Memory Systems for AI: Part 1
There has been quite a lot of recent news about domain-specific processors that are being designed for the artificial intelligence (AI) market. Interestingly, many of the techniques used today in modern AI chips and applications have actually been around for several decades. However, neural networks didn’t really take off during the last wave of interest in AI that spanned the 1980s and 1990s. The question is why.
The chart above provides some insight as to why AI technology remained relatively static for so many years. Back in the 1980s and 1990s, processors (CPUs) simply weren’t fast enough to adequately handle AI applications. In addition, memory performance wasn’t yet good enough to enable neural networks and modern techniques to displace conventional approaches. Consequently, conventional approaches remained popular in the above-mentioned timeframe.
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- Memory Systems for AI: Part 2
- Memory Systems for AI: Part 3
- Memory Systems for AI: Part 4
- The Importance of Memory Architecture for AI SoCs
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