Anne Aaron just can’t help herself.
Technology
Inside Netflix’s bet on advanced video encoding
/cdn.vox-cdn.com/uploads/chorus_asset/file/25477748/247139_Netflix_Video_Encoding_CVirginia0.jpg?ssl=1 "Inside Netflix’s bet on advanced video encoding")
Aaron, Netflix’s senior encoding technology director, was watching the company’s livestream of the Screen Actors Guild Awards earlier this year. And while the rest of the world marveled at all those celebrities and their glitzy outfits sparkling in a sea of flashing cameras, Aaron’s mind immediately started to analyze all the associated visual challenges Netflix’s encoding tech would have to tackle. “Oh my gosh, this content is going to be so hard to encode,” she recalled thinking when I recently interviewed her in Netflix’s office in Los Gatos, California.
Aaron has spent the past 13 years optimizing the way Netflix encodes its movies and TV shows. The work she and her team have done allows the company to deliver better-looking streams over slower connections and has resulted in 50 percent bandwidth savings for 4K streams alone, according to Aaron. Netflix’s encoding team has also contributed to industrywide efforts to improve streaming, including the development of the AV1 video codec and its eventual successor.
Now, Aaron is getting ready to tackle what’s next for Netflix: Not content with just being a service for binge-watching, the company ventured into cloud gaming and livestreaming last year. So far, Netflix has primarily dabbled in one-off live events like the SAG Awards. But starting next year, the company will stream WWE RAW live every Monday. The streamer nabbed the wrestling franchise from Comcast’s USA Network, where it has long been the No. 1 rated show, regularly drawing audiences of around 1.7 million viewers. Satisfying that audience week after week poses some very novel challenges.
“It’s a completely different encoding pipeline than what we’ve had for VOD,” Aaron said, using industry shorthand for on-demand video streaming. “My challenge to (my) team is to get to the same bandwidth requirements as VOD but do it in a faster, real-time way.”
To achieve that, Aaron and her team have to basically start all over and disregard almost everything they’ve learned during more than a decade of optimizing Netflix’s streams — a decade during which Netflix’s video engineers re-encoded the company’s entire catalog multiple times, began using machine learning to make sure Netflix’s streams look good, and were forced to tweak their approach when a show like Barbie Dreamhouse Adventures tripped up the company’s encoders.
When Aaron joined Netflix in 2011, the company was approaching streaming much like everyone else in the online video industry. “We have to support a huge variety of devices,” said Aaron. “Really old TVs, new TVs, mobile devices, set top boxes: each of those devices can have different bandwidth requirements.”
To address those needs, Netflix encoded each video with a bunch of different bitrates and resolutions according to a predefined list of encoding parameters, or recipes, as Aaron and her colleagues like to call them. Back in those days, a viewer on a very slow connection would automatically get a 240p stream with a bitrate of 235 kbps. Faster connections would receive a 1750 kbps 720p video; Netflix’s streaming quality topped out at 1080p with a 5800 kbps bitrate.
The company’s content delivery servers would automatically choose the best version for each viewer based on their device and broadband speeds and adjust the streaming quality on the fly to account for network slow-downs.
To Aaron and her eagle-eyed awareness of encoding challenges, that approach seemed inadequate. Why spend the same bandwidth to stream something as visually complex as an action movie with car chases (lots of motion) and explosions (flashing lights and all that noisy smoke) as much simpler visual fare? “You need less bits for animation,” explained Aaron.
My Little Pony, which was a hit on the service at the time, simply didn’t have the same visual complexity as live-action titles. It didn’t make sense to use the same encoding recipes for both. That’s why, in 2015, Netflix began re-encoding its entire catalog with settings fine-tuned per title. With this new, title-specific approach, animated fare could be streamed in 1080p with as little as 1.5 Mbps.
Switching to per-title encoding resulted in bandwidth savings of around 20 percent on average — enough to make a notable difference for consumers in North America and Europe, but even more important as Netflix was eyeing its next chapter: in January of 2016, then-CEO Reed Hastings announced that the company was expanding into almost every country around the world — including markets with subpar broadband infrastructure and consumers who primarily accessed the internet from their mobile phone.
Per-title encoding has since been adopted by most commercial video technology vendors, including Amazon’s AWS, which used the approach to optimize PBS’s video library last year. But while the company’s encoding strategy has been wholeheartedly endorsed by streaming tech experts, it has been largely met with silence by Hollywood’s creative class.
