Provided you don’t drive long distances every day, Level 1 charging could be all you need.

Level 1 vs. Level 2 vs. Level 3 charging: What’s the difference?

Level 1 vs. Level 2: Which EV charger do you need at home?

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When should you use Level 3 chargers?

Mayy Contributor/Shutterstock

Meta’s new AI agent Muse took the spotlight at the company’s annual Connect event, where CEO Mark Zuckerberg made it clear that Facebook’s parent company plans to push AI features everywhere.

On the latest episode of TechCrunch’s Equity podcast, Kirsten Korosec, Sean O’Kane, and I discussed Meta’s AI announcements seemed to steal the spotlight during a week of new model launches from OpenAI and Anthropic.

With other big AI companies focused on coding and enterprise tools, it was a little surprising to see Meta move in the opposite direction, with a consumer focus and a cute, Tamagotchi-style AI device that Meta insists is for adults only. But as Kirsten noted, this could be playing to Meta’s strengths.

Sean tried Muse for himself, and while he was pleased that the agent actually found him some unclaimed money, he described the feature as more “a party-trick type thing,” rather than something that will drive ongoing usage. Plus, there’s the question of whether users can trust Meta’s AI with sensitive information.

“Meta’s business is to sell you ads,” Sean said. “And yes, they’ll make the argument that the more they know about you, the more accurate and interesting the ads will be — wake me up when we get to that fever dream.”

Keep reading for a preview of our full conversation, edited for length and clarity.

Kirsten Korosec: So how do you put Muse, which is this new personal AI agent that’s just been released by Meta and [is] clearly a bet on consumer — how does that fit into what you just described, at least with other frontier AI model companies seeing opportunity and business within enterprise? Because Meta Connect, which is their big annual event, just happened, and they are all-in on Muse, that is very clear.

Anthony Ha: That was definitely very head spinning for me, because it certainly feels like what we’ve been talking about has been this shift towards enterprise — not exclusively, but certainly that’s where the money, the attention is going.

Maybe some of that is because of the relative position of these different companies — OpenAI and Anthropic are in the lead in a lot of ways, but also, they’re planning to go public either this year, or next year in the case of OpenAI. And so there’s this feeling of, “I think we’ve got to actually make money now.” Not to say that they’re not making money [already], but because the costs are so high and the valuations are so high, they have to make money on this scale that’s essentially unprecedented. And I think they’re seeing enterprise as the way to do that.

And I wonder if Meta, for a variety of reasons, sees a different opportunity. There’s a part of me that’s like, “Wait, did they not get the memo?” But I think more charitably, you could say, “Well, if that’s where OpenAI and Anthropic are going, then maybe there is more of an opportunity for Meta to make the more consumer-friendly [version and] continue advancing AI on the consumer side.”

Kirsten: I mean, we can complain about or criticize or critique Meta all day long, but they’re very good and have [an] established track record of embedding themselves in everyday people’s lives. I mean, there’s a reason why Facebook has so many users — Instagram, WhatsApp. And I’ve never really thought of them as an enterprise product anyway. So I think it’s smart for them to continue to push on the consumer piece. 

Sean, you’ve already tried Muse, which has already been out for a couple weeks. And I’m wondering if you see what your impression is, and if you see it being successful in the bid to become part of every part of your life.

Sean O’Kane: I mean, not really. I understand why some people think that is going to be the case. I’m sure a lot of people understand this, but this is roughly Meta’s kind ground-up version of an on-your iPhone, or on your Android, app of OpenClaw, which we talked about a couple months ago, which Meta went out and basically bought and integrated those folks’ work. It was the first big explosion of like, “Holy smokes, these agents can do all this stuff for me while I’m out and about, and I can just text with it and let it control my whole computer.” There’s a lot of the same elements of that at play. And having it in your hand, on an app that works like a relatively good chatbot as the interface, it does seem pretty powerful.

One of the first things that I did with it was — because it makes a bunch of suggestions for you, as to things that it can do, and one of them was, “I’ll scan to see if you have any unclaimed funds,” this thing that I think no one ever really thinks about and often is going to completely miss, because there’s just not a lot of unclaimed property funds out there in your name. Surprise, surprise, there were some for me.

