Category: 4. Technology

Proving that it’s not just Intel CPUs that get included in bundle bargains these days, Newegg has a fantastic AMD Ryzen 7800X3D deal going at the moment, which not only enables you to pick up this chip for just $369.99 ($80 lower than Newegg’s list price), but you also get a free 1TB Team Group SSD with it. It’s a decent PCIe 4.0 drive as well, which is faster than older PCIe 3.0 drives, and way quicker than older SATA SSDs.

Importantly, you also get one of our favorite processors in this bundle. We gave this chip a score of 9/10 in our AMD Ryzen 7 7800X3D review when it was released, and while it’s since been superseded by the new 9800X3D, the cheaper price of the 7800X3D means it still has a strong place on our guide to buying the best gaming CPU. That’s all thanks to this CPU’s huge slice of AMD 3D V-cache that sits on top of the CPU cores, and massively improves gaming performance.

We’ve seen the price of this chip fluctuate a fair bit over the last few months. Following a supply shortage after the launch of the new AMD Ryzen 7 9800X3D, we saw prices of over $500 being listed for the 7800X3D earlier this year. We’ve since seen it drop as low as $358.59 since then, but $369.99 is still an excellent price for such a capable chip.

Its eight Zen 4 cores are more than enough for gaming, and while the clock speed is a little low at 5GHz, the huge amount of cache makes up for this massively. By effectively having a massive 96MB of L3 cache available, you massively reduce the likelihood of cache misses, which means the CPU is less likely to have to page your slower system memory for data.

The Ryzen 7 9800X3D might be quicker, with its 5.2GHz clock speed and faster Zen 5 architecture, but it also costs over $100 more, and the 7800X3D is still a great CPU. In fact, this is the chip we use to test all the GPUs in our guide to buying the best graphics card.

Meanwhile, the SSD on offer is a Team Group MP44L, which uses the 4x PCIe 4.0 interface and can read at up to 5,000MB/s, with a top sequential write pace of 4,500MB/s. While those speeds aren’t going to rival the PCIe 5.0 drives on our guide to buying the best gaming SSD, they’re still nearly 10x the speed of a SATA drive. Besides, you really can’t complain when you’re getting a PCIe 4.0 drive for free – it’s going for $62.99 on Newegg now if you buy it separately.

If you want to take advantage of this deal, you just need to click on this link here to take you to Newegg, and then make sure the “Add Free Gift Offer to Cart” box is ticked. You’ll need to be quick, though, as it’s listed as a limited offer.

If you’re thinking of building a new rig with this bundle, check out our best gaming motherboard guide to find a decent AM5 board to house your CPU and SSD, as well as our newly updated guide to buying the best CPU cooler for your needs. If you’re looking for a great budget cooler, we’ve tested the Thermalright Peerless Assassin 120SE ARGB on the 7800X3D, and it works fine, while also looking good for just $39.99.

Google is now offering compensation to Pixel 6a users facing battery-related issues. As part of its new Battery Performance Programme, the company is giving customers the option to either get their phone battery replaced for free or claim a cash or store credit payout. The move comes after complaints of overheating and battery performance concerns linked to the Pixel 6a.

To prevent further battery-related problems, Google will push a mandatory Android 16 update to all Pixel 6a devices. This update is aimed at improving battery efficiency and reducing overheating risks. While free battery replacement at authorised centres was already available, Google has now added more support choices for users who prefer to move on from the device.

According to details shared by the company, affected users who don’t want to go for a battery replacement can opt for a trade-in offer. Under this, Pixel 6a users can receive $100 (around Rs 8,500) as direct cash or choose to get $150 (approximately Rs 12,800) as a Google Store credit code. This store credit can be used towards buying a new Pixel phone. The final value in local currency will be based on the day’s exchange rate, and Google has mentioned that cash payouts may not be available in all regions, depending on local rules.