Directors and actors like Judd Apatow and Aaron Paul were up in arms when Netflix began to let people change the playback speed of its videos in 2019. Changes to the way it encodes videos, on the other hand, never made the same kinds of headlines. That may be because encoding algorithms are a bit too geeky for that crowd, but there’s also a simpler explanation: the new encoding scheme was so successful at saving bandwidth without compromising on visual fidelity that no one noticed the difference.
Make that almost no one: Aaron quickly realized that the company’s per-title-based encoding approach wasn’t without faults. One problem became apparent to her while watching Barbie Dreamhouse Adventures. It’s one of those animated Netflix shows that was supposed to benefit the most from a per-title approach.
However, Netflix’s new encoding struggled with one particular scene. “There’s this guy with a very sparkly suit and a sparkly water fountain behind him,” said Aaron. The scene looked pretty terrible with the new encoding rules, which made her realize that they needed to be more flexible. “At (other) parts of the title, you need less bits,” Aaron said. “But for this, you need to increase it.”
The solution to this problem was to get a lot more granular during the encoding process. Netflix began to break down videos by shots and apply different encoding settings to each individual segment in 2018. Two people talking in front of a plain white wall were encoded with lower bit rates than the same two people taking part in a car chase; Barbie hanging out with her friends at home required less data than the scene in which Mr. Sparklesuit shows up.
As Netflix adopted 4K and HDR, those differences became even more stark. “(In) The Crown, there’s an episode where it’s very smokey,” said Aaron. “There’s a lot of pollution. Those scenes are really hard to encode.” In other words: they require more data to look good, especially when shown on a big 4K TV in HDR, than less visually complex fare.
Aaron’s mind never stops looking for those kinds of visual challenges, no matter whether she watches Netflix after work or goes outside to take a walk. This has even caught on with her kids, with Aaron telling me that they occasionally point at things in the real world and shout: “Look, it’s a blur!”
It’s a habit that comes with the job and a bit of a curse, too — one of those things you just can’t turn off. During our conversation, she picked up her phone, only to pause and point at the rhinestone-bedazzled phone case. It reminded her of that hard-to-encode scene from Barbie Dreamhouse Adventures. Another visual challenge!
Still, even an obsessive mind can only get you so far. For one thing, Aaron can’t possibly watch thousands of Netflix videos and decide which encoding settings to apply to every single shot. Instead, her team compiled a few dozen short clips sourced from a variety of shows and movies on Netflix and encoded each clip with a range of different settings. They then let test subjects watch those clips and grade the visual imperfections from not noticeable to very annoying. “You have to do subjective testing,” Aaron said. “It’s all based on ground truth, subjective testing.”
The insights gained this way have been used by Netflix to train a machine learning model that can analyze the video quality of different encoding settings across the company’s entire catalog, which helps to figure out the optimal settings for each and every little slice of a show or movie. The company collaborated with the University of Southern California on developing these video quality assessment algorithms and open-sourced them in 2016. Since then, it has been adopted by much of the industry as a way to analyze streaming video quality and even gained Netflix an Emmy Award. All the while, Aaron and her team have worked to catch up with Netflix’s evolving needs — like HDR.
“We had to develop yet another metric to measure the video quality for HDR,” Aaron said. “We had to run subjective tests and redo that work specifically for HDR.” This eventually allowed Netflix to encode HDR titles with per-shot-specific settings as well, which the company finally did last year. Now, her team is working on open-sourcing HDR-based video quality assessment.
Slicing up a movie by shot and then encoding every slice individually to make sure it looks great while also saving as much bandwidth as possible: all of this work happens independently of the video codecs Netflix uses to encode and compress these files. It’s kind of like how you might change the resolution or colors of a picture in Photoshop before deciding whether to save it as a JPEG or a PNG. However, Netflix’s video engineers have also actively been working on advancing video codecs to further optimize the company’s streams.
Netflix is a founding member of the Alliance for Open Media, whose other members include companies like Google, Intel, and Microsoft. Aaron sits on the board of the nonprofit, which has spearheaded the development of the open, royalty-free AV1 video codec. Netflix began streaming some videos in AV1 to Android phones in early 2020 and has since expanded to select smart TVs and streaming devices as well as iPhones. “We’ve encoded about two-thirds of our catalog in AV1,” Aaron said. The percentage of streaming hours transmitted in AV1 is “in the double digits,” she added.