It helped me make some money on my first day, and that was pretty cool. I wouldn’t have done that if I hadn’t been prompted by this thing to do it. And there’s a check on its way to me in the mail. Fantastic. [But] that ends pretty quickly, right? That was a one-time shot, but it’s not a thing that’s repeatable. That’s more like a party trick-type thing.

Kirsten: I mean, you just killed your own argument. I don’t see how that wouldn’t become wildly popular.

Sean: The more sustainable version of that, and the thing that Meta’s talked up a lot over the last couple of days, is taking that idea and applying it to your real, true everyday financials, like giving it your information for your credit card, your Gmail account, all this other stuff, do things that we’ve seen other companies do, like Rocket Money or whatever, where it’ll go cancel subscriptions that you’re not using or identify double charges, things that frankly the credit card company should be doing already. 

And at that point you just run into that trust wall with Meta. I think one of the reasons that I was willing to explore this and was curious to stick with it a little bit — even through to today — is that somewhat shockingly, when I downloaded it, I just assumed that it would like really instantly prompt me and like plug me right into Threads, Instagram, Facebook, which I don’t really use ever, and pull up that context immediately.

But it didn’t. And it was working with me like I was a stranger at first, which made me more willing to use it, because I didn’t feel like Meta had everything on me already. But you can see, as you start to use it, it really tries to grab you and pull those things into the system, so that it can learn all this stuff about you. 

I don’t know that I will ever trust Meta the same way. I think it’s an interesting timing for me, having just upgraded my iPhone and getting onto the new iOS with the new Siri that actually works and can do some controls on your phone in a way that is surprising and helpful, that it’s never been able to do. [I’ve been] thinking about how much I’ve been using that over the last week and how much more how much more willing I would be to have the Siri version of Muse take that information, because I just trust Apple more with that really sensitive information and not only trust it with the information from a cybersecurity perspective, but from the fact that its business is not to sell me a bunch of crappy ads.

Meta’s business is to sell you ads. And yes, they’ll make the argument that the more they know about you, the more accurate and interesting the ads will be — wake me up when we get to that fever dream. 

And beyond the one-time money lever that I got, which was great, I don’t feel like I’ve found anything else that’s really all that useful — other than the fact that it is, to Anthony’s point, really tailored at keeping it sort of consumer-y in your interactions with it, with which I do think helps it and is why people are talking about it so much.

Dolphin is an emulator for the Nintendo GameCube and Wii. It allows PC gamers to enjoy games from both consoles in full HD (1080p), along with a range of enhancements – including support for all PC controllers, turbo speed, networked multiplayer, and more.

To run the Windows version, the 64-bit Visual C++ redistributable for Visual Studio 2022 must be installed.

What games can you plan with Dolphin Emulator?

Dolphin lets you enjoy Nintendo GameCube and Wii games on PC. For a complete list of playable games, you can check out the list here.

What kind of CPU do I need to run Dolphin?

You’ll need a quad-core CPU or better. With four cores, Dolphin has two cores for the main emulation threads, a third core for other tasks, and another core for the OS and background tasks.

Do I need a powerful GPU to run the Dolphin emulator?

A discrete graphics card that supports DirectX11.1 and OpenGL 4.4 is highly recommended. The more powerful the graphics card, the more pixels and enhancements you can throw at it.

• Nvidia: A GeForce GTX 1060 or better Nvidia GPU will be able to play Dolphin in HD resolutions with Ubershaders well.
• AMD: A Radeon RX 570 or better AMD GPU will perform well in Dolphin with Ubershaders. AMD generally favors D3D over OpenGL.
• Intel: Iris Pro iGPUs will handle Dolphin well in D3D in Windows. Integrated graphics older than HD 4000 are not supported.

How much RAM do I need to run Dolphin?

Dolphin requires at least 2GB of RAM. RAM speed generally has no effect on emulation performance.

Can I use two or more controllers for local multiplayer on Dolphin emulator?

