Active Hackathon

Why Data Centers Should Utilise AI To Optimise Power Costs

data center power ai

Amid a global economic slowdown, companies are doing everything they can to cut costs. Energy consumption for data centres is topmost on everyone’s minds across the globe. So, optimising data centre costs amid rising demand for digital services is going to be crucial for 2020.

A data center building is a place where there are tens of components like servers, cooling gear, and networking, among others. Running of the data center is controlled by a combined functioning of all data center components, allowing several designs to coordinate together.


Sign up for your weekly dose of what's up in emerging technology.

This, in turn, needs vital means to keep them cool. In the past, this has driven businesses to make them at sea or picking locations with lower temperatures, like in Europe. At the same time, AI can also help decrease the amount of power data centers use for cooling, regardless of the location.

Why This Is Important

Energy consumption by data centers may become a costly affair for the tech industry. Along with these data centers, companies also need to hire skilled specialists to maintain and monitor data centers. Operating data centers and hiring staff can be expensive for every organisation. 

Furthermore, supervising and managing teams is an extra task. Therefore, organisations are continually looking for better options for conventional manual systems.

Even though there are cooling systems, nonetheless, they cannot run at the ideal effectiveness point. New AI-based systems leverage deep learning to figure out how to draw the fitting relationships between different types of cooling gear with IT workloads and condition factors. 

AI frameworks accomplish this by breaking down a huge measure of historical data and their effect on energy utilisation to produce predictive modeling, using specific parameters that are transmitted to different control frameworks. By gathering data from the power supply framework, AI-fueled systems can foresee approaching equipment failures to caution staff early.

What Google Did

In this regard, Google has also figured out the best way to alter cooling frameworks — fans, ventilation, and other hardware — to bring down power utilisation. Google’s system recently made proposals to its data center administrators, leading to around 40% cost cuts in those cooling frameworks. 

Developed in collaboration with DeepMind, Google’s algorithm employs a method known as reinforcement learning, which learns by trial and error. This led to AlphaGo, the DeepMind program which defeated human professionals of the board game Go.

DeepMind served its new algorithm data collected from Google data centers and allowed it to discover what cooling systems would decrease energy expenditure. The project could produce millions of dollars in electricity savings and may help the company reduce its carbon footprint, according to Google.

More Great AIM Stories

Vishal Chawla
Vishal Chawla is a senior tech journalist at Analytics India Magazine and writes about AI, data analytics, cybersecurity, cloud computing, and blockchain. Vishal also hosts AIM's video podcast called Simulated Reality- featuring tech leaders, AI experts, and innovative startups of India.

Our Upcoming Events

Conference, Virtual
Genpact Analytics Career Day
3rd Sep

Conference, in-person (Bangalore)
Cypher 2022
21-23rd Sep

Conference, in-person (Bangalore)
Machine Learning Developers Summit (MLDS) 2023
19-20th Jan

Conference, in-person (Bangalore)
Data Engineering Summit (DES) 2023
21st Apr, 2023

3 Ways to Join our Community

Discord Server

Stay Connected with a larger ecosystem of data science and ML Professionals

Telegram Channel

Discover special offers, top stories, upcoming events, and more.

Subscribe to our newsletter

Get the latest updates from AIM

The curious case of Google Cloud revenue

Porat had earlier said that Google Cloud was putting in money to make more money, but even with the bucket-loads of money that it was making, profitability was still elusive.

Global Parliaments can do much more with Artificial Intelligence

The world is using AI to enhance the performance of its policymakers. India, too, has launched its own machine learning system NeVA, which at the moment is not fully implemented across the nation. How can we learn and adopt from the advancement in the Parliaments around the world? 

Why IISc wins?

IISc was selected as the world’s top research university, trumping some of the top Ivy League colleges in the QS World University Rankings 2022