Why Enterprises Don't Upgrade AI Models After Solving 98% of Use Cases
code_star · x · 2026-08-25
Discusses the inertia in upgrading AI models within enterprise deployments. Once a model solves 98% of use cases and is pinned in production pipelines, companies often lack the incentive to upgrade. The author cites MPT7B as an example: despite the emergence of better open models like Llama 2/3 and Qwen, download numbers for the older model remained high simply because it was already integrated into deployed workflows.
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