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Evaluation is all you need: think like a scientist when building AI — scharf blog

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You can’t land a plane if your altimeter is off by 50 feet. You can't paint a masterpiece if you can’t see. You can’t build an AI pipeline if you can’t evaluate accuracy. LLMs have made building with AI incredibly easy and yet still very few companies have incorporated AI into their product. It’s not enough to build a feature, that feature needs to be good. If your goal is to build good AI software, you need to switch from thinking like an engineer to thinking like a scientist. Engineers design systems and then build them. Scientists run experiments based on a hypothesis until they have something that works. Thinking like a scientist starts by setting a clear goal and a framework for how you will evaluate experiments and measure success. Every ML engineer worth their salt knows the importance of evaluation. Now that anyone can be an AI engineer, every builder needs to understand why evaluation is so important and how to build measurable AI pipelines and robust evaluations. Testing is c

You can’t land a plane if your altimeter is off by 50 feet. You can't paint a masterpiece if you can’t see. You can’t build an AI pipeline if you can’t evaluate accuracy. LLMs have made building with AI incredibly easy and yet still very few companies have incorporated AI into their product. It’s not enough to build a feature, that feature needs to be good. If your goal is to build good AI software, you need to switch from thinking like an engineer to thinking like a scientist. Engineers design systems and then build them. Scientists run experiments based on a hypothesis until they have someth

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