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Personal Brand :: Social Media :: LinkedIn :: Post :: A high-performing model doesn’t mean you have a high-performing product

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• AI :: LLM :: LLMOps :: Evaluation :: Training :: LLM Evaluation: Frameworks, Metrics, and Best Practices

A high-performing model doesn’t mean you have a high-performing product

💨 𝗔 𝗵𝗶𝗴𝗵-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗺𝗲𝗮𝗻 𝘆𝗼𝘂 𝗵𝗮𝘃𝗲 𝗮 𝗵𝗶𝗴𝗵-𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗽𝗿𝗼𝗱𝘂𝗰𝘁.

It’s easy to get caught up 𝙩𝙚𝙨𝙩𝙞𝙣𝙜 𝙢𝙤𝙙𝙚𝙡𝙨 𝙞𝙣 𝙞𝙨𝙤𝙡𝙖𝙩𝙞𝙤𝙣:

↳ benchmark scores
↳ fine tuning
↳ task performance

But the real question is: 𝗗𝗼𝗲𝘀 𝘁𝗵𝗲 𝗲𝗻𝘁𝗶𝗿𝗲 𝘀𝘆𝘀𝘁𝗲𝗺 𝘄𝗼𝗿𝗸 𝗶𝗻 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝘄𝗼𝗿𝗹𝗱?

𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲:

🧪 𝗠𝗼𝗱𝗲𝗹 𝗲𝘃𝗮𝗹 — is like testing the engine in a lab
𝘊𝘢𝘯 𝘪𝘵 𝘩𝘢𝘯𝘥𝘭𝘦 𝘵𝘢𝘴𝘬𝘴 𝘭𝘪𝘬𝘦 𝙖𝙣𝙨𝙬𝙚𝙧𝙞𝙣𝙜 𝙦𝙪𝙚𝙨𝙩𝙞𝙤𝙣𝙨 𝙤𝙧 𝙩𝙧𝙖𝙣𝙨𝙡𝙖𝙩𝙞𝙣𝙜 𝙩𝙚𝙭𝙩?

🔧 𝗦𝘆𝘀𝘁𝗲𝗺 𝗲𝘃𝗮𝗹 — is like taking the whole car on the road
Do the 𝙥𝙖𝙧𝙩𝙨, 𝙥𝙧𝙤𝙢𝙥𝙩𝙨, 𝙙𝙖𝙩𝙖, and 𝙨𝙚𝙩𝙪𝙥 actually get someone where they need to go?

The takeaway:

↳ 𝗠𝗼𝗱𝗲𝗹 𝗲𝘃𝗮𝗹 → capabilities
↳ 𝗦𝘆𝘀𝘁𝗲𝗺 𝗲𝘃𝗮𝗹 → outcomes

If you're only evaluating the model, you're only solving half the problem.

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