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After the Liferaft exit I wanted to return to my machine learning roots and work directly with AI. LLMs represent the most transformative technology I've encountered since I first used Google Search over 25(!!!) years ago and I was itching to get hands on again. Over the past year at HealthMC, I've been able to delve deeply into these models, and we are beginning to share insights on how to make this amazing technology perform useful work reliably and effectively.
One key learning is that for enterprise use cases the LLM itself is not the product. While reaching the MVP stage is relatively straightforward, achieving the final 20% of accuracy is challenging, yet that is where significant value lies in many use cases. We needed to build a Data Factory around the models in order to capture that gain.
For a detailed look at the steps we took to build a production grade AI chart abstraction system, check out my post:
healthmc.ai/blog/the-archi…
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