For handling payments, Google is working with Payoneer, a third-party financial platform. To process the money, users might need to share personal details like identification numbers, this will depend on the rules of the country the user is in. For example, users in the US may be asked to share their Social Security Number, while other regions may require alternate ID proof.

To know if they are eligible, Pixel 6a users must visit a dedicated eligibility page set up by Google. They’ll be required to enter their email address linked to the device and the IMEI number of the phone. In case someone is helping a family member or friend with the process, they can submit the details using another email ID, although Google has warned that it might ask for more information in some cases for verification.

Once eligibility is confirmed, users can go ahead and choose whether they want the free battery service or claim compensation. This move from Google gives users flexibility and support, especially those using older units or planning an upgrade. The combination of a required software update and hardware support shows that the company is taking battery issues on the Pixel 6a seriously while giving affected customers practical solutions.

– Ends

We’ve scoured the internet for July 4 camera deals ahead of the Amazon Prime Day sales, taking place July 8-11 this year. There are some great offers to be had from top brands such as Canon, Sony and Nikon and more.

With our experienced reviewers having tested and reviewed these models (or their predecessors or successors), we can say with confidence that these cameras are worth the investment. What’s even better, you can grab them now for a reduced price.

Cruise robotaxis are back on the road… well, kind of. Though General Motors pulled the plug on its self-driving taxi business last year, the automaker has been quietly repurposing a few of the vehicles as it seeks to develop new driver-assistance technologies.

This week, WIRED spotted a GM Bolt electric hatchback on the San Francisco-Oakland Bay Bridge, and later saw a similar vehicle on Interstate 880 near Oakland. In each instance, the car was being driven by a human. But it held equipment on the roof such as lidar sensors that resembled the setup from the Cruise ride-hailing system. The vehicle had “Mint” written on the hood, but didn’t include any visually apparent Cruise branding.

GM spokesperson Chaiti Sen confirms to WIRED that the company is indeed “using a limited number of Cruise Bolt vehicles on select highways in Michigan, Texas and Bay Area for testing with trained drivers to further develop simulation models and advanced driver assistance systems.” She adds, “This is internal testing and does not involve public passengers.”

GM removed the orange-and-white Cruise logo from the cars’ sides after it took full ownership of the unit in February, she says. The recent activity began in Michigan and Texas in February and the San Francisco Bay Area-region in mid-April, Sen says. Cruise had named each vehicle in its fleet, and Sen confirmed that “Mint” has been among the vehicles newly active in the Bay Area.

The testing shows for the first time how GM is beginning to give a second life to a fleet of no less than hundreds of vehicles left over from a costly project that ran aground.

GM initially acquired a majority stake in San Francisco-based Cruise in 2016, and invested more than $8 billion into developing a robotaxi service. The operation was off to a fast start and eyeing a rapid expansion until October 2023, when a Cruise vehicle struck a pedestrian in San Francisco who had just been hit by a human-driven vehicle.

In the aftermath of the incident, Cruise misled state regulators, lost a key permit, halted operations, and laid off a quarter of its workers.

After some attempts to restart the business, GM announced this past December that the experiment would be cancelled altogether. At the time, GM CEO Mary Barra told analysts that running a robotaxi fleet was an expensive distraction from the business of making cars.

But the technology behind Cruise is helping improve the roughly 7-year-old Super Cruise system found in some GM cars. It aims to help drivers stay in and change lanes, or apply the emergency brake without needing to use their hands.

Several automakers are racing to develop cars that offload an increasing amount of driving tasks to computers. GM claims about 60 percent of its 360,000 Super Cruise customers regularly make use of the capability.

In the US, the robotaxi industry has been dominated by Waymo, though Elon Musk’s Tesla and Amazon’s Zoox are among those continuing to try to catch up.

GM’s repurposed Bolts blend into San Francisco-area roads, on which cars with heavy-duty computer gear attached to roof, back, and sides have become commonplace. They include not only companies testing sensors and algorithms, but also map providers collecting data and hobbyists attempting to upgrade their personal rides.

