OpenAI is ready to target free users of its services with advertisements around the web, based on what it knows about them.

On Thursday, OpenAI sent an email to users laying out major changes to the AI company’s privacy policy in the US. “We’ll now use cookies to promote OpenAI products and services on other websites,” reads the email sent on April 30. “This does not impact your conversations in ChatGPT. Your conversations with ChatGPT are private and are not shared with marketing partners.” Cookies store information in users’ browsers as they explore the web.

Chats with the bot aren’t shared with third parties. Even so, details OpenAI collects as users interact with its services may soon be used to market those same services, like ChatGPT, outside the platform. This appears to be targeted at converting free users (WIRED found that marketing settings were “on” by default) and seeing how effective its ads are at conversions.

The move comes as OpenAI looks to expand its own advertising network inside ChatGPT. The company started rolling out ads at the bottom of ChatGPT outputs for US users in February. Competitors including Google are exploring how ads can be woven into the user experience of generative AI tools and features.

“Nothing about our policy of not sharing people’s conversations or other private user content with advertisers has changed,” says OpenAI spokesperson Taya Christianson. “Like many companies, OpenAI works with select marketing partners to help people learn about our products on third-party websites and apps, and we updated our privacy policy to clarify how this works. We do not share your conversations with these marketing partners. To make OpenAI marketing efforts more relevant and measure their effectiveness, we may share limited identifiers, such as cookie IDs or device IDs, and users can opt out at any time in settings.”

To help you better understand what recently changed, WIRED compared the new privacy policy to a previous version saved from OpenAI’s website earlier this month. The biggest change revolves around how your data is shared for marketing purposes.

Courtesy of Reece Rogers

Data Usage Now Includes Third-Party Promotions

In the Disclosure of Personal Data section, OpenAI expanded the paragraph detailing how it discloses personal data. OpenAI now says it may share “limited information” with partners to promote services like ChatGPT and Codex off of OpenAI’s platforms.

The company details this change in a new help page. It says it might send identifiers, such as users’ email addresses or cookie IDs, to advertising platforms. That way, OpenAI can check whether users have taken specific actions—like signing up for its Codex tool after they get shown an ad for it on Instagram.

Users can opt out of this kind of tracking by going to Settings > Data Controls > Marketing Privacy on the ChatGPT site. WIRED tested two free accounts and found that those settings were on by default. The two paying accounts WIRED checked, one Plus and the other Enterprise, did not have it on by default.

Old Privacy Policy

We disclose your Personal Data in the following circumstances:

Vendors and Service Providers: To assist us in meeting business operations needs and to perform certain services and functions, we disclose Personal Data to vendors and service providers, including providers of hosting services, customer service vendors, cloud services, content delivery services, support and safety services, email communication software, web analytics services, payment and transaction processors, search and shopping providers, marketing service providers, and information technology providers. We also work with service providers who help us with age and identity verification, and you can learn more here⁠. Based on our instructions, these parties will access, process, or store Personal Data only in the course of performing their duties to us.

New Privacy Policy

We disclose your Personal Data in the following circumstances:

Vendors, Service Providers, and Marketing Partners: To assist us in meeting business operations needs and to perform certain services and functions, we disclose Personal Data to vendors, service providers, and marketing partners, including providers of hosting services, customer service vendors, cloud services, content delivery services, support and safety services, email communication software, web analytics services, payment and transaction processors, search and shopping providers, and information technology providers. We also work with service providers who help us with age and identity verification, and you can learn more here⁠⁠. When we work with Service Providers, these parties will access, process, or store Personal Data based on our instructions and only in the course of performing their duties to us. We also share limited information with select marketing partners who are not service providers in order to promote our products and services on third-party properties and help us assess the effectiveness of those efforts. Some of these partners may receive information through cookies and similar technologies. Learn more about these practices and the choices available to you here⁠.

Assurance About ‘Sensitive Personal Data’ Removed in Error

OpenAI categorizes many different types of information as a user’s “Personal Data,” including birth dates, payment information, and any prompts a user might have written. In its privacy policies, it doesn’t explain which types of this data it considers “sensitive,” but OpenAI does promise that it doesn’t use this information to infer characteristics about consumers.