And while the roll-out of AV1 continues, work is already underway on its successor. It might take a few more years before devices actually support that next-gen codec, but early results suggest that it will make a difference. “At this point, we see close to 30 percent bit rate reduction with the same quality compared to AV1,” Aaron explained. “I think that’s very, very promising.”
While contributing to the development of new video codecs, Aaron and her team stumbled across another pitfall: video engineers across the industry have been relying on a relatively small corpus of freely available video clips to train and test their codecs and algorithms, and most of those clips didn’t look at all like your typical Netflix show. “The content that they were using that was open was not really tailored to the type of content we were streaming,” recalled Aaron. “So, we created content specifically for testing in the industry.”
In 2016, Netflix released a 12-minute 4K HDR short film called Meridian that was supposed to remedy this. Meridian looks like a film noir crime story, complete with shots in a dusty office with a fan in the background, a cloudy beach scene with glistening water, and a dark dream sequence that’s full of contrasts. Each of these shots has been crafted for video encoding challenges, and the entire film has been released under a Creative Commons license. The film has since been used by the Fraunhofer Institute and others to evaluate codecs, and its release has been hailed by the Creative Commons foundation as a prime example of “a spirit of cooperation that creates better technical standards.”
Cutting-edge encoding strategies, novel quality metrics, custom-produced video assets, and advanced codecs: in many ways, Netflix has been leading the industry when it comes to delivering the best-looking streams in the most efficient ways to consumers. That’s why the past 14 months have been especially humbling.
Netflix launched its very first livestream in March of 2023, successfully broadcasting a Chris Rock comedy special to its subscribers. A month later, it tried again with a live reunion event for its reality show Love Is Blind — and failed miserably, with viewers waiting for over an hour for the show to start.
The failed livestream was especially embarrassing because it tarnished the image of Netflix as a technology powerhouse that is lightyears ahead of its competition. Netflix co-CEO Greg Peters issued a rare mea culpa later that month. “We’re really sorry to have disappointed so many people,” Peters told investors. “We didn’t meet the standard that we expect of ourselves to serve our members.”
Netflix wants to avoid further such failures, which is why the company is playing it safe and moving slowly to optimize encoding for live content. “We’re quite early into livestreaming,” Aaron said. “For now, the main goals are stability, resilience of the system, and being able to handle the scale of Netflix.” In practice, this means that Aaron’s team isn’t really tweaking encoding settings for those livestreams at all for the time being, even if it forces her to sit through the livestream of the SAG Awards show without being able to improve anything. “We’re starting with a bit more industry-standard ways to do it,” she told me. “And then from there, we’ll optimize.”
The same is true in many ways for cloud gaming. Netflix began to test games on TVs and desktop computers last summer and has since slowly expanded those efforts to include additional markets and titles. With games being rendered in the cloud as opposed to on-device, cloud gaming is essentially a specialized form of livestreaming, apart from one crucial distinction. “They’re quite different,” said Aaron. “[With] cloud gaming, your latency is even more stringent than live.”
Aaron’s team is currently puzzling over different approaches to both problems, which requires them to ignore much of what they’ve learned over the past decade. “The lesson is not to think about it like VOD,” Aaron said. One example: slicing and dicing a video by shot and then applying the optimal encoding setting for every shot is a lot more difficult when you don’t know what happens next. “With live, it’s even harder to anticipate complex scenes,” she said.
Live is unpredictable: that’s not just true for encoding but also for Netflix’s business. The company just inked a deal to show two NFL games on Christmas Day and will begin streaming weekly WWE matches in January. This happens as sports as a whole, which has long been the last bastion of cable TV, is transitioning to streaming. Apple is showing MLS games, Amazon is throwing tons of money at sports, and ESPN, Fox, and Warner Bros. are banding together to launch their own sports streaming service. Keeping up with these competitors doesn’t just require Netflix to spend heavily on sports rights but also actually get good at livestreaming.
All of this means that Aaron and her team won’t be out of work any time soon — especially since the next challenge is always just around the corner. “There’s going to be more live events. There’s going to be, maybe, 8K, at some point,” she said. “There’s all these other experiences that would need more bandwidth.”
In light of all of those challenges, does Aaron ever fear running out of ways to optimize videos? In other words: how many times can Netflix re-encode its entire catalog with yet another novel encoding strategy, or new codec, before those efforts are poised to hit a wall and won’t make much of a difference anymore?
“In the codec space, people were saying that 20 years ago,” Aaron said. “In spite of that, we still find areas for improvement. So, I’m hopeful.”
