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Honorable MentionsNow that the majority of new headphones and earbuds offer at least a modicum of noise canceling, it’d be impossible (and unproductive) to list everything we like above. If you haven’t yet found your fit, here are more favorites worth considering.Beyerdynamic Amiron 300 for $280: These simple-looking earbuds (8/10, WIRED Recommends) are a great way to experience quiet luxury. They have 10 hours of battery life with noise canceling engaged, and they have some of the best-sounding drivers for vocals I’ve heard in any earbuds.Sony WF-1000XM5 earbuds for $298: Sony’s fifth-generation flagship earbuds (7/10, WIRED Recommends) slim down while stepping up. These buds are smaller and slicker (maybe too slick when it comes to grabbing them) than the previous XM4 buds. As before, they provide great sound and noise canceling that outduels plenty of options, with a cost to match. In true Sony style, they serve up a truckload of adaptive features and EQ controls while retaining a solid eight hours of playback time per charge with ANC and 12 hours without it. —Ryan WaniataSoundcore Life Q30 for $60-85: Anker’s Soundcore line is nothing if not value-conscious, and the Life Q30 provide an embarrassing list of extras for their bargain-basement pricing. You’ll get clear and warm sound, great features, tons of battery life, and noise canceling that gets the job done even on a long flight, though it can’t keep up with flagship pairs. It’s hard to complain when they cost hundreds less, especially with sale pricing that sometimes drops to around $50.Sony WH-1000XM4 for $250-350: Sony’s WH-1000X lineup has produced some of the best noise-canceling headphones for nearly a decade, and the aging WH-1000XM4 (9/10, WIRED Recommends) are no exception. They periodically go on sale for under $300, but it’s getting harder to find them below full price, which is tough for a five-year-old model.Bowers & Wilkins Pi8 Earbuds for $400: Bowers & Wilkins’ Pi8 (8/10, WIRED Recommends) offer a sleek, comfortable design, solid (albeit not Bose-beating) noise canceling, and great sound. Call quality is also excellent, which makes these perhaps the perfect business-class earbuds, though their hefty price won’t appeal to everyone.Bowers and Wilkins PX7 S2e for $400: The Px7 S2e feature upgraded audio quality for fantastic sound in stylish and sophisticated design. They’re also among the most comfortable headphones we’ve tested, but their noise canceling doesn’t rise to the level of the top players for the money.Beyerdynamic Aventho 300 for $400: These over-ears from Beyerdynamic (7/10, WIRED Recommends) have the brand’s classic studio sound, with a tight crisp high range and punchy lows. The downside is that they don’t cancel noise quite as well as models from Sony, Bose, and others above. Still, they sound great and are worth considering, especially if you can snag them on sale.Soundcore Space A40 for $60: Another top value buy from Anker’s Soundcore brand, the Space A40 (8/10, WIRED Recommends) are some of our favorite cheap earbuds, especially as their price continues to fall. You’ll find a classy design, lots of features, quality sound, and great noise canceling for their class.Apple Beats Fit Pro for $199: The Beats Fit Pro are an aging but still knockout pair of wireless buds, with great sound, easy-access physical buttons, and solid noise canceling to boot. Add to that six hours of battery life, spatial audio compatibility with Apple Music and other services, and you’ve got one of the best pairs of earbuds ever “designed in California.”Epos/Sennheiser Adapt 660 for $210: Want excellent sound, a comfortable fit, and high-quality noise-canceling tech for less than what you’d pay for Sony or Bose headphones? Check out this collaboration between Epos and Sennheiser. The Epos/Sennheiser Adapt 660 (8/10, WIRED Recommends) sound fantastic and are some of the lightest noise-canceling headphones I’ve ever worn. They also feature excellent microphones for great silence on calls and Zooms.

