Separate developments in speech recognition technology from IBM and California universities at San Francisco and Berkeley offer promising news for patients suffering from vocal paralysis and speech loss.
IBM reported the creation of a faster and more energy-efficient computer chip capable of turbo-charging speech-recognition model output.
With the explosive growth of large language models for AI projects, limitations of hardware performance leading to lengthier training periods and spiraling energy consumption have come to light.
In terms of energy expenditure, MIT Technology Review recently reported that training a single AI model generates more than 626,000 pounds of carbon dioxide, almost five times the amount an average American car emits in its lifetime.
A key factor behind the huge energy drain of AI operations is the exchanging of data back and forth between memory and processors.
IBM researchers seeking a solution say their prototype incorporates phase-change memory devices within the chip, optimizing fundamental AI processes known as multiply–accumulate (MAC) operations that greatly speed up chip activity. This bypasses the standard time- and energy-consuming routine of transporting data between memory and processor.
"These are, to our knowledge, the first demonstrations of commercially relevant accuracy levels on a commercially relevant model," said IBM's Stefano Ambrogia in a study published Aug. 23 in the online Nature journal.
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