18 min readJust now
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AI is transforming how businesses operate, but choosing the right AI model for a given enterprise use case has become a complex challenge. Today’s AI landscape offers a dizzying array of options — from large general-purpose models to task-specific ones, proprietary services to open-source releases, and model sizes ranging from massive billion-parameter transformers to efficient small models for edge devices. This abundance is both the promise and the problem: the potential benefits of finding a perfect-fit model for your needs are enormous, yet the complexity of selection can be overwhelming. New and improved models appear constantly, so one size certainly does not fit all. A model that unlocks transformative business value in one context might be a…
18 min readJust now
–
AI is transforming how businesses operate, but choosing the right AI model for a given enterprise use case has become a complex challenge. Today’s AI landscape offers a dizzying array of options — from large general-purpose models to task-specific ones, proprietary services to open-source releases, and model sizes ranging from massive billion-parameter transformers to efficient small models for edge devices. This abundance is both the promise and the problem: the potential benefits of finding a perfect-fit model for your needs are enormous, yet the complexity of selection can be overwhelming. New and improved models appear constantly, so one size certainly does not fit all. A model that unlocks transformative business value in one context might be a poor choice in another.
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Figure 1 : Navigating AI Model Selection in the Enterprise
In this post, we’ll explore a practical, vendor-neutral framework to approach AI model selection confidently. We’ll cover aligning models to use cases, evaluating performance in context, factoring in cost and infrastructure, planning for flexibility over the model’s lifecycle, and ensuring safety, compliance, and reliability in production.
Align Models with the Use Case Goals
The first principle of model selection is simple: start with a clear understanding of your use case.