Summary
Executive summary:
● Generative AI systems, such as chatGPT, recently passed the Turing test, forever transforming human-machine interaction. These systems provide giant productivity leaps across many sectors. However, their energy requirements increase nine-fold annually and their abundance grows at exponential rate. The resulting carbon footprint becomes significant.
● IT giants such as Google, Nvidia, Microsoft, and Amazon, as well as many mid-sized companies, have committed to reduce their carbon footprint. The EU is strengthening regulation for emission reductions. But the new generative AI trend jeopardizes emission reduction commitments.
● Most power consumption of generative AI is spent on matrix multiplication. Our novel solutions reduce energy consumption and carbon footprint by replacing current matrix multiplication algorithms with more efficient ones. These can be implemented on existing hardware and software stacks. Potential energy saving predicted at about 40-50%, while maintaining performance and accuracy.
● The novel developments of Prof. Oded Schwartz and his strong team are based on years of research, and protected by patents. The funds are requested to pursue business opportunity.
● Generative AI systems, such as chatGPT, recently passed the Turing test, forever transforming human-machine interaction. These systems provide giant productivity leaps across many sectors. However, their energy requirements increase nine-fold annually and their abundance grows at exponential rate. The resulting carbon footprint becomes significant.
● IT giants such as Google, Nvidia, Microsoft, and Amazon, as well as many mid-sized companies, have committed to reduce their carbon footprint. The EU is strengthening regulation for emission reductions. But the new generative AI trend jeopardizes emission reduction commitments.
● Most power consumption of generative AI is spent on matrix multiplication. Our novel solutions reduce energy consumption and carbon footprint by replacing current matrix multiplication algorithms with more efficient ones. These can be implemented on existing hardware and software stacks. Potential energy saving predicted at about 40-50%, while maintaining performance and accuracy.
● The novel developments of Prof. Oded Schwartz and his strong team are based on years of research, and protected by patents. The funds are requested to pursue business opportunity.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101138056 |
| Start date: | 01-10-2023 |
| End date: | 31-03-2025 |
| Total budget - Public funding: | - 150 000,00 Euro |
Cordis data
Original description
Executive summary:● Generative AI systems, such as chatGPT, recently passed the Turing test, forever transforming human-machine interaction. These systems provide giant productivity leaps across many sectors. However, their energy requirements increase nine-fold annually and their abundance grows at exponential rate. The resulting carbon footprint becomes significant.
● IT giants such as Google, Nvidia, Microsoft, and Amazon, as well as many mid-sized companies, have committed to reduce their carbon footprint. The EU is strengthening regulation for emission reductions. But the new generative AI trend jeopardizes emission reduction commitments.
● Most power consumption of generative AI is spent on matrix multiplication. Our novel solutions reduce energy consumption and carbon footprint by replacing current matrix multiplication algorithms with more efficient ones. These can be implemented on existing hardware and software stacks. Potential energy saving predicted at about 40-50%, while maintaining performance and accuracy.
● The novel developments of Prof. Oded Schwartz and his strong team are based on years of research, and protected by patents. The funds are requested to pursue business opportunity.
Status
SIGNEDCall topic
ERC-2023-POCUpdate Date
12-03-2024
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