And always eagle-eyed to spot the next visual challenge, whether it’s a sea of camera flashes or a surprise appearance by Mr. Sparklesuit.
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Congress narrowly voted to fund President Donald Trump’s mass deportation agenda, giving the Department of Homeland Security $70 billion over the next three years.
The house voted 214 to 212 in favor of the reconciliation bill Tuesday, following the Senate’s 52-47 vote last Friday morning. The vote fell largely along party lines. Sen. Lisa Murkowski (R-AK) was the only Senate Republican to vote against it. Rep. Tim Walberg (R-MI), initially voted against the bill — meaning it would have failed — but changed his vote after huddling with House Majority Leader Steve Scalise (R-LA) and Appropriations Chair Tom Cole (R-OK), according to The Hill. No Democrats voted in favor of the funding bill, which was done through a budget reconciliation process to avoid a Democratic filibuster.
In a speech on the House floor ahead of the Tuesday vote, Rep. Mary Gay Scanlon (D-PA) criticized Republicans for using the budget reconciliation process to avoid negotiating with Democrats, and emphasized ICE’s lack of popularity with the American people.
“At its core, this Republican reconciliation budget bill is a statement about priorities, and the priorities represented in this budget bill could not be more out of step with the needs and values of the American people,” Scanlon said.
Scanlon noted that DHS has yet to spend $100 billion of the nearly $200 billion it received under Trump’s One Big Beautiful Bill Act. She added that Trump has not only expanded ICE’s reach by increasingly going after legal immigrants but also weaponized DHS against its critics. The bill, she said, will “supercharge” Trump’s abuses.
After the House markup last Friday, Rep. Rosa DeLauro (D-CT), ranking member of the House Appropriations Committee, noted that the bill not only lacks sufficient reforms but also cuts funding for cybersecurity and TSA, whose workers went weeks without pay during the DHS shutdown.
The funding bill comes at a time of deep unpopularity for ICE. One recent poll found that just 33 percent of voters approve of how the agency is doing its job.
And it comes amid yet another threat from border czar Tom Homan to flood New York City with ICE agents. In an interview with Fox News on Monday, Homan said he would send “more ICE agents than you’ve ever seen” to New York City if the state government passed a bill limiting cooperation with DHS.
“Providing a quarter trillion dollars to an administration promising that the public ‘ain’t seen shit yet’ when it comes to mass deportation is a historic mistake,” Todd Schulte, president of the immigration reform group FWD.us, said in a statement. “Supercharging the funding for these already out of control systems will come with terrible human consequences and continue to be met with increasing opposition from voters.”
Correction, June 9th: A previous version of this story said Rep. Tim Walberg voted against the funding bill. He initially voted against it but then changed his vote to support it.
Update, June 9th: This story has been updated to include comment from FWD.us president Todd Schulte.
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Food prices have a way of sneaking up on you. One week, your usual grocery run feels normal. The next week, a few basics suddenly cost a lot more than you expected.
That is why money-saving food apps are worth a closer look. All of these apps are free to download or sign up for, but you still pay for any food, groceries or purchases you make through them.
Some help you find discounted groceries before stores toss them. Others connect you with surprise meals, receipt rewards, free local listings or recipes based on what you already have at home.
The trick is knowing which app fits the way you actually shop. Here are eight apps that can help you stretch your food budget, reduce waste and maybe make your next receipt feel a little less painful.
10 THINGS TO STOP PAYING FOR TO SAVE MONEY NOW
Food savings apps can help shoppers find discounted groceries, restaurant meals, receipt rewards and free local food listings. (iStock)
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1) Flashfood
Flashfood helps you find discounted groceries from participating stores near you. The app focuses on food that is still good but getting close to its best-by date. You browse local deals in the app, pay through the app and pick up your order in the store. Flashfood says shoppers can find grocery deals for up to 50% off. That can include produce, meat, dairy, pantry items and other staples, depending on what stores near you have available.
- Best for: Discounted grocery pickup.
- How you save: Buy marked-down groceries from participating stores before they go to waste.
- Good to know: Availability depends on participating stores near you.
2) Misfits Market
Misfits Market delivers groceries to your door. The company says it offers high-quality rescued foods and lets you choose what goes in your order. After signing up, you receive a weekly shopping window. You can review your cart, remove items, add groceries and skip orders when needed. This can work well if you want grocery delivery and like the idea of reducing food waste at the same time. Misfits Market says there are no subscription fees or order obligations. You can skip, pause or cancel.
