LLeMpower: Understanding Disparities in the Control and Access of Large Language Models
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913314879045632 |
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| author | Sathish, Vishwas Lin, Hannah Kamath, Aditya K Nyayachavadi, Anish |
| author_facet | Sathish, Vishwas Lin, Hannah Kamath, Aditya K Nyayachavadi, Anish |
| contents | Large Language Models (LLMs) are a powerful technology that augment human skill to create new opportunities, akin to the development of steam engines and the internet. However, LLMs come with a high cost. They require significant computing resources and energy to train and serve. Inequity in their control and access has led to concentration of ownership and power to a small collection of corporations. In our study, we collect training and inference requirements for various LLMs. We then analyze the economic strengths of nations and organizations in the context of developing and serving these models. Additionally, we also look at whether individuals around the world can access and use this emerging technology. We compare and contrast these groups to show that these technologies are monopolized by a surprisingly few entities. We conclude with a qualitative study on the ethical implications of our findings and discuss future directions towards equity in LLM access. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_09356 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | LLeMpower: Understanding Disparities in the Control and Access of Large Language Models Sathish, Vishwas Lin, Hannah Kamath, Aditya K Nyayachavadi, Anish Computers and Society Artificial Intelligence Computation and Language Emerging Technologies K.4.0; K.7.4 Large Language Models (LLMs) are a powerful technology that augment human skill to create new opportunities, akin to the development of steam engines and the internet. However, LLMs come with a high cost. They require significant computing resources and energy to train and serve. Inequity in their control and access has led to concentration of ownership and power to a small collection of corporations. In our study, we collect training and inference requirements for various LLMs. We then analyze the economic strengths of nations and organizations in the context of developing and serving these models. Additionally, we also look at whether individuals around the world can access and use this emerging technology. We compare and contrast these groups to show that these technologies are monopolized by a surprisingly few entities. We conclude with a qualitative study on the ethical implications of our findings and discuss future directions towards equity in LLM access. |
| title | LLeMpower: Understanding Disparities in the Control and Access of Large Language Models |
| topic | Computers and Society Artificial Intelligence Computation and Language Emerging Technologies K.4.0; K.7.4 |
| url | https://arxiv.org/abs/2404.09356 |