AI: Making the case for analog in-memory computing with DRAM
Machine learning (ML), a subset of artificial intelligence (AI), has become integral to our lives. It allows us to learn and reason from data using techniques such as deep neural network algorithms. Machine learning enables data-intensive tasks such as image classification and language modeling, from which many new applications emerge.
There are two phases in the process of machine learning. First is the training phase, where intelligence is developed by storing and labeling information into weights—a computationally intensive operation usually performed in the cloud. During this phase, the machine-learning algorithm is fed with a given dataset. The weights are optimized until the neural network can make predictions with the desired level of accuracy.
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