A sentence regarding “sensitive Personal Data” was briefly absent from the Privacy Policy on Friday as WIRED accessed the updated document. When WIRED reached out to OpenAI for comment, the company claimed this removal was an error and added a similar sentence back, in a different paragraph.

Looking for the most recent regular Connections answers? Click here for today’s Connections hints, as well as our daily answers and hints for The New York Times Mini Crossword, Wordle and Strands puzzles.

Today’s Connections: Sports Edition features a mix of difficulty. If you’re struggling with today’s puzzle but still want to solve it, read on for hints and the answers.

Connections: Sports Edition is published by The Athletic, the subscription-based sports journalism site owned by The Times. It doesn’t appear in the NYT Games app, but it does in The Athletic’s own app. Or you can play it for free online.

Read more: NYT Connections: Sports Edition Puzzle Comes Out of Beta

Hints for today’s Connections: Sports Edition groups

Here are four hints for the groupings in today’s Connections: Sports Edition puzzle, ranked from the easiest yellow group to the tough (and sometimes bizarre) purple group.

Yellow group hint: Steel City sports.

Green group hint: Baseball info.

Blue group hint: She shoots, she scores!

Purple group hint: Giddy up!

Answers for today’s Connections: Sports Edition groups

Yellow group: A Pittsburgh athlete.

Green group: Seen on an MLB scorebug.

Blue group: Teams in the PWHL playoffs.

Purple group: Horse racing Triple Crown winners.

Read more: Wordle Cheat Sheet: Here Are the Most Popular Letters Used in English Words

What are today’s Connections: Sports Edition answers?

The yellow words in today’s Connections

The theme is a Pittsburgh athlete. The four answers are Panther, Penguin, Pirate and Steeler.

The green words in today’s Connections

The theme is seen on an MLB scorebug. The four answers are count, inning, outs and score.

The blue words in today’s Connections

The theme is teams in the PWHL playoffs. The four answers are Charge, Fleet, Frost and Victoire.

The purple words in today’s Connections

The theme is horse racing Triple Crown winners. The four answers are Affirmed, Citation, Justify and Whirlaway.

For years, Apple has been rumored to be bringing native touch functionality to the Mac. A new display gives us an early look at what that may be like, for better and worse.

Recently, I got an early look at the Aspekt Touch, a new monitor from Alogic. This isn’t the first touchscreen monitor from the brand, but the tilt functionality combined with macOS Tahoe gives early impressions about how a first-party solution could be implemented.

Feel free to check out Mike’s initial hands-on of the Aspekt Touch, but here’s the high-level. It’s a 32-inch 4K display that is also able to house a Mac mini in the bottom of the stand, and it can tilt nearly flat to be used more comfortably as a touchscreen.

A skeptic, early

I’m conflicted about the idea of a touchscreen Mac. I’ve been a detractor for ages, agreeing with Apple’s official stance that the iPad is the best touchscreen computer.

Aspekt Touch tilted back

By and large, I haven’t felt the need for a touch interface on my Mac. Recently, though, that’s started to change.

I’ve gone from using my iPad and the Magic Keyboard over to my Mac and inadvertently kept poking at the display. If the iPad can get trackpad functionality, why can’t we get supplemental touch functionality on the Mac?

After a lot of thought, I think what matters is the approach. Based on current rumors, that approach could be what sets it apart.

Over on iPad, it is designed as touch first, with cursor support added for certain users when it makes sense. On the Mac, it will still be cursor first, with touch added as a supplemental interaction method.

Magic Keyboard for iPad Pro

During Windows’ push toward touch-first design, the UI was watered down to accommodate it. The result was a hodgepodge interface that felt smashed together, inconsistent, and didn’t seem to work well.

As long as macOS remains macOS, I think there could be some potential here, and it has been fun to explore with the Aspekt Touch.

Aspekt Touch monitor brings touch to macOS, with caveats

Alogic provides a simple driver package to add touch support to the Mac. You download the installer and grant it a few permissions, and you’re ready to go.

Alogic’s software to enable and customize the touch controls

Once done, I could just start tapping away on the large 32-inch screen. I could scroll through Safari, zoom by pinching in and out, and even initiate a right-click.

Using the stylus was a solid experience, too. Any capacitive stylus will work, but Alogic has its own with some extra features.

