Apple Adds Matter Support for Robot Vacuums in iOS Beta

Matter Support for Robot Vacuums Confirmed

As spotted by 9to5Mac, Smart Home Centre confirmed the functionality using a Switchbot S10, which offers its own beta support for Matter. (Switchbot first added Matter robot vacuum support last year, but it required a hub and was kind of a hack.)

Features of Matter Support for Robot Vacuums

Apple Home screenshots shared in the story show the robot vacuum’s Home widget (complete with a little robot vacuum glyph) along with a control screen featuring a start / stop button, options for choosing between “Vacuum” and “Vacuum and Mop,” selections for operating modes like “Quiet” or “Deep Clean.” There’s also a “Send to Dock” option, although Smart Home Centre notes that this only paused the S10.

Adding Robot Vacuums to Automations and Scenes

Robot vacuums in the new iOS beta can also be added to automations and scenes. You can see how all of it works in the outlet’s video below.

Current State of Matter Support in Robot Vacuums

Apple was expected to add Matter support for robot vacuum cleaners last year, but that didn’t materialize. Few robot vacuum companies offer Matter support at the moment, and some of those are still waiting on a firmware update to enable it.

Confirmed Robot Vacuums with Matter Support

Robot vacuum makers have confirmed to us that these models will support Matter:

Conclusion

The addition of Matter support for robot vacuums is a significant step forward in the smart home ecosystem. With this feature, users will have more control over their robot vacuums and be able to integrate them seamlessly with other smart devices.

Frequently Asked Questions

Q: What is Matter?
A: Matter is a new smart home protocol that allows different devices to communicate with each other and work together seamlessly.

Q: Which robot vacuums will support Matter?
A: Robot vacuum makers have confirmed that the following models will support Matter: [list of models].

Q: How do I add a robot vacuum to my automation and scenes?
A: You can add a robot vacuum to your automation and scenes by going to the Apple Home app and following the prompts.

Q: Is Matter support exclusive to iOS?
A: No, Matter support is not exclusive to iOS. It will be available on other platforms as well.

Debates over AI Benchmarks Spill into Public View

Debates over AI benchmarks and how they’re reported by AI labs are spilling out into public view. This week, an OpenAI employee accused Elon Musk’s AI company, xAI, of publishing misleading benchmark results for its latest AI model, Grok 3. One of the co-founders of xAI, Igor Babushkin, insisted that the company was in the right.

The Dispute

The truth lies somewhere in between. xAI’s graph showed two variants of Grok 3, Grok 3 Reasoning Beta and Grok 3 mini Reasoning, beating OpenAI’s best-performing available model, o3-mini-high, on AIME 2025, a collection of challenging math questions from a recent invitational mathematics exam. However, OpenAI employees pointed out that xAI’s graph didn’t include o3-mini-high’s AIME 2025 score at "cons@64."

What is Cons@64?

Cons@64, short for "consensus@64," gives a model 64 tries to answer each problem in a benchmark and takes the answers generated most frequently as the final answers. This tends to boost models’ benchmark scores, and omitting it from a graph might make it appear as though one model surpasses another when in reality, that’s not the case.

A More Accurate Picture

Grok 3 Reasoning Beta and Grok 3 mini Reasoning’s scores for AIME 2025 at "@1" fall below o3-mini-high’s score. Grok 3 Reasoning Beta also trails ever-so-slightly behind OpenAI’s o1 model set to "medium" computing. Yet, xAI is advertising Grok 3 as the "world’s smartest AI."

A Neutral Party’s Take

A more neutral party in the debate put together a more "accurate" graph showing nearly every model’s performance at cons@64. As Twitter user Teortaxes pointed out, "Hilarious how some people see my plot as an attack on OpenAI and others as an attack on Grok while in reality it’s DeepSeek propaganda."

The Importance of Transparency

As AI researcher Nathan Lambert noted, the most important metric remains a mystery: the computational (and monetary) cost it took for each model to achieve its best score. This just goes to show how little most AI benchmarks communicate about models’ limitations – and their strengths.