Google DeepMind has unveiled new artificial-intelligence software that could help historians recover the meaning and context behind ancient Latin engravings.  Aeneas can analyze words written in long-weathered stone to say when and where they were originally inscribed. It follows Google’s previous archaeological tool Ithaca, which also used deep learning to reconstruct and contextualize ancient text, in its case Greek. But while Ithaca and Aeneas use some similar systems, Aeneas also promises to give researchers jumping-off points for further analysis. To do this, Aeneas takes in partial transcriptions of an inscription alongside a scanned image of it. Using these, it gives possible dates and places of origins for the engraving, along with potential fill-ins for any missing text. For example, a slab damaged at the start and continuing with … us populusque Romanus would likely prompt Aeneas to guess that Senat comes before us to create the phrase Senatus populusque Romanus, “The Senate and the people of Rome.”  This is similar to how Ithaca works. But Aeneas also cross-references the text with a stored database of almost 150,000 inscriptions, which originated everywhere from modern-day Britain to modern-day Iraq, to give possible parallels—other catalogued Latin engravings that feature similar words, phrases, and analogies. 
This database, alongside a few thousand images of inscriptions, makes up the training set for Aeneas’s deep neural network. While it may seem like a good number of samples, it pales in comparison to the billions of documents used to train general-purpose large language models like Google’s Gemini. There simply aren’t enough high-quality scans of inscriptions to train a language model to learn this kind of task. That’s why specialized solutions like Aeneas are needed.  The Aeneas team believes it could help researchers “connect the past,” said Yannis Assael, a researcher at Google DeepMind who worked on the project. Rather than seeking to automate epigraphy—the research field dealing with deciphering and understanding inscriptions—he and his colleagues are interested in “crafting a tool that will integrate with the workflow of a historian,” Assael said in a press briefing. 
Their goal is to give researchers trying to analyze a specific inscription many hypotheses to work from, saving them the effort of sifting through records by hand. To validate the system, the team presented 23 historians with inscriptions that had been previously dated and tested their workflows both with and without Aeneas. The findings, which were published today in Nature, showed that Aeneas helped spur research ideas among the historians for 90% of inscriptions and that it led to more accurate determinations of where and when the inscriptions originated. In addition to this study, the researchers tested Aeneas on the Monumentum Ancyranum, a famous inscription carved into the walls of a temple in Ankara, Turkey. Here, Aeneas managed to give estimates and parallels that reflected existing historical analysis of the work, and in its attention to detail, the paper claims, it closely matched how a trained historian would approach the problem. “That was jaw-dropping,” Thea Sommerschield, an epigrapher at the University of Nottingham who also worked on Aeneas, said in the press briefing.  However, much remains to be seen about Aeneas’s capabilities in the real world. It doesn’t guess the meaning of texts, so it can’t interpret newly found engravings on its own, and it’s not clear yet how useful it will be to historians’ workflows in the long term, according to Kathleen Coleman, a professor of classics at Harvard. The Monumentum Ancyranum is considered to be one of the best-known and most well-studied inscriptions in epigraphy, raising the question of how Aeneas will fare on more obscure samples.  Google DeepMind has now made Aeneas open-source, and the interface for the system is freely available for teachers, students, museum workers, and academics. The group is working with schools in Belgium to integrate Aeneas into their secondary history education.  “To have Aeneas at your side while you’re in the museum or at the archaeological site where a new inscription has just been found—that is our sort of dream scenario,” Sommerschield said.

We’re launching Web Guide, a Search Labs experiment that uses AI to intelligently organize the search results page, making it easier to find information and web pages.Web Guide groups web links in helpful ways — like pages related to specific aspects of your query. Under the hood, Web Guide uses a custom version of Gemini to better understand both a search query and content on the web, creating more powerful search capabilities that better surface web pages you may not have previously discovered. Similar to AI Mode, Web Guide uses a query fan-out technique, concurrently issuing multiple related searches to identify the most relevant results.For example, try it for open-ended searches like “how to solo travel in Japan.” Or try detailed queries in multiple sentences like, “My family is spread across multiple time zones. What are the best tools for staying connected and maintaining close relationships despite the distance?”