Ploopy has announced another desktop accessory called the Ploopy Knob that can function like a control dial for adjusting volume, scrolling documents, or scrubbing through media on a computer. The Canadian company isn’t exactly a household name like Logitech, but Ploopy’s open-source peripherals offer a lot of customizability, and like its mouse and trackballs, you can customize the look of the Knob by 3D-printing your own hardware.

The Ploopy Knob is available now through the company’s website for $49.99 CAD (around $37). Unlike many of the company’s other products, which can be purchased as cheaper DIY kits you build yourself, the Knob is only available as a fully assembled product with software preinstalled that works right out of the box. However, since it’s open-source, you can download all the design files and software on Ploopy’s GitHub page if you want to source the parts and build your own from scratch.

Powered by a Raspberry Pi RP2040 microcontroller, the Ploopy Knob uses a position sensor with a 12-bit resolution and a polling rate of over 1kHz to track its rotational movements. The company says the Knob supports high-resolution pixel-by-pixel scrolling on Windows and Linux, but warns that the experience may not be as smooth on Apple computers. “macOS does smoothing for input devices automatically. This interferes with the code that runs on the Knob, meaning that pixel-by-pixel high-resolution scrolling doesn’t work on macOS. It still functions as a scrolling device, but the scrolling is in discrete steps.”

As with the company’s other peripherals, the Ploopy Knob uses the open-source QMK firmware, which runs entirely on the device so you don’t need to install additional software on your computer.

On this week’s episode of The MacRumors Show, we discuss Apple’s apparent plan to launch a low-cost MacBook powered by an iPhone chip.

Earlier this week, Apple analyst Ming-Chi Kuo reported that Apple is set to launch an all-new “affordable” MacBook powered by an iPhone chip. The machine is expected to feature a 13-inch display, the A18 Pro chip, and color options that include silver, blue, pink, and yellow. MacRumors first spotted evidence of such a device in backend code related to Apple Intelligence last summer, and subsequently confirmed its use of the A18 Pro chip. The machine features the identifier “Mac17,1.”

This would be the first Mac powered by an ‌iPhone‌ chip. To date, all Apple silicon Macs have contained M-series chips, which offer higher core counts, support for larger amounts of memory, and better external display support. The A18 Pro chip debuted in the iPhone 16 Pro last year.

With the A18 Pro chip, the device is highly unlikely to feature Thunderbolt ports, more than 8GB of unified memory, and support for more than one external display. In line with how Apple tends to handle its other low-cost devices, the new MacBook could re-use the design and chassis of an older machine like the M1 MacBook Air to keep costs down and differentiate it from the MacBook Air. Apple could also revive the simple “MacBook” moniker, separating it from the MacBook Air and MacBook Pro, and mirroring the iPad lineup, which simply has the iPad as the entry-level model.

According to Kuo, the new MacBook is expected to enter mass production late in the fourth quarter of 2025 or early in the first quarter of 2026, which situates launch in the first half of next year.

We also discuss Apple’s broader low-cost device strategy, how it seems to be positioning its device lineups going forward, and more. The MacRumors Show has its own YouTube channel, so make sure you’re subscribed to keep up with new episodes and clips.

You can also listen to The MacRumors Show on Apple Podcasts, Spotify, Overcast, or your preferred podcasts app. You can also copy our RSS feed directly into your podcast player.

If you haven’t already listened to the previous episode of The MacRumors Show, catch up to hear is talk through through the changes introduced in the second developer beta of iOS 26.

Subscribe to The MacRumors Show for new episodes every week, where we discuss some of the topical news breaking here on MacRumors, often joined by interesting guests such as Kevin Nether, John Gruber, Mark Gurman, Jon Prosser, Luke Miani, Matthew Cassinelli, Brian Tong, Quinn Nelson, Jared Nelson, Eli Hodapp, Mike Bell, Sara Dietschy, iJustine, Jon Rettinger, Andru Edwards, Arnold Kim, Ben Sullins, Marcus Kane, Christopher Lawley, Frank McShan, David Lewis, Tyler Stalman, Sam Kohl, Federico Viticci, Thomas Frank, Jonathan Morrison, Ross Young, Ian Zelbo, and Rene Ritchie.

