GamingNews

Qualcomm teases new Snapdragon 865 and 765, announces 3D Sonic Max fingerprint scanner

December 4, 2019
On Tuesday, Qualcomm kicked off its annual Summit. On the first day, the chip maker teased two new upcoming chipsets on Qualcomm’s new Modular Platform. The Snapdragon 865 is the successor to the 855. Meanwhile, the Snapdragon 765/765G is a new chipset with integrated support for 5G. The Modular Platform part of the announcement offers carriers the tools to let them more easily implement their…
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MobileNews

Nokia 7.2's front camera found to be just average by DxOMark

December 4, 2019
The Nokia 7.2 is the latest upper-midrange smartphone from HMD Global, announced in September at IFA and going on sale in the meantime. DxOMark’s selfie camera testing has just finished for this device, and the result is anything but impressive. The Nokia 7.2’s…
MobileNews

Shopping apps for iOS see Black Friday boost as holiday spending shifts to smartphones

December 4, 2019
Now that Black Friday and Cyber Monday are in the books, we’re getting our first look at the data from the big holiday shopping weekend. Sensor Tower reports that Black Friday marked a major increase in downloads for shopping apps on the App Store. According to that data, the overall number of first-time app downloads in the Shopping category on the App Store increased 8% year-over-year. In…
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AI & RoboticsNews

OpenAI’s Procgen Benchmark prevents AI model overfitting

December 3, 2019
Where the training of machine learning models is concerned, there’s always a risk of overfitting — or corresponding too closely — to a particular set of data. In point of fact, it’s not infeasible that popular machine learning benchmarks like the Arcade Learning Environment encourage overfitting, in that they have a low emphasis on generalization. That’s why OpenAI — the San…
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AI & RoboticsNews

Google details AI that classifies chest X-rays with human-level accuracy

December 3, 2019
Analyzing chest X-ray images with machine learning algorithms is easier said than done. That’s because typically, the clinical labels required to train those algorithms are obtained with rule-based natural language processing or human annotation, both of which tend to introduce inconsistencies and errors. Additionally, it’s challenging to assemble data sets that represent an adequately diverse…
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