AI Demands Data Center Internals
Previously, we discussed the differences between AI Model building and AI Inference activities. We also talked about the location sensitivity[…]
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Category: Infrastructure
AI Model Training vs Inference: Key Infrastructure Differences
The infrastructure requirements for training AI foundation models and deploying them into production are vastly different, primarily due to the nature of the tasks they perform. One is a resource-intensive, one-off (or infrequent) process, while the other is a continuous, scalable, and low-latency operation. Understanding use is critical to understanding opportunities.
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The need to extend SIAM for the Digital Enterprise
In the new “as a Service” Enterprise, we talk aggressively about Service Integration becoming a combinator of core enterprise services,[…]
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Data Centers and the [Forced] March to an IaaS Utility
Simon Wardley has once again made me think seriously using his “Mapping” methodology as I try and think thru the[…]
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Finding Value in OpenSource
It seems a perpetual journey for me to help my employers understand the value associated with full participation with the[…]
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SDN for the Global Enterprise
For many in the enterprise, their relationship with their WAN carriers has been an opaque, long lead time, inflexible experience,[…]
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IT and SDDC, Agile Development and Release Management
For me, there have been a number of processes in typical IT that have been substantial challenges from a business[…]
Read moreIndustrializing Application Modernization
One of the things that I have learned and is a substantial challenge for enterprise technologists, is the exceedingly large[…]
Read moreAT&T and CSC join forces in “Journey to the Networked-Enterprise Cloud”
CSC & AT&T Announce Global Alliance CSC has been a recognized leader in Cloud Computing for the past 2 years[…]
Read moreRazor, Puppet, Hadoop and the CSC Cloud (pt2)
Using Razor to Boot the CSC Cloud (Part 2): Step 3: Configuring Razor The Image Catalog Running razor post installation[…]
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