With Microsoft’s new partnerships, the pillars of the PC ecosystem have teamed up to challenge Apple’s dominance in the AI ecosystem.
Dreams of the Edge
At the recent Microsoft Build conference, the company expressed its desire to integrate AI into all its products. Developers were also incentivized to build AI features for Windows and other Microsoft products through the Hybrid AI Loop and Windows Olive for model optimization.
However, one important thing that stood out to us was the announcement of partnerships with AMD, Intel, NVIDIA, and Qualcomm to create new silicon optimized for AI computing.
Embracing the Power of Edge Computing
By working more closely with chip manufacturers, Microsoft seems to be pushing for more efficient inference on-device rather than relying on Azure to do so. Not only will this cut down the cost for Microsoft, but it will also equip the next generation of computers with neural processing units (NPUs). These chips are purpose-built for AI tasks and can perform them faster than general-purpose chips while remaining more efficient.
AMD and Microsoft Collaborate on AI Chips
AMD and Microsoft have already been reported as working together to create more capable AI chips. Reports have emerged that Microsoft is “providing support” to strengthen AMD’s AI chips.
While these were only rumors before the Windows AI announcement, they now seem to be coming to fruition.
Intel’s New Line of Chips with Neural Vision Processing Unit (VPU)
As part of the partnership, another company Intel has stated that its new line of Meteor Lake chips has a built-in neural vision processing unit or VPU. This will reportedly accelerate AI inference while working in software like Adobe Premiere Pro for more “effective machine learning.”
Apart from this, Intel has also added support for these chips on WinML and DirectML, so developers can directly address the new hardware.
NVIDIA Optimizes GPUs for AI Tasks
While NVIDIA has done its part in creating the AI compute market, it seems that it’s not completely done yet. As part of the partnership with Microsoft, NVIDIA has released updates to its driver software that will make RTX-enabled GPUs even faster at AI tasks.
By leveraging the GPUs’ in-built tensor cores, NVIDIA has promised performance improvements for ML models, such as a 2x improvement for Stable Diffusion.
Microsoft’s Robust Dev Chain for AI Tasks on Windows
Beyond the partnerships, Microsoft has been pouring resources into creating a robust dev chain for AI tasks on Windows. The biggest part of this is the ONNX runtime and tools like Windows Olive, which can help optimize models.
The WinML API also plays a huge role in facilitating AI development on the platform, as it provides an easy way to integrate ML capabilities into Windows applications.
Apple-Microsoft: Head-on-Head
While this partnership might seem like the Avengers of the tech world coming together, it seems that Thanos is sitting pretty, waiting for the battle. Apple has already set the stage for on-edge AI development workloads.
Apple-Microsoft: Clash of Titans
Ever since Apple moved to the SoC (system on chip) design for laptop chips, the Neural Engine has been a mainstay of its chips. In 2021, TensorFlow was updated with the capability to allow AI models to be trained on the ANE. According to Apple, this resulted in almost a 5x improvement in training times for common workloads like CycleGAN, Style Transfer, DenseNet, and more.
Microsoft Catching up with ANE Magic
Microsoft is trying to catch up to the M-series of chips by tying up with chipmakers to recreate the magic of ANE.
Developer Tools and Ecosystem
While the Neural Engine is one of the most important pieces of the puzzle, it is just one part of the story. Apart from releasing all its new laptops with AI compute on board, Apple has also been hard at work creating developer tools to leverage the ANE.
Microsoft’s Answer: WinML API
In a way, the WinML API is Microsoft’s answer to Apple’s Core ML library. WinML allows developers to leverage on-device processing capabilities to add ML to their applications.
Different Approaches, Same Market
As we can see, Apple and Windows may target the same market but in fundamentally different ways. With its lead in the market, privacy-preserving features, and on-device processing, it seems Apple might hold on to the lead for now.
On the other hand, Microsoft’s approach will bring AI to the masses, putting Windows devices on par with Apple’s for AI-focused tasks.
Pushing Towards an AI-Powered Future
While it might seem that this puts Apple and Windows head-to-head in the AI ecosystem, both companies are trying to stay on the curve. The market is progressing towards deploying AI at the edge, pushing system manufacturers to include AI capabilities in the devices.
Offering support and creating a developer ecosystem is a no-brainer for both these companies, which are leading personal computing toward an AI-powered future.
