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


We started a year on Tuesday an early iPad event. And what a wild iPad we got. Apple has shaken things up by putting the new M4 chip in the 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 processing.

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But that’s only half the story. Another major improvement is Tandem OLED, which is the stacking of two OLED panels. Expect richer colors and deeper blacks, while brightness levels max out at 1,000 nits for standard and HDR and 1,600 nits for HDR highlights. This shift in screen technology makes it thinner than previous iPads. In fact, this makes the new iPad pro thinner than the iPod nano (sort of).

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 have already got our first impressions here.

We got it too the new iPad Airs and one Apple Pencil Profor you professional doodlers.

– Matt Smith

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The latest Pixel A series phone is usually announced at Google I/O. However, Google broke the cover early so as not to be distracted by all the other news. Compared to the standard Pixel 8, which has a 6.2-inch display, the 8a has a slightly smaller 6.1-inch OLED display with noticeably larger bezels. But other than that, the Pixel 8 and 8a are pretty much 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 will start next week on May 14.

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OpenAI is trying to tackle the problem with these near-real images floating around the web by creating a toolkit that detects images created by its DALL-E 3 generator. The company says it can identify images captured by the DALL-E 3 with 98 percent accuracy. While this sounds good, it is full of caveats. The image must be generated by DALL-E, and it successfully classified only five to ten percent of images generated by other AI models. It also has difficulty finding user-generated images that have been manually tweaked.

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