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Large language models are \u2026 large. Forget Bitcoin and recharging electric vehicles; the grid could be toppled by powering AI in a few years. It would be optimal if AI could run on more underpowered edge devices. What if there was a quantum-inspired way to make LLMs smaller without sacrificing overall performance in combined metrics? We explore a way to do that and other advanced ideas, like selectively removing information from models, in this episode. Join Host Konstantinos Karagiannis for a chat about how businesses can solve many of the woes associated with bringing AI in-house with Sam Mugel from Multiverse. \xa0
For more on Multiverse, visit\xa0https://multiversecomputing.com/. \xa0
Read the CompactifAI paper:\xa0https://arxiv.org/abs/2401.14109. \xa0
Visit Protiviti at\xa0www.protiviti.com/US-en/technology-consulting/quantum-computing-services\xa0 to learn more about how Protiviti is helping organizations get post-quantum ready. \xa0
Follow host Konstantinos Karagiannis on all socials: @KonstantHacker and follow Protiviti Technology on LinkedIn and Twitter: @ProtivitiTech.\xa0\xa0\xa0 \xa0
Questions and comments are welcome!\xa0 \xa0
Theme song by David Schwartz, copyright 2021.\xa0 \xa0
The views expressed by the participants of this program are their own and do not represent the views of, nor are they endorsed by, Protiviti Inc., The Post-Quantum World, or their respective officers, directors, employees, agents, representatives, shareholders, or subsidiaries.\xa0 None of the content should be considered investment advice, as an offer or solicitation of an offer to buy or sell, or as an endorsement of any company, security, fund, or other securities or non-securities offering. Thanks for listening to this podcast. Protiviti Inc. is an equal opportunity employer, including minorities, females, people with disabilities, and veterans.