The Very Energy-Hungry AI Problem

How Can Real Wireless Power Come to the Rescue?

Artificial intelligence (AI) is becoming more and more relied upon in many different contexts.  Organizations collect data, develop algorithms, analyze trends and patterns, and leverage AI to continue to provide insights from that data to make valuable predictions and business decisions. 

AI requires all types of data

  • Transportation and travel data
  • Behavioral data
  • Online shopping data
  • Advertising data
  • Word, image, and face recognition data
  • Weather data
  • Mobile app data

This list is just the tip of the iceberg. You probably have five other types of data in mind right now that you use to train your AI models.

But storing, processing, and accessing that data, as well as training the AI in the first place, comes at a huge expense -- from the use of energy. “Between storing data in large-scale data centers and then using that data to train a machine learning or deep learning model, AI energy consumption is high,” reports TechTarget. And the more we collect data and create newer, more complex AI algorithms, the more energy we need.

That poses not only a cost problem, but also an environmental sustainability problem that’s just getting bigger.

How can we solve the very energy-hungry AI problem?

Our question for you is, how can wireless power over air help solve this problem? Real Wireless Power, — power delivered over air, at a distance — is already well-positioned to solve many environmental (and related cost) challenges. Primarily, it solves the problem of requiring disposable batteries in devices, which also enables products to be lighter and longer-lasting: a trifecta of sustainability. But can wireless power also help with the very energy-hungry AI problem?

We’ve been thinking about this a lot lately. We know that part of the problem is that there is just SO MUCH data to crunch through. Academics might argue that saving all data, whether or not it’s relevant, is important for future analysis. We understand this position. But from a business strategy perspective, most professionals are focused on the last three weeks to 90 days of data, and only a subset at that.

A new approach to collecting data efficiently

So why not create a system where the data that gets sent is only the data needed, and the data that is out of date gets automatically archived or deleted? What would it take to accomplish this?

With the rapid advancement of IoT and our connected world, we have the opportunity to collect a whole lot more data than we could ever imagine before. Wireless power is helping make this possible by eliminating the batteries that limit what IoT can do. 

As one example, wireless electronic shelf labels have been created with battery preservation top of mind. No one wants to change the batteries in thousands of displays. To prolong battery life, designers limit what the display can do. But when device energy is no longer limited, as is the case with wireless power like Cota, then the device can accomplish so much more. People can update and access information rapidly, and respond to real-world conditions, including supply and demand. 

The point is, when energy is no longer a limiting IoT factor, we can develop our smart devices to save and send only the data that we require for the AI, and those parameters can change all the time.

When we are specific about our data needs, the data center does not need to wade through as much noise, which could potentially speed up processing and decrease energy needs.  

Your AI expertise is needed

We imagine there are many more possibilities where wireless power like Cota can help decrease our artificial intelligence energy consumption, and you’ve probably already thought of a few. We’d love to hear about your challenges with AI energy needs, and your ideas on how wireless power might help alleviate that. Let’s start a conversation

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