The MacRumors Show is on X @MacRumorsShow, so be sure to give us a follow to keep up with the podcast. You can also head over to The MacRumors Show forum thread to engage with us directly. Remember to rate and review the podcast, and let us know what subjects and guests you would like to see in the future.

Plugin developer 3d-io has released Packer-IO 1.3, the latest version of the free standalone UV packing application for games, motion graphics, VFX and visualization artists.

New features include support for real-world scene scale units, and for texel density, making it possible for games artists to maintain consistent texture resolution across models.

3dio has also released a separate free Blender integration plugin, UnwrellaConnect, which makes it possible to use Packer-IO directly inside the open-source 3D software.

An efficient standalone UV packing tool for organic and hard surface models
First released last year, Packer-IO is a free standalone UV packing tool.

It automatically arranges the UV islands of an imported 3D model to minimise wasted UV space, reducing the total file sizes of its texture maps.

The software can be used on both hard surface and organic models, and supports tiled UV layouts, used in applications like ZBrush.

It works with assets with “thousands of charts and millions of polygons”, and is resolution-independent, so packing times remain constant, regardless of the resolution of the textures.

However, it is currently purely a UV packing tool: it doesn’t unwrap the UVs of a model first. You can find more details in our original story on Packer-IO 1.0.

Now supports scale units and texel density
3d-io has now released its first feature updates to the software, in the shape of Packer-IO 1.2, which came out last month, and Packer-IO 1.3, which came out earlier this week.

New features in version 1.2 include scale-aware packing, with users now able to specify real-world scene scale units, including both metric and imperial measurements.

Games artists get support for texel density: it is now possible to specify a target resolution in pixels per centimeter, so that packed textures look visually consistent with those of other assets.

Version 1.3 provides “vastly improved” hole filling, with Packer-IO packing smaller UV islands into the space left between larger islands more intelligently.

New UnwrellaConnect plugin makes it possible to pack UVs directly inside Blender
3d-io has also released a free connector plugin for Blender, UnwrellaConnect, which integrates Packer-IO with Blender’s UI, making it possible to pack UVs of models directly inside Blender.

It supersedes UV-Packer for Blender, 3d-io’s old Blender plugin, which was based on the same core technology.

The Blender download link on the UV-Packer website has now been redirected, although the other editions, UV-Packer for 3ds Max and UV-Packer for Unreal Engine, are still available.

So how do Packer-IO and UnwrellaConnect differ from UVPacker for Blender?
If you already have UV-Packer for Blender, one reason to update to Packer-IO and UnwrellaConnect would be better integration with the other tools in your production pipeline.

Packer-IO itself supports 3D models imported from any DCC app, while UnwrellaConnect – as the name suggests – also works with Unwrella-IO, 3d-io’s commercial UV unwrapping tool.

Packer-IO also features a more streamlined UI and workflow than previous UV packing tools.

Licensing and system requirements
Packer-IO 1.3 is compatible with Windows 10+ and macOS 10.15+. The software is free, and is licensed for use in commercial projects.

UnwrellaConnect is compatible with Blender 4.2+. Source code is available under a MIT license.

Download free standalone UV packing software Packer-IO from 3d-io’s product website

Download free Blender integration plugin UnwrellaConnect from the plugin’s GitHub repository

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Meet AUTOSEL, a Linux maintainer that helps keep the kernel stable.

AUTOSEL is a script, one that uses a Large Language Model (LLM) to complete its task.

It does a thankless job, one loathed by all kernel maintainers, that of backporting patches.

Backporting patches is a “very tedious and frustrating process” that “doesn’t scale,” said NVIDIA Distinguished Software Engineer Sasha Levin, in a talk at the Open Source Summit. The presentation focused on how AI is starting to be used in the Linux kernel community to help keep up with the Herculean tasks of maintaining the Linux kernel.