Yes, if you have two or more friends connecting from the same computer, you can give a single computer multiple controllers. You only need to configure the first two ports of the Controller Configuration page.

What operating systems are supported?

Dolphin is a cross-platform emulator that runs on Windows 10 and Windows 11, Linux, macOS (10.15 Catalina and up), and Android (5.0 and above). Dolphin requires 64-bit operating systems to run properly.

What’s New

Welcome to Dolphin 2609’s accompanying Progress Report! Like everyone else, we’ve been doing our best to weather the Techpocalypse brought on by AI, but it’s really come after us in the past few months. Our website has been up and down repeatedly lately, as our defenses are barely holding out under the endless bombardment. But now AI has started to come for the emulator directly, with people using AI to mass-scan open source projects for potential vulnerabilities and overwhelm our volunteer team with very verbose reports. Though draining, once these vulnerabilities are out there, we can’t ignore them. A lot of effort has had to be diverted to deal with them, both in patching them and adjusting our workflows to better manage them. For more information, zip directly to that section with this link here.

But that’s not all. A vulnerability in macOS allowed our macOS buildbot to be briefly compromised by a generic cryptominer attack. We’ll skip the quick summary and just point you toward the full story below, which you can reach by clicking here. The important thing is that we have determined that no builds were compromised.

We really just want to keep making Dolphin better. Fortunately, despite these headaches and roadbumps, there are still quite a few notable changes to go through, so let’s get to it.

Notable Changes

2606-91 – Android NetPlay by tom-pratt

Under the hood, our mobile and desktop builds are almost identical. Dolphin is simply Dolphin; the only difference is the UI that lays on top. Despite this, our Android release doesn’t have feature parity with our flagship desktop builds. A lot of features that are missing in the Android GUI that are present in the desktop GUI are mostly missing because they’d be difficult to implement or would have limited value on Android.

NetPlay once fell into both camps.

For those unaware, Dolphin has lockstep NetPlay available to allow for online play in games that only had local multiplayer. Lockstep NetPlay requires perfect synchronization between each instance, and thus Dolphin has to run in a deterministic mode. This means forcing Single Core (or using a slower and even hackier version of Dual Core), setting the same starting time/seed, and making sure the same inputs make it to every machine. Optionally, save data and cheats can also be synchronized for use on NetPlay. If done right, each instance of the emulator will stay synchronized with no further intervention, with Dolphin only passing inputs.

All of these complexities make NetPlay an enticing, but often cumbersome-to-use feature. And given that it would be annoying to create a good GUI for NetPlay on Android and it would make games run slower on already limited hardware, there was no rush to implement it on Android.

In the 2020s, the scales started to tilt in the other direction. Android devices have gotten stronger and stronger, and though CPU governors and GPU drivers still confound us, many flagship devices can run games in Single Core just fine. Additionally, Jetpack Compose for Android allows for easier and faster development of Android GUIs.

Wanting to share some of his favorite childhood experiences with his own kids, tom-pratt stepped up to the challenge. Using Compose, he built up the NetPlay Android GUI across several pull requests, with an initial bare bones implementation. This made it easier to review and eventually merge, and was quickly followed up with more features, such as controller port configuration for the host, that brings it closer to parity with the desktop implementation.

And now, as of Dolphin 2609, NetPlay is ready for Android users!

Currently, Android NetPlay requires users to be on a standard network (Wi-Fi, Ethernet, etc), but work has been started on adding support for Wi-Fi Direct, which would allow Android NetPlay to function between nearby devices with no network, similar to how the Nintendo DS’s local Wi-Fi play worked.

Note: Using NetPlay over mobile data is not recommended. Even if you can get it to work, the packet loss and latency are not particularly suitable for lockstep multiplayer.

Cross Platform NetPlay

Can Android and desktop Dolphin play together with NetPlay? Yes, they can! Players can mix and match devices with whatever they have, so phones and laptops can play together just fine! However, there are some limitations that must be kept in mind.