- Best for: Grocery delivery with rescued food.
- How you save: Order discounted groceries, including rescued or excess food, delivered to your door.
- Good to know: Delivery depends on your ZIP code. Misfits Market says it serves nearly every ZIP code in the contiguous U.S., with limited service in select areas.
Misfits Market lets you customize grocery deliveries with rescued or excess food that may cost less than traditional shopping.
3) Too Good To Go
Too Good To Go helps you buy surplus food from nearby restaurants, bakeries, cafés and stores. The app uses “Surprise Bags,” which means you usually know the type of food and pickup window, but not every exact item inside. That surprise part can be fun, especially if you like trying local spots. It can also be less ideal if you need a very specific dinner plan. Too Good To Go says users can save and enjoy food at half price or less.
- Best for: Discounted restaurant and bakery food.
- How you save: Buy discounted Surprise Bags from local restaurants, bakeries, cafés and stores.
HEALTH-CONSCIOUS AMERICANS EMBRACE YUKA APP TO GUIDE GROCERY SHOPPING CHOICES
Food savings apps work best when they match how you already shop, pick up food, save receipts or plan meals. (David Paul Morris/Bloomberg via Getty Images)
4) Olio
Olio connects people locally so they can give away food and other useful items. The app says you can browse free food from local shops and neighbors. You may also find books, toys, toiletries and household items. This one feels more community-based than a regular coupon app. It can be especially helpful if you live in an active area where neighbors and local shops often post.
- Best for: Free local food and household items.
- How you save: Find free food and household items shared by neighbors or local businesses.
- Good to know: Results depend heavily on your local community.
5) SuperCook
SuperCook helps you turn the food already in your kitchen into meals. You enter the ingredients you have at home, and the app suggests recipes you can make. That can save money in a different way. Instead of buying more groceries, you may find a way to use the half bag of rice, frozen vegetables or canned beans you already paid for.
- Best for: Using up food you already have.
- How you save: Turn ingredients you already have into meals, so you can avoid another grocery run.
- Good to know: This one does not give cash back. It helps you avoid extra spending and food waste.
6) Ibotta
Ibotta gives you cash back on eligible purchases. Before you shop, you add cash-back offers in the app. After shopping in-store, you submit your receipt. Ibotta says you can withdraw earnings once you reach $20. It’s great because it can work with groceries and other everyday purchases. The key is remembering to add offers before you shop and submit your receipt after.
- Best for: Grocery cash back.
- How you save: Earn cash back on eligible grocery and everyday purchases after you submit receipts.
- Good to know: You need to match the right offers and follow the redemption steps.
7) Fetch
Fetch turns receipts into points. You shop, snap receipts and earn points that can be redeemed for gift cards. Fetch says you can earn points from in-store or online shopping, plus offers from participating brands. This app can be simple because you do not always need to pick offers before you shop. Still, special offers can help you earn more points.
- Best for: Turning receipts into gift cards.
- How you save: Snap receipts to earn points you can redeem for gift cards.
- Good to know: Points vary by receipt, brands and offers.
Fetch turns receipts into points you can redeem for gift cards from popular retailers.
10 TECH UPGRADES TO SAVE YOUR TIME, PRIVACY AND MONEY
Receipt rewards apps such as Ibotta, Fetch and Upside can help shoppers earn cash back or gift cards on eligible purchases. (SDI Productions/Getty Images)
8) Upside
Upside is best known for gas savings, but it can also work for groceries and restaurants where offers are available. You open the app, claim a cash-back offer near you, shop as usual and pay with a credit or debit card.
- Best for: Cash back on groceries, gas and dining.
- How you save: Claim cash-back offers on gas, groceries and restaurants at participating locations.
- Good to know: Grocery and restaurant offers depend on participating locations near you.
For direct links to each app and any available CyberGuy savings codes, visit CyberGuy.com and search for “8 apps that can help you cut your food bill.”
Which app should you try first?
Start with the app that fits your normal routine. If you already shop at grocery stores in person, try Flashfood or Ibotta. If you save receipts anyway, Fetch is an easy add-on. If you order groceries online, Misfits Market may be worth checking. If you like trying local food, Too Good To Go can be a fun way to save. If your fridge is full, but dinner still feels impossible, SuperCook may help you avoid another grocery run. For gas and food cash back in one place, Upside deserves a look. For free local food and community sharing, Olio may surprise you, depending on where you live.