Conclusion

The debate over AI benchmarks highlights the need for transparency and clear communication in the AI community. As the field continues to evolve, it’s essential to ensure that benchmark results are accurately reported and that model comparisons are made on a level playing field.

FAQs

Q: What is cons@64?
A: Cons@64, short for "consensus@64," gives a model 64 tries to answer each problem in a benchmark and takes the answers generated most frequently as the final answers.

Q: Why is cons@64 important?
A: Cons@64 tends to boost models’ benchmark scores, and omitting it from a graph might make it appear as though one model surpasses another when in reality, that’s not the case.

Q: What is the most important metric in AI benchmarking?
A: The most important metric remains the computational (and monetary) cost it took for each model to achieve its best score.

The Luigi Hearing: A Study in Cultural Obsession

There are so many people here that nobody can tell where the end of the line is. New people arrive, ask if there’s a line, shuffle into a blob of bodies idling and waiting for someone to give them instructions. The hallway is horribly warm — unclear if it’s from the bodies or the heat — and it’s a little smelly, which could just be me but I don’t think it is. I estimate between 100 and 150 people are hanging around, waiting for 2:15PM to roll around, their anticipation building. This is not a club with a strict bouncer, though it feels like it. This is the Luigi Mangione hearing.

A Minor Pre-Trial Status Update

The hearing is a relatively minor pre-trial status update, but for the people most tapped in, there is a lot riding on it — the Luigi info-drip has been a bit dry lately. Court dates for the 26-year-old accused of murdering UnitedHealthcare CEO Brian Thompson in December keep getting pushed back. Mangione, who is currently being held in federal custody in a Brooklyn jail, has not made a public appearance since before Christmas. (Mangione is accused of gunning down Thompson in December outside a Midtown Manhattan hotel, and has pleaded not guilty.) On TikTok, commenters regularly complain that they haven’t seen Luigi on their For You page in months. When Mangione’s legal team launched a new website with updates on the case, a flood of donations came pouring into his legal fund — more than half a million dollars as of this writing.

A Study in Contrasts

Everyone involved understands that this case is unique: there are the many officers patrolling the hallway to keep us in check, like we are kids waiting to be seen by the principal; the hordes of people, some of whom live in the city and some of whom flew in for the occasion, trying to make sense of what’s about to happen; the members of the media who are just as gobsmacked and wide-eyed, angling to get a good view.

The Press Line

The media frenzy inside the Manhattan courthouse, with press corralled into their own line. Illustration: Molly Crabapple for The Verge

The Cultural Impact of a Tragic Event

In a way, Thompson’s death and Mangione’s fate are two sides of the same wretched coin. Both men have become symbols of an industry that has brought about so much pain — and generated so much profit — that people on both sides of the equation are willing to kill or die for it. And just as the cultural impact of his death has completely obscured who Thompson was as a person (and in many cases, that he was a person at all), so has Mangione’s beatification obfuscated the cold hard reality of a young man — cuffed, chained, and held without bail — who has pleaded not guilty to the murder that has made him an American icon.

The Cycle of Obsession

As he sits in prison, his photos go viral. TikToks and Reels blow up, new jokes and songs and memes are constructed every second. But then the content mills will finish grinding out what they can from the twenty minutes of Luigi the public got on Friday afternoon. The Luigi references on the For You pages will start drying up or get content-moderated out of sight; the die-hards will once again voice suspicions about the Narrative. And when Mangione and his attorneys next return to court, it’ll happen all over again: the crowds, the media, the police, the protest, the green sweaters, the memes, the livestreams, the thinkpieces and the outrage bait, a cultural engine that is ready to roar back to life the moment we catch a glimpse of Luigi Mangione once more.

Conclusion

The Luigi hearing is a case that has captured the public’s imagination, and it will likely continue to do so for the foreseeable future. As we wait with bated breath for the next update on Mangione’s case, it’s worth taking a step back to consider the cultural impact of this tragic event.

Frequently Asked Questions

Q: Who is Luigi Mangione?
A: Luigi Mangione is the 26-year-old accused of murdering UnitedHealthcare CEO Brian Thompson in December.

