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Technology has absolutely exploded over the last several decades, especially since the emergence of the internet and accessible computing. Everything from smartphones to virtual reality headsets and high-definition streaming have graced the world recently, making it ever-easier for people to enjoy entertainment, communication, banking, and more.
However, all this comes at a price, and one that’s increasingly being overlooked. Tech industries all use mammoth amounts of energy to power servers and maintain cooling systems, not to mention keeping data flowing. Not only does this increase operational costs, but it also contributes heavily to carbon emissions, one of the gravest challenges facing mankind in the 21st century.
Companies must balance cost savings with the imperative to also save the environment, and fortunately, the new world of AI is offering powerful solutions to help achieve both goals simultaneously. The strides made with AI have made the technology increasingly better at automatically spotting opportunities to optimize energy consumption, and many companies are now taking advantage.
The impact of climate change and the need for sustainable practices have never been more urgent. Energy demand will continue to soar; there’s no doubt about that. As a result, our energy usage must become more optimized. In many ways, it’s similar to our previous article on whether plastic, aluminum, glass, or paper is more environmentally friendly. Humans will struggle to drive down energy consumption and commodity production, but we can think smarter about how to mitigate the effects.
AI is at the forefront of an evolution towards cleaner and smarter energy practices in the tech world. Keep reading for a comprehensive investigation into how AI can be used in the battle against energy overconsumption. We’ll outline the essential challenges for tech industries and ways AI can help.
The energy challenge in tech industries
As technology continues to evolve, the general trend points towards ever-increasing consumption. This poses significant challenges for various industries, especially considering global energy consumption rates over the past few years. To give you a better idea of the task at hand, here are some of the main areas to consider:
Cloud computing and SaaS
Cloud computing has completely revolutionized the way companies and individuals store data, enabling storage across massive global server farms collectively called the “cloud”. Contrary to what you might think after uploading a few photos to this so-called cloud, all this memory still has a physical footprint, and it requires a massive amount of energy.
The Software-as-a-Service (SaaS) world creates an equally challenging area for the growing tech industry. Companies can use over 100 different pieces of software for everything from finance to HR and company messaging. These are all stored in the cloud, again requiring huge amounts of energy to power properly.
Renewable energy integration
Renewable energy should always be the goal if humans want to completely solve the energy problem, but until we’ve got a foolproof method, this remains a challenge for the tech industry to integrate. Green energy can fall foul of downtimes and less stable energy sources, for example, which can paradoxically take even more energy to fix.
Using AI to optimize green energy usage and production is the key, and something we’re increasingly working towards. The tech industry will eventually turn this challenge into an indispensable benefit, but only with the right amount of effort and application.
Energy-intensive gaming
The gaming industry is a particularly energy-hungry technology user, especially now that high-definition graphics and streaming have become so common. The live dealer casino world is a great example, with many leading companies live-streaming multiple camera angles with ultra-low latency, also using tons of electricity to do so.
AI will continue to help these live dealer games achieve more optimized and cost-effective energy use. The experience for players will also benefit, with ever-more technologically advanced roulette, blackjack, and other table games. For those interested, expert casino reviews can help you find the best live dealer platforms. Read these evaluations to find information on casino bonuses, betting limits, and table popularity.
Blockchain and cryptocurrency energy use
Ever since Bitcoin exploded onto the scene in 2009, the cryptocurrency and blockchain industries have evolved significantly. The technology has created entirely new possibilities across various sectors, but it also has a troublesome energy problem.
Bitcoin and many other cryptocurrencies require “mining” to upkeep, a complex requirement that essentially demands computers solve complex cryptographic problems around the clock. As you can imagine, this uses an enormous amount of electricity. In fact, Bitcoin is estimated to consume more than many small countries.
Data storage and processing
Tech industries are built on a vast treasure trove of data, including everything from customer details to complex coding. Every email, video, photo, and spreadsheet has a physical footprint, either on the “cloud” or on company data servers.
The energy needed to uphold this arrangement is massive, not only to keep the computers switched on, but also to keep cooling equipment running 24/7. The whole foundation will crumble without doing so. It’s an essential challenge that AI can significantly help with.
How AI can optimize energy consumption
All the energy challenges above are vital hurdles for tech industries to beat, and fortunately, AI can bring the magic touch across the board. Here are some of the most exciting areas:
Real-time energy monitoring
While we’ve had the capacity for real-time energy monitoring for a while, it’s not always been easy to gain insights from or gauge how to improve usage. This is where AI comes in, giving companies an around-the-clock way to monitor energy usage and automatically make adjustments when needed.
Predictive maintenance
One thing many people forget is how much energy can be used when specific pieces of equipment fail. Rebooting a server can use as much energy as a week of stable running, for example, so the imperative to fix these issues before they happen is massive. Again, AI can help here, using complex algorithms to instantly predict when machines should be replaced or updated.
Dynamic resource allocation
Cloud computing and SaaS demands an ever-shifting flow of energy, especially with companies constantly juggling various workflows. The tech industry is increasingly using AI as a conductor, helping to divert energy to exactly where it’s needed without wasting any resources.
Smart cooling systems
Cooling a data center takes astonishing amounts of energy, especially without optimization. AI can effortlessly optimize cooling systems using comprehensive data analysis to create the perfect conditions. For example, it could pre-empt a heatwave by turning down cooling temperatures before the outside temperature increases.
Energy consumption forecasting
Planning strategically is the only way to optimize energy consumption throughout tech industries, but it’s not always easy to do so. AI can crunch unimaginably huge amounts of data within seconds, something that can dramatically improve consumption forecasting, ultimately driving greater levels of optimization.
What’s next for AI and tech energy optimization?
AI can continue to drive energy consumption optimization throughout the tech industry, but experts must also solve the issue of how to power these artificial intelligence algorithms without contributing to the energy problem. The future looks very bright indeed, but there’s still undoubtedly work to be done.
This is a promotional post whose views and opinions do not necessarily represent those of illuminem.
