Artificial intelligence (AI) is becoming an everyday piece of technology in modern homes. It is now not uncommon to find smart home devices such as Google Hubs and wearable technology such as Apple Watches in a typical home - each including a smart assistant (i.e. Siri or Alexa) that uses AI. With the introduction of self-driving cars, this type of technology will soon touch almost every aspect of our lives.
Currently, most AI technology relies heavily on the cloud, using a collection of data that is stored there. Unfortunately, this reliance on the cloud can lead to latency issues as the process of data traveling between data centers and the device can be affected by several factors. Today, this problem is merely annoying when it comes to smart home devices and wearable technology, but it could prove to be dangerous when self-driving cars start to become prevalent.
How HCI and Edge Computing is Powering the Future of Artificial Intelligence
To solve this issue, the logical step is for AI to adopt a combination of hyperconverged infrastructure (HCI) and edge computing. HCI allows technology to operate within a smaller hardware design while edge computing is the processing of data outside of the traditional data center, typically on the edge of a network. When combined with HCI and edge computing, AI benefits from drastically reduced latency, as edge computing enables the data to reside on the edge of the device’s network, and allows for new data to be stored, accessed and later uploaded to the cloud. Meanwhile, HCI would allow for all of this to operate in something as small as an Amazon Echo Spot and soon, even a smart watch.
While the cloud has played an important role in making AI a commonly used technology, adopting the combination of HCI and edge computing will give AI the tools needed to grow to the next level, making it faster and smarter without the restrictions of latency.
Scale Computing offers an industry-leading and award winning HCI and edge computing solution. Our SC//HyperCore virtualization platform combines servers, storage, and virtualization into a single solution, and we recently launched the HE100 Series of appliances, which is small enough to be deployed almost anywhere.
Read more about Scale Computing HyperCore's virtualization.