You must very well know what are traditional processors but do you what are artificial intelligence chips and how they are different from traditional processors? In this article, we will interpret the differences between AI chips and traditional processors. Recently, Microsoft presented AI chips during its Ignite developers’ conference. However, prior to Microsoft, well-known processor companies like Qualcomm and MediaTek had already entered the fray. Microsoft unveiled AI chips which have been designed to perform AI computing tasks particularly. Concurrently MediaTek and Qualcomm proffering on-device generative artificial intelligence capabilities through their upcoming chipsets for mid-range and flagship smartphones. You should stick with this page and go through the article till the end for more details. Swipe down the page.
How AI Chips Are Different From Traditional Processors?
The introduction of artificial intelligence chips from leading tech companies heralds a departure of traditional processors from conventional CPUs, depicting a trend towards specialized processing units meticulously optimized to perform artificial intelligence computing tasks. MediaTek and Qualcomm recently underscored a wider industry progression when forthcoming chipsets are proposed to integrate on-device generative artificial intelligence computing tasks. Shift to the following section and learn what are artificial intelligence chips.
Artificial Intelligence chips show a specialized category of semiconductors designed to facilitate on-device artificial intelligence capabilities and adept at executing Large Language Models. The AI Chips typically embrace a system-on-chip configuration to direct the diverse functions that are not able to be performed by the traditional processors for general processing and computation. It is important to comprehend the practical workings of AI to understand the need for a distinct processing unit for on-device AI. For example, when your smartphone camera focuses on a cat. The device deploys AI algorithms oriented to determine a cat with precision. This training unfolds within a neural network, either in on-device or the cloud, mimicking the human brain. Scroll down.
On-device rendition necessitates specialized processing segments since conventional CPUs are good only at one process at a time. For the devices designed to perform AI tasks on-device, it is imperative to have a dedicated chip that can execute multiple calculations and processes at the same time. For example, GPUs (Graphic Processing Units) are capable of performing such workloads, but these are not designed specifically for AI tasks. Therefore, a forked version of GPUs or a dedicated AI chip is required. Stay tuned to this website for more details and further updates.