Hover support on the Alogic stylus

The stylus supports hover effects, so as I work in Affinity, I can see tooltips appear over the different tools. When you flip the stylus around, you can use the other side as an eraser to erase what you’ve drawn.

The stylus supports varying degrees of pressure, and I didn’t seem to have any issues with palm rejection.

Zoom in and out by pinching in Safari

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When you dig into the Alogic app, you can fine-tune your experience. You can customize the touch effects on a per-app basis to get very granular in how you interact with macOS.

Overall, it’s a solid experience for being added with a third-party plugin. However, a native experience would need to go even further.

Liquid Glass arrives in macOS Tahoe

The problem with the non-native experience is that it’s cobbled together piecemeal from different existing macOS features. There’s no native touch layer that works universally, and many UI elements aren’t designed for touch.

The magnifier effect

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For example, when using the zoom feature, many times it just initiates the magnifier from the accessibility settings. This gets the job done, sure, but not in the way I expected.

I also struggled tapping certain elements, like when editing in Affinity or Pixelmator. The sheer number and size of items made it hard to tap the exact one, especially if I was trying to move with any degree of urgency.

Liquid Glass is easy to touch

My biggest takeaway was how great Liquid Glass was. The UI elements that were skinned with Liquid Glass were easier to tap and felt more natural.

This offers an early glimpse of how touch functionality might be implemented. Liquid Glass may be divisive, but it suggests a more consistent cross-platform experience, and that includes touch support.

I’d also love to see native support for Apple Pencil. I don’t draw, but I do edit a lot of photos, and Apple Pencil is great for getting that done on iPad.

The Alogic stylus still has lag when drawing or writing

The Alogic stylus has noticeable lag, which is hardly ideal. I’d like to think that an Apple first-party implementation wouldn’t have that issue, just as it doesn’t on iPad.

Other Apple Pencil features could also debut, like the squeeze gesture to open up a tool palette or maybe something specific for Mac. I’d love it if I could squeeze the Apple Pencil Pro and see a collection of my favorite shortcuts to quickly run.

Probably not a 2026 experience

My biggest concern is that if touch is added, it needs to complement macOS. It shouldn’t try to replace what’s already there.

At the moment, it appears the first touchscreen Mac will be the redesigned M6 OLED MacBook Pro. Clearly, a keyboard and trackpad will be front and center to that experience.

Touching macOS Tahoe

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That means we won’t be getting an iPad form factor running macOS, at least any time soon. I think that’s a good thing, but opinions vary amongst the AppleInsider staff, given that the Magic Keyboard with trackpad exists.

We’ll likely have to wait a bit longer to see though, as recent rumors say Apple’s redesigned MacBook Pro, first slated for the end of 2026, is now likely going to ship in early 2027. This isn’t because of developmental reasons, but rather component shortages that are plaguing the industry.

I’m still a bit skeptical here on whether macOS needs touch support or not. After using it for the last couple of weeks, I’m at least leaning towards more “for” than “against” at the moment.

Maybe we’ll get a clearer picture come WWDC with the preview of macOS 27. We’ll find out soon.

Musely, a direct-to-consumer telemedicine platform, has secured over $360 million in non-dilutive capital from General Catalyst’s Customer Value Fund (CVF).

The company specializes in compounded treatments for skin, hair, and menopause care. Musely co-founder and CEO Jack Jia told TechCrunch that when CVF investors reached out to him last year, he wasn’t looking to raise capital.

That’s because Musely, which was founded in 2014 as a wellness community before pivoting to prescription skincare in 2019, has been cash flow positive for years, he said. Jia didn’t want to reduce his ownership in the company by selling off a chunk of it to VCs. They frequently approached him about a potential round and he consistently turned them down, he said.

But unlike traditional venture capital, CVF wasn’t looking to take an equity stake, nor was it offering a loan that would carry interest rate charges. Instead, CVF’s alternative financing is similar to a tiny revenue-share agreement: Companies with predictable revenue streams borrow capital, and then repay the funds along with a fixed, capped percentage of revenue it generates from the use of General Catalyst’s fund.

Although Jia was initially skeptical, he quickly realized CVF’s terms were more favorable than a standard bank loan and far less costly than a dilutive equity round.

