Artificial Intelligence (AI) Chips
- Posted By
10Pointer
- Categories
Science & Technology
- Published
25th May, 2022
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Context
Recently, Intel launched new Artificial Intelligence (AI) chips to provide customers with deep learning compute choices for training and inferencing in data centres.
What are AI chips?
- AI chips are built with specific architecture and have integrated AI acceleration to support deep learning-based applications.
- These chips have hardware architectures and complementary packaging, memory, storage and interconnect technologies which make it possible to infuse AI into a broad spectrum of applications.
- There are different types of AI chips such as:
- Application-specific integrated circuits (ASICs),
- Field-programmable gate arrays (FPGAs),
- Central processing units (CPUs)
- GPUs
What is Deep Learning?
- Deep learning, more commonly known as active neural network (ANN) or deep neural network (DNN), is a subset of machine learning and comes under the broader umbrella of AI.
- It combines a series of computer commands or algorithms that stimulate activity and brain structure.
- Deep learning can make the process of collecting, analysing, and interpreting enormous amounts of data faster and easier.
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Significance
- AI chips generally contain processor cores as well as several AI-optimised cores (depending on the scale of the chip) that are designed to work in harmony when performing computational tasks.
- The AI cores are optimised for the demands of heterogeneous enterprise-class AI workloads with low-latency inferencing, due to close integration with the other processor cores, which are designed to handle non-AI applications.