It may not be writing exciting new features for the open source operating system kernel yet, but AI has excelled in tasks that are mind-numbingly repetitive yet still necessary. In other words, AI is already making the lives of Linux kernel developers easier, said Levin, who helps maintain the Linux Kernel Stable and LTS trees.

Patch Inspection

As the world’s single largest open source project, the Linux kernel gets updated and upgraded … a lot.

The pace has remained constant: As many as 10,000 new patches have landed in the mainline kernel over a 10-week period.

Stable and Long-Term Support (LTS) kernel maintainers usually review around 100 patches per day, every day, including weekends and holidays.

Only a few, about 5-10, turn out to be suitable for backporting.

Levin’s AUTOSEL, written in Rust, takes a first pass at incoming commits, looking for similarities across submitted commits and past backporting decisions, and suggesting only those to human committers to seem to be worthy of closer review.

AUTOSEL is built from multiple LLMs, with each LLM used for a particular strength, as well as for cross-validation to reduce errors and hallucinations.

For each commit, the tool creates mathematical representations (or “embeddings”) of the text that preserve semantic meaning for every commit in the kernel’s history, making them easily comparable.

For human maintainers, the tools cuts down the number of commits that humans have to review. It even explains its reasoning in an email.

Know Your Tools

Like any other tool, the value of an LLM corresponds to how well it is understood by it user.

You can think of Large Language Models as the next generation of compilers, providing developers with a jump in productivity, Levin said. They act like “massive state machines,” though what is unusual about them is that they perform state transitions in a probabilistic, rather than deterministic, manner.

They are good at matching patterns given a huge number of parameters and an input provided by a user. A “temperature” parameter controls how probabilistic the LLM is, or how liberally it interprets its material.

Other Uses

And like any other technology, LLMs are first being tested in minor tasks.

LLMs excel at “small, well-defined tasks.” Levin said.

One such use is code generation and refactoring. Tightly-defined bug fixes, or converting code to other forms, such as standard APIs, are good tasks.

For the 6.15 kernel release, Levin had an LLM write a patch to convert the open-coded hash table implementation to a standard API.

Linux kernel 6.16 included git-resolve. This tool resolves incomplete or incorrect commit IDs, a nagging issue for core developers, though not one that occurs often enough to spend a lot of time manually writing a tool to figure out which commit an incomplete SHA-1 is actually connected to.

It took Levin all of 20 minutes to work with the LLM to create the tool.

It would take an engineer about half a day to create such a tool, making it not worth the effort given the relative rarity of the issue it addressed. Plus the LLM did a lot of extra credit: It created a set of self-tests and even documentation, which a human engineer would have done begrudgingly if at all.

There’s no end of clean-up tasks that could be done with the kernel, Levin said. An LLM could help non-native English speakers write descriptive commit messages.

CVE Classification

Another tedious chore is classifying security vulnerabilities (CVEs), a task that the Linux kernel community took on in 2024.

The work involves inspecting commits to see if they address security issues.

Originally, a set of “hacky Bash scripts” was written to help.

LLMs were used to replace the scripts with a set of far more refined tools written in Rust, which included a full set of testing tools and documentation.

Using AUTOSEL as a launching point, a CVE classifier uses LLMs to identify commits that address security issues, and then goes on to check the vulnerability hasn’t already addressed in a previous patch. This is an overwhelming task for humans, given the 40 million lines of code that make up the Linux kernel.

LLMs can understand the semantic meaning of the commits, which provides for a far more comprehensive matching capability. A Retrieval Augmented Generation (RAG) cycle pulls in the kernel’s development history and documentation (e.g., Git repositories) to minimize hallucinations.

The LLMs effectively act as AI agents, Levin noted. They can run git commands, such as git blame, directly against the code repository to learn from the history of the kernel development itself.

In summary, AI has thus far helped Linux scale its maintenance efforts, while enhancing consistency and reducing manual labor for tedious tasks.