Apple says that only it can conjure performance and battery life magic from PCs, because the electronics giant controls both the Mac OS and its processor mate, the M1 chip. Moreover, they say, they've just turned up their coordination to 11 to give new mobile PCs unveiled at CES last week an unprecedented leap in both battery savings and horsepower. Personal computers aren't dead yet: Laptops are showing new signs of life at CES Actually, you might say they've turned it up to 12 – that is, the Intel 12th-generation Core processors powering laptops running Microsoft Windows 11. And thanks to the two companies' extraordinary collaboration, they contend, new laptops like the new XPS 13 Plus from Dell, HP's Elite Dragonfly G3 and the Lenovo Yoga 9i 2-in-1 will fly with next-level speed all day on a single charge. Of course, there's no shortage of motivation for Intel and Microsoft to join forces these days.

We are happy to announce that Microsoft and Intel are partnering to bring optimized deep learning frameworks to Azure. These optimizations are available in a new offering on the Azure marketplace called the Intel Optimized Data Science VM for Linux (Ubuntu). Over the last few years, deep learning has become the state of the art for several machine learning and cognitive applications. Deep learning is a machine learning technique that leverages neural networks with multiple layers of non-linear transformations, so that the system can learn from data and build accurate models for a wide range of machine learning problems. Computer vision, language understanding, and speech recognition are all examples of deep learning at play today.

Artificial intelligence (AI) is spanning across server, desktop, and edge markets. Intel has AI solutions spanning server, desktop, and edge markets. From the CPU infrastructure, Intel Xeon processors, Intel Core processors, and Intel Atom processors providing the basis of AI processing, to dedicated acceleration provided by Intel Iris Graphics, the low wattage Intel Movidius vision processing unit (VPU), new Intel Gaussian Network Accelerator (GNA), Mobileye* automotive technology, and dedicated Intel field-programmable gate array (FPGA) custom integration, the Intel AI product offerings span the gamut of applications. Windows* Machine Learning (ML) is an inference engine running on the edge on the Windows operating system (OS) and provides a very simple developer interface that will be optimized under the hood for Intel hardware. Intel is working very closely with Microsoft to ensure that the hardware optimization using Windows ML are state of the art acceleration of model evaluation.

That was the question last week as Element.ai raised this hefty sum in a Series A funding. Investors included Microsoft, Nvidia, and Intel Capital, all of whom have their own AI ambitions. Element aims to make AI easy for businesses to use by connecting them with machine learning experts. And while Element may have brought together competitors Microsoft and Intel, the rivals have been fiercely staking their own claims with a flurry of investments and acquisitions. While these moves point to AI one day becoming ubiquitous for business tasks, Google's release of an academic paper called "One Model to Learn Them All" shows another route for machine learning to become commonplace.

Intel and Microsoft have been on something of an artificial intelligence (AI) investment binge of late, with the chip and software giants announcing a slew of deals this week via their respective VC arms -- Intel Capital and Microsoft Ventures. Perhaps the most notable of these was Element AI, which raised a gargantuan $102 million in what is one of the largest series A rounds in recent times. The Montreal-based startup, which helps connect companies with machine learning experts, drew in some other interesting investors besides Intel and Microsoft, including rival chipmaker Nvidia. The Element AI deal followed just a day after Intel and Microsoft joined forces for a $15 million investment into CognitiveScale, a Texas-based startup that uses AI to harness big data and deliver insights and recommendations. The very same day, Intel participated in a $16 million round into California-based robotic vision startup Aeye, while on Monday Microsoft got involved in a $20 million funding round into CrowdFlower, a platform that meshes machines with human input to ensure data science teams have access to properly tagged, clean data.

Taiwan's original design manufacturers (ODMs) grew up with Computex and put Taiwan on the map as a global PC hub. Companies that profited from the Taiwan ODMs' success were Intel and Microsoft, who played key roles in defining PC technology. This week, Nvidia is coming to Computex, in hopes of replicating what Intel and Microsoft achieved a few decades ago with the PC market. Nvidia's sole focus is domination in the new era of "accelerated computing." Nvidia defines accelerated computing as the increased use of a graphics processing unit together with a CPU to accelerate deep learning, analytics and engineering applications.