The algorithm itself is, according to experts, safe. And in fact, it's so safe that WhatsApp uses the same encryption algorithm. They use signals guts, basically, to do the end to end encryption of WhatsApp. The issue is that in order to be read, it has to be decrypted, right? Like on your device, it's not encrypted when you read it, it's in English or whatever language you speak. And likewise, when you type it in, it's not encrypted. And what's vulnerable are your phones, the endpoints. And that's the weak link when it comes to ending encryption. And that's why government officials aren't supposed to use personal devices to handle classified information, no matter what app they use. If your phone gets hacked, then, of course, the hackers can read what's on your phone.

[Sam Schechner]

So what do government officials use for this kind of communication?

[Moxie Marlinspike]

Usually, normally, conversations concerning classified military plans, like striking foreign targets, are supposed to only happen in what the US government calls Secure Compartmented Information Facilities, or SCIFs. And these are rooms that are specially designed to prevent conversations from being spied on. They have technical things about them that make it hard to be spied on, and they have secure communications inside. And you're not supposed to bring your cell phone inside that room because a phone can be hacked.

[Sam Schechner]

Walk us through who owns and operates Signal? Because that's also a question for users when they start using a new app, is who ultimately has access to my user data.

[Moxie Marlinspike]

Signal is owned by a nonprofit called the Signal Technology Foundation. So that doesn't necessarily tell you that much. It was started by a cryptographer, an entrepreneur named Moxie Marlinspike, who was very interested in private communications. And actually, the foundation was set up by Moxie, along with initial funding from WhatsApp's co founder, Brian Acton. And it's still run by that foundation, which is funded largely by grants and donations. What the foundation says is that that actually should give you some reassurance that they're not looking to monetize your data. And what Signal says is that they actually keep almost no metadata about what its users are doing on the app. And that's an important distinction because there are apps that are encrypted end to end, but that's the content of your message that's encrypted, not the fact that X phone number sent a message to Y phone number or X Internet address sent a message to Y Internet address. A company might actually have a network of who messaged who, when, and that tells an adversary a lot. Without even knowing the content of the messages, Signal doesn't keep any of that information. It's all purged. And so if they're hacked or if a government comes to them with a subpoena asking for information, they can only provide two pieces of information. They say the date an account was created and the last time it was used, but not when and where and to whom messages were sent.

[Victoria Craig]

That was Wall Street Journal tech reporter Sam Schechner. Coming up, from clay models to computer stress tests, we'll hear how Ford is speeding up its car making process thanks to artificial intelligence. That's after the break.

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[Victoria Craig]

Here's a good quiz night fact for you. Before we ever hop into the driver's seat of a brand new car, a life size clay model is first painstakingly sculpted by a designer. It's then passed on to engineers who run lengthy stress tests to make sure it's safe. At least that's how carmaking still originates at Ford. But now those same designers are getting a leg up from AI to cut down on development time. Wall Street Journal reporter Isabel Bousquet told me more about a recent conversation she had with the carmakers director of AI.

[Sam Schechner]

I was genuinely surprised, Isabel, to read in your story that Ford engineers actually create life size clay versions of their car designs before they ever begin the manufacturing process. The company's director of artificial intelligence has some ideas about how to make that entire process less time consuming and more efficient by leveraging AI.

[Victoria Craig]

Walk us through that.

[Isabel Bousquet]

These designers, they also really like to sketch, but the problem with a sketch is that it's two dimensional. And what some of these AI engines can do now is you can give it a two dimensional picture, a two dimensional sketch, and it can generate essentially a three dimensional model of a car. And from there you can continue to make tweaks to it, the roof, the windows, etc. But yeah, getting from the 2D to this fully formed 3D model without having to do the whole clay sculpting process does seem like it can speed things up. They do not want to get rid of clay totally. They still love being able to feel and see that the AI is basically just looking to accelerate some parts of the process here. Part of the reason it's taking them so long is because there's the design process where they're building the clay model of the car, they're figuring out what they want it to look like. And then there's also the engineering team then comes in and has to run stress tests. They're using AI models that essentially can predict some of how the car will react in those stress tests a lot faster than it would traditionally take to run the stress test. In the past, one run might take 15 hours, but now this AI model can predict what the output of the stress test will be in 10 seconds. Being able to speed that up a lot is really helpful for them. They're really looking for efficiency and speed right now, especially to compete with some of the Chinese automakers who are just rolling out new models really fast.

[Sam Schechner]

So what AI platforms is Ford leveraging?

[Isabel Bousquet]

They told me they're using the OpenAI models, the Google models, Anthropic. They really like open source models. So those include Meta's Llama model and the Deep SEQ model. In the past, companies have been kind of hesitant to use Deep seq. They do like it because it's open source, which means you can build and customize a lot.

[Sam Schechner]

On top of that, cost is always.

[Victoria Craig]

A factor in some of these new technological innovations. And these AI models are powered by graphics processing units or GPUs. Brian Goodman told you that the company uses Nvidia's chips. But cost, of course, is a hurdle to that. And I love the way he characterized it because he compared it to trying to get Taylor Swift tickets. We had Nvidia'S developer conference recently and they unveiled a whole new slate of chips. So how is Ford thinking about the need to use those chips?

[Isabel Bousquet]

Ford's strategy is essentially to build its own data centers and buy its own GPUs, and it's been doing that for a while. Ford has been coming to this Nvidia conference for the last 10 years. They have a close relationship with Nvidia and they've been buying these Nvidia chips and filling their own data centers with them. And I think they feel like that gives them the opportunity to not be reliant on the cloud providers. They don't have to wait for that capacity. They don't have to worry about what that capacity might cost today versus what it might cost tomorrow. They sort of have their set costs and, yeah, they're continuing to buy GPUs and build out that infrastructure.

[Victoria Craig]

That was WSJ reporter Isabel Bousquet. And that's it for Tech News Briefing. Today's show was produced by Jess Jupiter with supervising producer Emily Martosi. I'm Victoria Craig for the Wall Street Journal. We'll be back this afternoon with TNB Tech Minute. Thanks for listening.