A few smart tips before using food savings apps
Before you download every app on this list, take a moment to think about your habits. First, check whether the app works in your area. Some apps depend on local stores, restaurants or community activity. If there are no nearby offers, the app may not help much yet.
Next, watch pickup windows. Apps like Flashfood and Too Good To Go can save you money, but they also require timing. If you miss the pickup, you may lose the deal. Also, avoid buying food only because it looks cheap. A discounted item saves money only if you actually use it. Finally, read the app’s privacy settings. These apps often work through location, receipts, purchases and rewards accounts. Use only the permissions you feel comfortable sharing.
Kurt’s key takeaways
Food savings apps can help, but they work best when they match your real life. Flashfood and Too Good To Go are great for deal hunters who can pick up food nearby. Misfits Market works better for people who want groceries delivered. Ibotta, Fetch and Upside can help you earn something back from purchases you already make. SuperCook and Olio come at savings from a different angle. One helps you use what you already bought. The other connects you with local people and shops that share food and useful items. The biggest takeaway? Do not let the app make you spend more. Use it as a tool, not a temptation.
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MacOS 27 Golden Gate will usher in a bunch of changes to the Mac when it’s released later this year, with its biggest new features revolving around Siri AI. But for now, using the first developer beta, Siri AI is only offered through a waitlist. So what’s available to try is mostly about how the upcoming operating system looks and feels.
You’re not welcomed with any fanfare when you boot up the macOS 27 developer beta (that’ll probably come later), but there’s reason to celebrate. Jump to the appearance settings, and you find that Apple now has a Liquid Glass slider, allowing users to set the amount of UI transparency in macOS. On one end of the slider, it’s as seethrough as Liquid Glass gets, and on the other end the transparent accents are heavily frosted. Golden Gate starts you in the middle of the slider by default, for just a touch of frosting — perhaps a gentle admission that the original look went too far. You sadly can’t go fully opaque, but this frosted look does greatly reduce the distracting elements of Liquid Glass.
After spending just a short while with Golden Gate, I already prefer the minimum transparency look. I’d crank that slider in the full version and never turn back. For the strongest Liquid Glass haters out there, the Reduce Transparency option is still available in the Accessibility settings, but using it is like taking a hammer to all that glass — introducing lots of harsh gray and black backgrounds to the dock, Menu Bar, and Control Center.
The absolute wins for macOS 27’s design is the return of edge-to-edge sidebars with colorful icons and the increased corner radii of windows across the OS. The former is basically a backtrack to the way sidebars used to look (which looked better and easier to parse, with less wasted space). And the latter is just logical. How on Earth did Apple get so high on its own design supply that it allowed windowed apps to have mismatched corners?
I do have my nitpicks — the new battery icon taken from iOS is less legible (really, I hate it). Also, after Apple finally added the most basic window snapping feature in Sequoia, it hasn’t refined it one bit. Both Tahoe and now Golden Gate are leaving me wanting better and faster tiling controls like Windows 11, as well as the simple ability to rename virtual desktops. But so far, nothing.
Apple says Golden Gate is supposed to feel snappier, with faster search indexing. It’s too early to tell how much of a difference this makes on the MacBook Neo I’m testing it on — especially since dev betas are notoriously buggy and unstable. Using Spotlight search for local files on Golden Gate performed similar to another Neo I had on-hand running macOS 26 Tahoe. And opening apps on both systems side-by-side led to mixed results: Golden Gate opened Lightroom Classic and Slack faster, but Tahoe was faster to open Photoshop and Steam. I hope Apple’s under the hood improvements to memory and CPU usage will really show on the MacBook Neo, which could use all the efficiency it can get, but the jury’s out for now.
There’s still more to come with further beta releases of macOS 27, where we’ll at some point be able to fully test Siri AI, Visual Intelligence, and the revamped Spotlight Search. Last year’s power user-focused Spotlight with clipboard history was a nice improvement, but I’m skeptical that Siri AI being baked into Spotlight will be quite the gamechanger Apple’s billing it as. I’ll keep an open mind and be looking to find out once I’m off the waitlist.
For now, I’m relieved Apple is slightly backpedaling on Liquid Glass. While the look was never quite as bad on the Mac as it was on iOS, it’s a welcome change to be able to turn down these transparencies and get a little closer to the old looks from Sequoia. That and the other bits of UI polish are a nice upgrade on their own. Now, Apple has to show that it can nail all the new AI features, too — I’m eager to see how it fares.
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