We kicked off our Tuesday with an early iPad event. And what a beastly iPad we have. Apple shook things up by putting its brand new M4 chip in its new top-of-the-line 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 graphics.



But that’s only half the story. The other big upgrade is the 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 1,000 nits for standard and HDR and 1,600 nits for HDR highlights. This change in display technology makes it thinner than previous iPads. In fact, this ensures that the new iPad pro is (sort of) 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. And we already have our first impressions, right here.

We’ve also got new iPad Airs and Apple Pencil Pro for you professional doodlers.

— Matt Smith

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The latest Pixel A series phone is usually announced at Google I/O. However, to avoid being distracted by all the other news, Google revealed the 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 other than that, the Pixel 8 and 8a are almost the same size. The 8a uses the same 64-megapixel and 13-megapixel 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 14th.

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OpenAI is trying to get ahead of the problem with these near-real images circulating on the internet by creating a toolkit that detects images created by its own DALL-E 3 generator. The company says it can accurately recognize images obtained by the DALL-E 3 98 percent of the time. While this sounds good, it is full of caveats. The image must be created by DALL-E, and it successfully classifies only five to ten percent of the images made by other AI models. It also struggles to spot generated images manually modified by a user.

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