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While most organizations are clear about the outcomes they expect from generative AI, what’s not so well understood is the way to go about realizing these outcomes. Different outcomes require different approaches—in terms of the data sets you prepare and the AI models you employ.

If you are searching for How to choose the right AI foundation model. Then this white-paper is for you:

• This five-step cyclical process for model selection has governance at its core
• When assessing AI models, one of the key evaluation criteria is how well the model’s functionalities intersect with your use case requirements.
• The Capability criteria is designed to assess the products and features across a broad range of GenAI platforms capabilities that supports: Data preparation, Types of models and LLMOps. In addition, the criteria for Generative AI is assessed using industry standards.
• Evaluate size, performance and risks
• In model selection, while the key criteria are the use case, the size and performance of the model and the mode of deployment, there’s a common throughline of costs and ROI.
• To harness the true potential of AI, enterprises should stop looking at AI as an add-on to existing systems and instead embed it into the core of their business.

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