Apple’s new iPad Pro is thinner than an old iPod nano


We kicked off our Tuesday with an early iPad event. And what a beastly iPad we got. Apple shook things up by slotting its brand-new M4 chip into its new highest-end iPad Pro. Apple says the new device delivers 50 percent faster performance than the M2 iPad Pro. It supports dynamic caching, hardware-accelerated ray tracing and hardware-accelerated mesh shading — so, better-looking games and faster graphic processing.

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But that’s only half the story. The other major upgrade is Tandem OLED, which is a display of two OLED panels on top of each other. Expect richer colors and deeper blacks, but also brightness levels that max out at 1000 nits for standard and HDR and 1600 nits for HDR’s brightest spots. This switch in display tech makes it thinner than previous iPads. Actually, it ensures the new iPad pro is (somehow) thinner than the iPod nano.

The new iPad Pro starts at $999 for the 11-inch model and $1,299 for the 13-inch, each with 256GB of storage. We’ve already got our first impressions right here.

We also got new iPad Airs and an Apple Pencil Pro, for you professional scribblers.

— Mat Smith

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The latest Pixel A-series phone typically gets announced at Google I/O. However, to avoid distractions from all the other news, Google broke cover early. Compared to the standard Pixel 8, which has a 6.2-inch screen, the 8a features a slightly smaller 6.1-inch OLED display with noticeably larger bezels. But aside from that, the Pixel 8 and 8a are almost the exact same size. The 8a uses the same 64-megapixel and 13MP sensors for its main and ultra-wide cameras as its predecessor, but the Pixel 7a was a great camera phone, so no major complaints here. Sales start next week on May 14.

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OpenAI is trying to get ahead of the problem of these almost-real images circulating the internet by creating a toolset that detects images created by its own DALL-E 3 generator. The company says it can accurately detect pictures whipped up byDALL-E 3 98 percent of the time. While that sounds good, it’s loaded with caveats. The image has to be created by DALL-E, and it only successfully classified five to ten percent of images made by other AI models. It also struggles to spot generated images manually tweaked by a user.

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