Project description
A greener future for energy-intensive matrix multiplication algorithms
Generative artificial intelligence (AI) systems like ChatGPT have revolutionised human-machine interactions, but they come at a growing environmental cost. Their energy demands multiply nine-fold yearly, posing a significant carbon footprint challenge. Tech giants and mid-sized companies have pledged emission reductions, while the EU has tightened regulations. However, the increase in generative AI threatens these commitments. Funded by the European Research Council, the Green-GPT project aims to tackle AI’s energy woes. By replacing energy-intensive matrix multiplication algorithms with efficient alternatives, Green-GPT anticipates savings of up to 50 % of energy while maintaining performance and accuracy. With years of research and patented innovations, the project seeks funds to turn sustainability into a business opportunity, ushering in a greener era for AI.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencessoftware
- social scienceseconomics and businesseconomicsproduction economicsproductivity
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsHost institution
91904 Jerusalem
Israel