AI in the datacentres

This is getting incredibly complex. I usually don’t post links from TechCrunch- it is a glorified PR wire. However, this is a significant development. They are optimising the “workflows” and data distributions across the data centres because of the frequent outages. First consider this:

Microsoft and Meta join Google in using AI to help run their data centers – TechCrunch

“We have significant operational data from our data centers, in some areas at high frequency with built-in sensors in servers, racks, and in our data halls,” a Meta spokesperson told TechCrunch. “Each server and network device, taking on different workloads, will consume different amounts of power, generate different amounts of heat, and make different amounts of airflow in the data centers. Our [infrastructure] team collects all the data from each server and then develops AI models which can allocate our servers and racks in the data centers and send workloads into these servers to optimize [for] performance and efficiency.”

The data for outages:

Of course, companies have motivations aside from safety to ensure data centers remain in peak condition. Outages are expensive — and are becoming more frequent. According to a 2020 survey by the IT Uptime Institute, an IT consulting firm, a third of data center owners and operators admitted to experiencing a major outage over the past 12 months. One in six claimed that their outage cost them more than $1 million —  up from one in ten in 2019.

I can’t reliably comment, since the data isn’t public. This one is gleaned from a “survey” with its own attendant issues related to “recall” or wilful biases. There is an additional environmental impact of moving towards the cloud too:

The reduced environmental footprint is an added benefit of energy-regulating AI systems. Data centers consumed about 1% of the global electricity demand and contributed to 0.3% of all carbon dioxide emissions in 2020, according to a report from the Environmental Investigation Agency. And the typical data center uses 3 million to 5 million gallons of water per day, the same amount of water as a city of 30,000 to 50,000 people.

Are the efforts sustainable? Should you consider these in the next ESG impact studies? That’s an open question for interpretation, and offloading everything to the cloud also comes with significant challenges.

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