After months of speculation that Microsoft was developing its own semiconductors, the company at its annual Ignite conference Wednesday took the covers off two new custom chips, dubbed the Maia AI Accelerator and the Azure Cobalt CPU, which target generative AI and cloud computing workloads, respectively.\n\nThe new Maia 100 AI Accelerator, according to Microsoft, will power some of the company's heaviest internal AI workloads running on Azure, including OpenAI\u2019s model training and inferencing workloads.\n\nSam Altman, the CEO of Microsoft-backed OpenAI, claimed in a news release that the custom Maia chip has paved the way for the AI company to train more capable models in a way that will result in lower costs for end customers.\n\nAnalysts agreed with that assessment. \u201cMicrosoft is creating their own AI processors to improve the performance per watt and performance per dollar versus Nvidia\u2019s offerings,\u201d said Dylan Patel, chief analyst at semiconductor research and consulting firm Semianalysis. The reduction in cost will ultimately be passed on to customers subscribing to Azure\u2019s AI and generative AI offerings, he said.\n\nThe Azure Cobalt 100 CPU, which is built on Arm architecture, is also an attempt by Microsoft to make its infrastructure more energy efficient when compared to commercial AMD and Intel CPUs, according to Patel.\n\nThe Arm architecture of Cobalt 100 CPU allows Microsoft to generate more computing power for each unit of energy consumed, the company said, adding that these chips will be used across its data centers.\n\n\u201cWe\u2019re making the most efficient use of the transistors on the silicon. Multiply those efficiency gains in servers across all our datacenters, it adds up to a pretty big number,\u201d Wes McCullough, corporate vice president of hardware product development at Microsoft, said in a news release.\n\nMicrosoft is announcing the news at a time when public cloud spending is expected to grow significantly.\n\nEnd-user spending on public cloud services is forecast to grow 20.4% to total $678.8 billion in 2024, up from $563.6 billion in 2023, according to a report from Gartner.\n\nNew way to cool the new Maia 100 Accelerator chips\n\nMicrosoft had to create a new design for its data center racks to house the Maia 100 Accelerator chips inside its data centers. The racks, which are wider than existing ones, have been expanded to leave ample space for both power and networking cables, the company said, adding that a separate liquid cooling solution, different that the existing air-cooling methods, had to be designed to manage the temperature of the chips due to intensive AI and generative AI workloads.\n\nTo implement liquid cooling, Microsoft has developed a \u201csidekick\u201d that sits next to the Maia 100 chips\u2019 rack. These sidekicks, according to Microsoft, work a bit like a radiator in a car.\n\n\u201cCold liquid flows from the sidekick to cold plates that are attached to the surface of Maia 100 chips. Each plate has channels through which liquid is circulated to absorb and transport heat. That flows to the sidekick, which removes heat from the liquid and sends it back to the rack to absorb more heat, and so on,\u201d a company spokesperson said.\n\nEconomics, sustainability key drivers of custom chips\n\nEconomics, and not chip shortages, are the key driver for custom chips for large cloud service providers, such as Microsoft, AWS, and Google, according to analysts.\n\n\u201cMicrosoft\u2019s decision to develop custom silicon, from the point of view of economics, allows it to integrate its offerings and enables the company to continue to optimize silicon for its services while also increasing margin and having better control of costs and availability,\u201d said Daniel Newman, CEO of The Futurum Group.\n\nThese same reasons, according to Newman, resulted in AWS developing its own custom chips. While AWS has its Inferentia chips paired with the Trainium machine learning accelerator, Google has been developing iterations of its Tensor chips. \n\n\u201cThe Cobalt CPU is all about Microsoft offering cloud optimized silicon and being able to offer Arm based instances to Azure customers much the way AWS is with EC2,\u201d Newman said.\n\nAdditionally, analysts believe that the new chips provide a window of opportunity for Microsoft to build its own AI accelerator software frameworks as demand for AI or generative AI grows further.\n\n\u201cBuilding accelerators for AI workloads will be a way to improve performance while using less power than other chips such as graphics processing units (GPUs). Increasing performance while being energy efficient will continue to be more important for vendors and enterprises as attempt to meet sustainability goals and benefit from the potential of AI,\u201d Newman said.Custom chips to give Nvidia, AMD and Intel a run for their money\n\nMicrosoft\u2019s new custom chips are not powerful enough to replace GPUs from Nvidia for the purposes of developing large language models. But they are well-suited for inferencing \u2014 being used in operational AI workloads \u2014 and as they roll out they will reduce the need for the company to use chips from Nvidia, AMD and Intel, analysts said, adding that custom chips from AWS and Google will also challenge chipmakers in the future.\n\n\u201cIntel, NVIDIA, and AMD are all seeing the rise of Arm based instances and should see them as a competitive threat in certain instances,\u201d Newman said.\n\nThe migration of workloads from x86 architecture chips to Arm isn't plug and play yet \u2014 since software is often written for specific chip architectures \u2014 but has become less of a sticking point as developers continue to make progress in running more and more workloads on Arm, the Futurum Group's Newman said.\n\nAnalysts say that with cloud service providers using custom silicon at varying levels, the data center market will see a \u201cmore meaningful shift\u201d to Arm in the coming years despite x86 chips currently dominating market share by a substantial margin.\n\nAmong all chipmakers, Newman believes that Nvidia will be the least impacted, at least in the near term, as demand for its GPUs is set to remain elevated.\n\nHowever, in some instances or use cases the custom chips from cloud service providers may see a symbiotic relationship with Nvidia, especially the Grace Hopper chips, which are targeted towards developing and training large language models. \n\nMicrosoft\u2019s new custom chips are expected to start rolling out in early next year to its data centers. Since Microsoft does not plan to sell the chips to third parties, it will not have to deal with the restrictions imposed by the administration of US President Joe Biden on tech exports to China.