Industry benchmarks are important because, no matter that comparisons are odious, IT organizations nonetheless have to make them to plot out the architectures of their future systems. …
There are a lot of things that compute engine makers have to do if they want to compete in the datacenter, but perhaps the most important thing is to be consistent. …
Expect to hear increasing buzz around graph neural network use cases among hyperscalers in the coming year. …
Machine learning inference models have been running on X86 server processors from the very beginning of the latest – and by far the most successful – AI revolution, and the techies that know both hardware and software down to the minutest detail at the hyperscalers, cloud builders, and semiconductor manufacturers have been able to tune the software, jack the hardware, and retune for more than a decade. …
It has been a long time coming. Over two years, in fact. …
Four years ago, Cloudian was a six-year-old startup in an object storage space that, while the technology had been around for more than a decade, was seeing a surge of interest from cloud providers desperate for a storage architecture that only could scale to meet the demands of their rapidly growing datacenters, the massive amounts of data that was being generated and the need to be able to more easily move it between core on-premises datacenters and multiple cloud environments – and in the coming years the edge. …
Machine learning techniques based on massive amounts of data and GPU accelerators to chew through it are now almost a decade old. …
Amazon Web Services, the juggernaut of cloud computing, may be forging its own path with Arm-based CPUs and associated DPUs thanks to its 2015 acquisition of Annapurna Labs for $350 million. …
We have a good sense of what projects U.S. companies open source but when it comes to Chinese webscale companies, most notably the big three—Baidu, Alibaba, and Tencent—that ecosystem is less public and not often discussed. …
One of the great things about the database market is that there are many different kinds of data and the problems that need to be addressed to store, organize, and query that data are also increasing with the speed and amount of data stored. …
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