(PATENT) The Complying Language Model™ aka. "CLM™" - Secure, Compliant, and Trustworthy Language, Generative and Reasoning AI (2025)

This report introduces the Complying Language Model (CLM), a novel architecture designed to address the inherent security and compliance failures of current Large Language Models (LLMs). The CLM aims to provide a secure, compliant, and trustworthy generative AI solution. "The Complying Language Model (CLM) Secure, Compliant, and Trustworthy Generative and Reasoning AI" highlights the significant vulnerabilities of existing LLMs, including prompt injection, data and model poisoning, and model inversion attacks, which can lead to sensitive data exposure and financial risks. It notes that the economic consequences of insecure AI are projected to reach $10.5 trillion annually by 2025, with data breaches costing U.S. organizations an average of over $10 million per incident. Furthermore, current LLM architectures are incompatible with major data protection regulations like GDPR and HIPAA, leading to substantial regulatory fines.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-29
DOI
https://doi.org/10.5281/zenodo.16997660
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

(PATENT) The Complying Language Model™ aka. "CLM™" - Secure, Compliant, and Trustworthy Language, Generative and Reasoning AI (2025)

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

(PATENT) The Complying Language Model™ aka. "CLM™" - Secure, Compliant, and Trustworthy Language, Generative and Reasoning AI (2025)

article en

Abstract

This report introduces the Complying Language Model (CLM), a novel architecture designed to address the inherent security and compliance failures of current Large Language Models (LLMs). The CLM aims to provide a secure, compliant, and trustworthy generative AI solution. "The Complying Language Model (CLM) Secure, Compliant, and Trustworthy Generative and Reasoning AI" highlights the significant vulnerabilities of existing LLMs, including prompt injection, data and model poisoning, and model inversion attacks, which can lead to sensitive data exposure and financial risks. It notes that the economic consequences of insecure AI are projected to reach $10.5 trillion annually by 2025, with data breaches costing U.S. organizations an average of over $10 million per incident. Furthermore, current LLM architectures are incompatible with major data protection regulations like GDPR and HIPAA, leading to substantial regulatory fines.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Openalex Percentile: Top 58%
Geochemistry and Geologic Mapping
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