The world is still losing its shit over each successive OpenAI release.
But let’s take a minute and get excited about some other AI news. AI biotech unicorn Owkin said on Friday that it was leading a new €33m consortium — backed by the French government — to improve cancer diagnosis and better tailor treatments to individuals.
While Europe is, undoubtedly, lagging in the generative AI race, it’s performed incredibly well when it comes to innovations in AI-driven medicine.
In 2020, Oxford’s Exscientia brought an AI-discovered drug molecule to human clinical trials for the first time ever (though the study eventually failed). In 2021, London’s DeepMind spun out a unit, Isomorphic Labs, to work on AI drug discovery using protein-folding AI model AlphaFold. And in 2023, European AI drug discovery startups continue to attract funding.
Still, OpenAI’s recent progress makes AI drug development seem frustratingly slow. The latest GPT-4 Technical Report shows how that model could be used in pharma, either to look for existing patents or look for compounds with similar properties to a certain medicine.
No doubt that these kinds of models will be applied more and more as one tool in the arsenal of AI drug discovery companies — despite how terrible they are at science (hello, made-up academic papers).
But wouldn’t it be great if AI medicine developed at the same speed and attracted the same hype that we see around large language models like GPT-4? And wouldn’t it be great if new large language models had the same guardrails — the equivalent of clinical trials — that are required in medicine? Each have something to learn from the other.
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