“When I mathematically modeled it, I found this absolutely compelling,” he said.

While Musely has been growing its revenue on average 50% year-over-year and has served over 1.2 million patients, acquiring new customers for DTC brands like Musely can be very costly, Jia explained. “When you become a billion-dollar revenue company, you need another billion in order to grow to the next billion,” he said. “That’s why most of the DTC companies, if you look at the capital burn, it is huge.”

The funding from CVF solves this problem, providing Musely with a capital war chest to support its customer growth. The funding will support sales, marketing, and other customer acquisition efforts.

Musely joins a CVF portfolio that includes Grammarly, Lemonade, and Ro. The fund maintains its own distinct limited partners, and the capital it invests was not included in General Catalyst’s last $8 billion fundraise.

Unlike many of its peers, Musely has been remarkably capital-efficient. After raising $20 million from DCM and other investors in 2014, the company has not raised a single dollar of equity capital since, according to Jia. Musely allows patients to access prescription products through asynchronous consultations with board-certified dermatologists and OB-GYNs.

Enterprise AI teams are hitting a wall — not because their models can’t reason, but because the workflows underneath them were never built for agents. Tasks fail, handoffs break, and the problem compounds as organizations push agents deeper into back-office systems. A new architectural layer is emerging to address it: workflow execution control planes that impose deterministic structure on processes agents are expected to run.

One of the companies bringing this to the forefront is Salesforce, with a new workflow platform that turns back-office workflows into a set of tasks for specialized agents to complete. Users can upload their processes or use one of the set Blueprints provided by Salesforce, and Agentforce Operations will break it down for agents. 

Salesforce senior vice president of Product, Sanjna Parulekar, told VentureBeat in an interview that the problem is that many enterprise workflows are not built for agents. “What we’ve observed with customers is that a lot of times, the brokenness in a process is probably in your product requirements document,” Parulekar said. “So when that’s uploaded into a product, it doesn’t quite work. We can optimize it and cut out some things and replace it with an agent.”

Without this control panel layer, enterprises could risk deploying agents that increase cost rather than fix their workflow problems.

Making the workflow work for agents, not just humans

Enterprises deploying agents are learning a costly lesson: Their workflows were designed around human judgment gaps, not machine execution. Processes that evolved through years of workarounds — loosely defined steps, implicit decisions, coordination that depends on individuals knowing what to do next — break when agents are asked to follow them literally.

Even with all of an enterprise’s context at its fingertips, AI systems will have difficulty completing tasks if it is not clear what it’s supposed to do. 

Parulekar said her team found that focusing on what makes the process tick and breaking it down into more explicit steps and workflows makes the system more deterministic. Then, when platforms like Agentforce Operations introduce agents, those agents already know their specific tasks.  

“It forces companies to rethink their processes and introduces observability into the mix because of the session tracing model in the system,” she said.

Parulekar said human checks can be built into the system, so the process is more transparent.

What makes this approach different from other workflow automation offerings is that it doesn’t rely on agents to decide what to do next; the system does. Unlike more traditional automation tools that route tasks and agents on probabilistic decision-making, this enforces execution on a more pre-defined, deterministic structure.

The problem it introduces

Codifying a workflow doesn’t fix a broken one. If a process has flawed steps, encoding it for agents locks in the problem at scale. And once workflows are distributed across agents, the challenge shifts from execution to governance: who owns the process, who validates it, and how it evolves when business conditions change.

It puts the onus on teams to take a hard look at what works for them and what doesn’t.

Organizations need to consider that, along with the execution control plane offered by platforms like Agentforce Operations, someone should be made responsible for task completion and success. 

Brandon Metcalf, founder and CEO of workforce orchestration company Asymbl, told VentureBeat in a separate interview that the key to both humans and agents following a workflow is a shared goal. 

“You have to understand the goal or the agent or human won’t complete the task successfully,” Metcalf said. “Someone has to manage that outcome that has to be delivered. It can be a person or an agent.”

The bottleneck has moved. As Metcalf framed it, the question is no longer whether agents can reason through a task, it’s whether the workflow underneath them is coherent enough to execute. For enterprises that built their processes around human judgment and institutional memory, that’s a harder fix than swapping in a smarter model.