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AI chips could get faster with 30-nanometer embedded memory that cuts data shuttling

When we watch videos or ask AI questions, enormous amounts of data are constantly moving inside computers. In particular, data centers that support AI must process and transfer vast amounts of data at very high speeds. However, current computers have a fundamental limitation: the place where calculations are performed and the place where data is stored are physically separated.

Because of this, data has to travel back and forth many times within a chip. This repeated movement takes time and consumes energy, creating a bottleneck that limits both speed and efficiency.

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