AI is moving to the edge, are you ready?
"Apple's Siri will finally work without an internet connection with on-device speech recognition" – The Verge 2021-06
Google Assistant speech recognition, has worked offline with some limitations since 2019 (LifeWire). "Google announced it will build its own smartphone processor, called Google Tensor, that will power its new Pixel 6 and Pixel 6 Pro phones this fall." CNBC 2021-08-02
This change is expected to enhance its offline capabilities significantly. "We're now able to run data-center quality models on our device." The Verge 2021-08-2
There are good reasons why consumers and AI service providers want AI at the edge. These include better privacy, speed, capacity to continue operating even when connectivity is down, and much more. Another reason is the reduction of costs to the AI/ML service provider. Instead of providing and paying for huge processing power in the Cloud to support the customers' requests, each customer will pay for their own processing power and electricity (buying a strong enough device, charging it, etc.)
In a sense, this is a similar revolution from the movement many years ago, from mainframes with dumb terminals to personal computers.
The maturity of AI and the availability of huge processing power at affordable prices for the consumer market permit this change.
The advantages of edge processing do not just apply to giants like Google and Apple. Many providers of AI solutions will want to push them to the edge.
Moving AI to the edge also has its risks, and it is much more challenging to identify AI going rogue or underperforming. Instead of monitoring and controlling a few deployments of AI in the Cloud, you will have billions of deployments on end devices, each deployment adapting to a different environment and behaving differently. To ensure your customer's satisfaction, you should not just rely on your lab test. You must be able to track them, detect rogue behaviors, and take proactive measures to fix them. Of course, you can build your own solution, but it will be time-consuming and expensive. Yokaranda offers an out-of-the-box solution to this.
AI is moving to the edge, and Yokaranda is ready to support it.