# kaal:claim:5095633-004

**Claim.** The apparent abundance of internet text overstates the usable supply, because much of it fails quality thresholds for model training due to redundancy, noise, or irrelevance.

**Type.** mechanism  **Support.** argued

**Holds when.**

- applies to internet-sourced text used for model training

**Source quote.**

> while the internet contains a vast corpus of textual material, not all content meets quality thresholds suitable for model training, given issues such as redundancy, noise, or irrelevance.

**From.** Wulf A. Kaal, *Artificial Intelligence The Final Frontier* (2025), I. Introduction, page 2

**Cite as.** Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025). SSRN: https://ssrn.com/abstract=5095633

**Verify.** sha256 of source PDF `cbb484711f89bcefc9fc6a5730a1ed0a3f764d7999ad9b6f7d8ea05634c26c63` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202025%20-%20Artificial%20Intelligence%20The%20Final%20Frontier.pdf

**Failure mode.** quality-filtered supply shortfall  (family: ai-model-and-training-failure)

**Topics.** ai-and-agents, education-and-practice

**Keywords.** data-quality, llm-training-data, data-exhaustion, curation

**Related claims.**

- extends: https://wulfkaal.github.io/claims/4755632-002

**Canonical form.** This markdown file is the canonical hashed representation of the claim. Its sha256 is the content hash used for attestation.