Most full-size desktops use x86-64 processors, while most phones use ARM processors, and Dolphin uses different JITs depending on the host CPU. While our ARM64 and x86-64 JITs are very similar, they are not completely identical, and those JIT differences are likely to cause desyncs. Mixing and matching CPU architectures isn’t a guaranteed failure though – whether these differences lead to a desync or not depends on what instructions games use and in what order.

Ignoring the JIT problem, there is one more major source of potential desyncs: the Framebuffer! Games that use EFB Access and/or Store EFB/XFB Copies to RAM can get different results from different graphics drivers. If these results mismatch at all, even if it doesn’t directly affect game logic, a timebase desync will usually be reported. Often this won’t outright break NetPlay (at least immediately), but if the difference becomes big enough, the instances will diverge. Given how special Adreno and Mali drivers are, there may even be problems when playing between different kinds of phones in those games!

Complete release notes here.

Quordle was one of the original Wordle alternatives and is still going strong now more than 1,500 games later. It offers a genuine challenge, though, so read on if you need some Quordle hints today — or scroll down further for the answers.

Enjoy playing word games? You can also check out my NYT Connections today and NYT Strands today pages for hints and answers for those puzzles, while Marc’s Wordle today column covers the original viral word game.

Campaigners who helped stop the UK from letting AI companies train on copyrighted work without permission have warned Australia not to try the same thing. They spoke to Dan Milmo for the Guardian.

Australia’s government is weighing an opt-out model, under which AI firms could train on creators’ work unless they object. The plan came to light this month in leaked slides from the Attorney-General’s Department, ABC News reported.

The UK dropped a similar plan in March. Technology secretary Liz Kendall said the government no longer had a preferred option, after only 3% of more than 10,000 people who responded to its consultation backed opt-out.

Beeban Kidron, a film director and member of the House of Lords, led the political fight in the UK. She told the Guardian that Prime Minister Anthony Albanese should take note.

“He should not squander his reputation by selling Australian creatives down the river,” Kidron said.

Composer Ed Newton-Rex, a former AI executive, organised a silent protest album backed by more than 1,000 musicians and a book with no text, signed by 10,000 writers. He said the UK campaign made the government see that the public wanted AI firms to pay for content.

“It will take just a moment for people to understand this is not fair,” Newton-Rex told the Guardian.

However, the tech industry still argues that AI training and fair pay for creators can go together. Antony Walker of trade group techUK told the Guardian that rights holders had been very effective at shouting down the debate in the UK.

In Australia, AI firms including OpenAI and Anthropic have asked the government to ease its rules. OpenAI has said it could not set up an Australian training centre without changes to copyright law, according to ABC News.

Attorney-General Michelle Rowland’s office said it is still consulting on options that give creators meaningful control and fair payment.

Amazon billed the newest Echo Show 11, priced at $149.99 (was $250), as a mini entertainment center you can park anywhere in the house, even on the road. Rooms with a wall outlet get the better half of that promise. This late-2025 smart display sits on the same rounded, fabric-wrapped base as the current Echo Show 8, then hangs an 11-inch Full HD touchscreen in front so the glass appears to float. Graphite and Glacier White are the two finishes. At about 10 by 7.2 by 5 inches and 2.9 pounds, you can slide it from kitchen to guest room. A 30-watt brick is the only power source, and the only port on the back is that power jack, so a weekend trip means packing a cord and hunting for an outlet.

This model exists solely because of its screen size. The panel measures around 10.95 inches diagonally and boasts a sharp resolution of 1920 by 1200 pixels, which is a significant improvement over the 8.7 inch HD screen on the comparable Show 8 and the previous Echo Show 10. The color remains visible from the side of a counter, which is beneficial when looking at a recipe while chopping. Adaptive brightness is useful in a bright kitchen, but don’t expect HDR. However, features like as timers, weather, Prime Video, and Netflix make the additional glass worthwhile.