Q: What is the current status of the case?
A: The case is ongoing, with court dates being pushed back and Mangione being held in federal custody in a Brooklyn jail.

Q: Why is there so much attention surrounding the case?
A: The case has captured the public’s imagination, with many people fascinated by the details of the crime and the subsequent investigation. The case has also sparked controversy and debate, with some people questioning the handling of the case and others defending the accused.

Q: What is the significance of the "Luigi" nickname?
A: The nickname "Luigi" has become a meme and a cultural phenomenon, symbolizing the accused’s notoriety and the public’s fascination with the case.

Transcript of "Hard Fork" Episode

Kevin Roose: I’m having quite a morning. I was on the train today, got off, went up the escalator at Embarcadero, and someone bumped into me and knocked my phone out of my hand and onto the platform below. I thought, "Well, I’m midway up the escalator. Someone will have snatched it or kicked it onto the tracks. My phone is gone."

Casey Newton: So how far did it drop?

Kevin Roose: Probably 15 feet. A significant drop. I thought to myself, if I get to the end of this escalator and come back down, it’s going to be too late. Someone will have snatched it or accidentally kicked it onto the tracks. My phone is gone.

Casey Newton: You don’t have much faith in the citizens of San Francisco.

Kevin Roose: Have you visited San Francisco?

Casey Newton: Yes, I think a phone can generally survive 30 seconds on the ground, but I guess we’ll find out what happens.

Kevin Roose: Anyway, I had severe separation anxiety in the split second before I decided to do what I did, which was to try to run down the crowded up escalator. So I became that guy who was pushing through the commuters, saying, "I’m sorry, I’m sorry."

Casey Newton: You were a character in a bad comedy, running down the up escalator.

Kevin Roose: [Laughing] Yes.

Casey Newton: I was at that platform this morning and I heard a woman screaming. But now I’m realizing that was you. Did you get the phone?

Kevin Roose: I did. It’s safe. No cracks. It was retrieved. But yeah, that was a wild way to start my day.

Casey Newton: Well, thank you to all the good Samaritans of San Francisco who did not steal Kevin’s phone during the 30 seconds when it was on the floor. It kind of restores your faith in humanity a bit.

Kevin Roose: Oh, it does.

Casey Newton: So, this week, another upstart AI lab has the tech world talking with the release of a powerful new large language model. But unlike the others, this one might be running the federal government by springtime.

Kevin Roose: [Laughing]

Casey Newton: This week, xAI, which is Elon Musk’s AI company, released its latest model, Grok 3. And based on their own benchmark results and early reviews, it seems like it’s basically on par with the best models out there right now. And while it hasn’t been subjected to rigorous, independent testing, the early word from AI nerds is that it’s pretty good.

Kevin Roose: Well, Grok 3 is the new premium tier model of Grok, which is xAI’s AI model. It’s available to Premium+ subscribers on X, which is their $40 a month premium tier, which is cheaper than OpenAI’s most powerful plan, which is $200 a month. But it’s also built into X, the former Twitter app.

Casey Newton: Yeah, and I should say that I actually have used Grok 3 for this exact same reason, which is I have just been given free access to this thing for some reason. I guess the Department of X Efficiency or DOXE has not yet uncovered my account.

Kevin Roose: Right. [Laughing]

Casey Newton: We both played around with it a little bit. What were your impressions of Grok 3?

Kevin Roose: Well, like others who have commented, it seems like it’s about as good as some of the other models. When I asked Grok about itself, it said Grok 3 launch is a pivotal moment in AI. It seemed like a bit much. But I also asked it if it had an opinion about Platformer, my newsletter, and it actually said some really nice things – which I had to respect.

Casey Newton: And you?

Kevin Roose: So I put it through some of my proprietary evals. I actually do have things that I test AI models on. The Roose benchmarks. And yeah, I would say it did OK. It was not mind-blowingly good. It was not bad. It got some things that other models missed and vice versa. It did have access to X data, which is interesting. You can do things like tell it to analyze this person’s posts on X and tell me what they think about this topic.

