By Ed Scannell
Bigger, faster and stronger were the watchwords for many top-tier hardware manufacturers over the first half of this year, delivering products largely aimed at driving greater performance of AI and machine learning-based systems.
Either through acquisitions, partnerships or their own invention, companies including IBM, HPE and NVIDIA delivered or promised to deliver a wide array of AI hardware offerings, ranging from supercomputers to souped-up board-level products crammed with performance accelerators to servers that proposed to deliver futuristic technologies to the IT world now.
After 30 years of research and development, IBM finally delivered the industry’s first integrated quantum computer, the 20-qubit IBM Q System One. While Big Blue delivered the complete hardware-software-communications package, including an SDK for corporate developers and a 9-foot airtight glass-paneled cube to house the system, it will be some time before IT personnel have the necessary skills to deliver exploitive commercial applications.
That lack of experience, coupled with the high cost of maintaining the system on-premises, means IBM will deliver quantum capabilities to customers via cloud-based services. IBM officials expect to make a 50-qubit system available to developers later this year, which should allow developers to create more meaningful applications.
But chip companies are running out of real estate to cram in more transistors. This has given rise to a wide variety of support chips, most notably GPUs, and other board-level sub-systems that are rapidly becoming standard componentry in server hardware. All of this aimed at churning AI and machine learning workloads faster.