Amazon Echo Show 11 (newest model), Vibrant Full-HD 11″ display with more viewing area and spatial audio…

• New size, more viewing area: The 11“ smart display features a vibrant Full-HD touchscreen with 60% more viewing area versus Echo Show…
• Content looks and sounds incredible: Watch shows on Prime Video, Netflix, and more on the vibrant Full-HD 11″ screen and enjoy room-filling spatial…
• Your everyday assistant: The 11″ display makes it easy to see recipes and calendars at a glance, find meal inspo, and manage your shopping lists. With…

The sound comes from a 2.8-inch woofer and two forward-facing speakers wrapped in this lovely 3D knit fabric. Spatial audio does a good job of broadening the stage and is appropriate for a kitchen or small living room, but Amazon claims it has up to twice the bass of the 2023 Echo Show 8. Vocals are clear on podcasts and phone calls, however. The two speakers are set close together, so you won’t get much stereo width from them. That speaker setup is actually identical to the new Show 8, so the extra money you spent likely only got you a bigger and sharper screen and absolutely nothing better in the audio department.

Amazon’s AZ3 Pro chip, which features a specialized AI engine for Alexa+, is the brains behind this device in the United States, and it does an excellent job of keeping Alexa’s wake phrase sharp even when music is playing. Responses are also prompt. Above the bezel, there’s a 13 megapixel camera that auto frames video calls and feeds Visual ID, allowing the home screen to move to someone’s calendar. However, this time, there is no real camera shutter. There is a button on the side that disables the microphones and camera and illuminates a red LED, which is adequate for regular use, but those who preferred a sliding cover will likely miss it.

The new Omnisense is a quieter update, though. It employs ultrasound, Wi-Fi radar, an accelerometer, light and temperature sensors, and a camera to determine when someone enters the room, who they are, and how far away they are standing. Stand back and you’ll see a simple clock or photo reel. The widgets become visible as you move closer. Routines can be triggered even when a room is empty. You also get built-in Zigbee, a Thread border router, and Matter compatibility, allowing the Show 11 to function as a standalone smart-home hub without the need for additional box on the shelf. It supports Wi-Fi 6E and Bluetooth 5.3 radios.

Continuing their reverse-engineering of Intel’s 8087 FPU, [Ken Shirriff] and friends took a look at one of the trigonometric functions, specifically FPTAN.  The most exciting part with such reverse-engineering is probably figuring out which algorithm was used in the implementation, while trying to determine the reasoning behind the final hardware design.

If you’re running a simple MCU or MPU like the 6502 or Z80 without hardware functions you’d likely use an algorithm such as CORDIC or similar, as this requires only basic hardware features like addition, subtraction, bitshift, and look-up tables. One can also use polynomial approximation if there’s hardware support for a potential speed-up, or as is the case in the 8087, create a hybrid approach that targets speed and accuracy.

In the article the exact implementation to get to 64 bits of accuracy is detailed, starting with the 16 bits calculated using CORDIC before switching to the Padé approximant technique involving the ratio of two polynomials. Since after calculating the brunt of the final value with CORDIC the remainder is a fairly small value this polynomial approximation not just very accurate but also fast.

This approach allows the FPTAN and similar trigonometric functions in this FPU to hit a very high level of accuracy and not require the look-up table sizes and additional time required to work through the remaining bits with CORDIC. For those who want to see the full algorithm Intel’s engineers used, [Ken] has the full microcode listing with comments in the article as well.

As for the exact speed-up from this approach, [Ken] calculates for one value that FPTAN would spend 33% on CORDIC pseudo-division, 47% on CORDIC pseudo-multiplication and a mere 15% on the polynomial approximation along with about 5% overhead.

With the Pentium series of CPUs Intel moved completely away from CORDIC, as it’s clear that as accurate as it may be, it’s hard to scale to a significant number of bits without incurring significant time penalties. With the introduction of SIMD instructions the x87 ISA has further seen its functionality reduced, but this analysis shows once again why the 8087 made such an impact when it was released.

Good morning! Let’s play Connections, the NYT’s clever word game that challenges you to group answers in various categories. It can be tough, so read on if you need Connections hints.

What should you do once you’ve finished? Why, play some more word games of course. I’ve also got daily Strands hints and answers and Quordle hints and answers articles if you need help for those too, while Marc’s Wordle today page covers the original viral word game.