Casey Newton: There’s this famous question that we always love to ask large language models. Can you count the Rs in strawberry? I asked Grok the equivalent question for X, which is, can you count Elon Musk’s children? Which it’s known to be very hard for large language models.

Kevin Roose: Well, a new one just dropped.

Casey Newton: Exactly. And that’s why it’s so hard for them to keep up.

Kevin Roose: And part of Elon Musk’s pitch for Grok for the past year or… are just certain decisions that it will prompt you to make where you’re like, "I don’t actually know what these terms mean or what the right decision is here." And you can ask the AI to just make the decision for you, but you might not be totally happy with the result.

Casey Newton: Now, during this process, I’m curious if you felt like you were learning something about the coding process. Like, if you spent the next year making these little one-off apps, do you feel like you would maybe be a decent junior software engineer? Or is the idea actually not to get into the details, to just let it build things? And if you don’t know what it’s doing, that’s none of your business.

Kevin Roose: Yeah, I think I’m more in the latter camp. I mean, this was the part that I found fascinating about what Andrej Karpathy said about vibe coding. He’s an extremely good programmer. But he says that he now can enter this mode where he basically just says, "OK, OK, OK, accept, accept, accept, and the computer will go off and do its thing."

Casey Newton: You know, I’ve been thinking about a blog post I read this week by a guy named Namanyay Goel. And his blog post was titled "New Junior Developers Can’t Actually Code". This post got a million views, according to the post that I’m looking at. And he is saying that when he talks to junior developers, they are having an experience very similar to you, which is that as they are building these systems, they are essentially just supervising an AI. They aren’t actually getting their hands dirty and understanding which mechanisms are leading to which results.

Kevin Roose: Yeah, I think this is a very real thing. I mean, the flip side of me, a non-coder being able to build stuff, is that if real coders are using these tools, there’s no incentive for them to learn the basic skills of programming and learn the syntax of the different languages. And yeah, I don’t know what to do about that.

Casey Newton: What do you think?

Kevin Roose: It seems like a version of what happened when we all got like Google Maps on our phones is that people started losing their sense of direction. There’s this kind of skill atrophy issue that people worry about. But I think that the returns to knowing how to use these things effectively are still great enough and still require enough knowledge of how the various pieces of code fit together, that it still makes sense for people to learn to code.

Casey Newton: All right.

Kevin Roose: What do you think?

Casey Newton: What I think is that as AI systems get more and more powerful, we need people who do understand them on a very detailed, technical, complex, down-to-the-metal kind of way. And that if we don’t do that, our only alternative will just be to trust the AI when we ask it, "Hey, how do you work?" And there are a lot of reasons why I don’t want to end up in that world. So I’m comfortable having fewer people in this world who know the code at that level of detail. And it’s fine with me if most software engineers don’t. But I want a solid core of people who do.

Kevin Roose: Yeah. And I’d like to continue with my vibe-coding experiments, trying to build increasingly more useful tools for myself and my friends.

Casey Newton: And I’m thinking about starting because if you can do it, surely I can.

Kevin Roose: [Laughing] Yes, anyone can. That is sort of the point. And I also would love to hear from our listeners, what they are vibe coding. What tools and apps are you building using AI that are solving your own personal, specific problems?

Casey Newton: Did you invent a novel bio weapon using ChatGPT? We’d love to hear from you.

Kevin Roose: Yeah, please email that one to tips@fbi.gov.

Casey Newton: [Laughing] But the others, hardfork@nytimes.com.

[Upbeat electronic music]

Kevin Roose: "Hard Fork" is produced by Whitney Jones and Rachel Cohn. We’re edited by Rachel Dry. We’re fact-checked by Caitlin Love. Today’s show was engineered by Alyssa Moxley. Original music by Elisheba Ittoop, Marion Lozano, Diane Wong, Rowan Niemisto, and Dan Powell. Our audience editor is Nell Gallogly. Video production by Chris Schott, Sawyer Roque, and Pat Gunther. You can watch this full episode on