I used to spend about half my time thinking about ways we can better understand how to use AI in #biology — but increasingly, I’m worried about how about how we scale platforms to cope with data volumes 🧪🧵
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It's not just that. Training an AI on aspects of biology is basically stealing the life and work of others. If your body is your own, you don't want some cheap LLM making up things using your DNA as the building blocks.
Today, healthcare (a sorta ok proxy for life sciences) generates about 30% of the world’s data volume. By 2025, its data growth rate will reach 36%, faster than manufacturing, financial services, and media & entertainment.
Although the volumes are large, scaling in life sciences is similar to other industries. Institutions should focus on cloud for scalable data storage, AI/ML for faster insights, and standardized data formats to streamline workflows.
I agree - I've been working as a physician/developer/strategist in the EHR field for 25+ years. The innovation potential over the next few years is going to be unprecedented.
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https://www.rbccm.com/en/gib/healthcare/episode/the_healthcare_data_explosion
https://www.statista.com/statistics/949144/worldwide-global-datasphere-real-time-data-annual-size/