After helping to define the modern internet era with Search and Android, Google is already at the forefront of the next wave in computing research and development: AI. Many consider artificial intelligence and neural network computers to be the next step in computing, enabling new use cases and faster computation to solve currently unsolvable problems. The search giant, which now calls itself an "AI first" company, has been leading adoption of these new technologies in a number of ways. Neural networking algorithms and machine learning are already at the heart of many of Google's services. They filter out spam in Gmail, optimize targeted advertising, and analyze your voice when you talk to Google Assistant or your Home speaker.

After helping to define the modern internet era with Search and Android, Google is already at the forefront of the next wave in computing research and development: AI. Many consider artificial intelligence and neural network computers to be the next step in computing, enabling new use cases and faster computation to solve currently unsolvable problems. The search giant, which now calls itself an "AI first" company, has been leading adoption of these new technologies in a number of ways. Neural networking algorithms and machine learning are already at the heart of many of Google's services. They filter out spam in Gmail, optimize targeted advertising, and analyze your voice when you talk to Google Assistant or your Home speaker.

Roundup Welcome to our roundup of major AI news from the past two weeks. Machine learning is so hyped right now, it doesn't help when companies such as Intel and Nvidia announce new chips and reveal little information about the specs, but make lofty claims of increased speed and precision. It's also difficult to keep track of all the different software frameworks and hardware options. Outfits like ARM, AMD, Amazon and Facebook are aware of this and are trying to make it easier to transfer models written in one language to another and optimize the models across various chips. Google's'surprise' Pixel 2 chip It's the first smartphone chip Google has ever designed, and it wasn't announced during the launch of the Pixel 2, which features the new silicon, because, er, it isn't enabled nor supported by applications yet.

The Google Pixel 2 and Pixel 2 XL devices, which were revealed earlier this month, are highly focused on imaging, just like their predecessors, the first Pixel devices. On Wednesday, the smartphone company released its first developer preview for Android 8.1 -- Oreo OS, which will make use of the Pixel 2 series' high-end camera capabilities. The Pixel 2 series builds on the success of the first Pixel devices, which were awarded the best smartphone camera of 2016 by DxOMark. The company has, in the past year worked with DxOMark on the cameras for the Pixel 2 and revealed the device on Oct. 4. One of the new features of the device is its neural networks API which is its artificial intelligence based software, that the company says will "enhance the on-device machine intelligence."

Google revealed the Pixel 2's and Pixel 2 XL's HDR and machine learning capabilities for computational computing will be the result of work by the Pixel Visual Core, the company's first-ever own-design co-processor. Together, they can perform more than 3 trillion calculations per second -- allowing for up to five times the processing speed for HDR at 10 percent of the power usage. It's able to glide between domain-specific languages (Halide for images and Google's TensorFlow for machine learning) to make things easier for third-party developers. The Pixel Visual Core will be enabled on Pixel 2 (and, presumably, Pixel 2 XL) devices with the Android 8.1 Oreo update (Maintenance Release 1) and third-party apps will be able to crack at code to harness the power of this new hardware. Rumors of Google developing its own mobile applications processor have been around for years.

The camera on the new Pixel 2 is packed full of great hardware, software and machine learning (ML), so all you need to do is point and shoot to take amazing photos and videos. One of the technologies that helps you take great photos is HDR, which makes it possible to get excellent photos of scenes with a large range of brightness levels, from dimly lit landscapes to a very sunny sky. HDR produces beautiful images, and we've evolved the algorithm that powers it over the past year to use the Pixel 2's application processor efficiently, and enable you to take multiple pictures in sequence by intelligently processing HDR in the background. In parallel, we've also been working on creating hardware capabilities that enable significantly greater computing power--beyond existing hardware--to bring HDR to third-party photography applications. To expand the reach of HDR, handle the most challenging imaging and ML applications, and deliver lower-latency and even more power-efficient HDR processing, we've created Pixel Visual Core.