> DeepMind started developing AlphaFold in 2018.
> DeepMind started developing AlphaFold in 2018. In 2020, it was recognized as a solution to humanity's 50-year-old "protein folding problem," which sought to answer how amino acids automatically fold into complex 3D shapes. Those shapes determine the biological role of a protein. Scientists had identified the structures of roughly 170,000 proteins over the past 50 years, using tools and techniques like X-ray and nuclear magnetic resonance. The AlphaFold team took information from those previous work and then fed it to their AI to train AlphaFold. > In 2021, Nature published the papers with AlphaFold's methodology and the structure predictions of the entire human proteome, or the complete set of proteins expressed by our species. DeepMind then launched the AlphaFold Protein Structure Database, giving researchers free access to over 200 million protein structure predictions. Why is there no information on corroborations of the predictions? Anyone can make predictions. Surely there must have been teams picking predicted structures out of the database and comparing them to actual molecules?
Posted by thaumasiotes on Jul 29, 2026, 4:35 PM
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The biggest problem with MOND is that it was hand-crafted with additional parameters simply to fit the data.
(My comment is about detached houses).
The biggest problem with this is that I can't run my company's own internal benchmarks against this API, because they will be trained int...
> steer Claude away from over-engineering parts of the system in response to hypothetical concerns.
Why is there no comparison with FLUX 3 Image?
> our Git monorepo was developing an annoying problem Sentences like this are so common from people using monorepos that I am convinced ...
Why is there no contact form?
The biggest problem with plugging a generator into an outlet is you need a double ended cord.
> DeepMind started developing AlphaFold in 2018.
> DeepMind started developing AlphaFold in 2018. In 2020, it was recognized as a solution to humanity's 50-year-old "protein folding problem," which sought to answer how amino acids automatically fold into complex 3D shapes. Those shapes determine the biological role of a protein. Scientists had identified the structures of roughly 170,000 proteins over the past 50 years, using tools and techniques like X-ray and nuclear magnetic resonance. The AlphaFold team took information from those previous work and then fed it to their AI to train AlphaFold. > In 2021, Nature published the papers with AlphaFold's methodology and the structure predictions of the entire human proteome, or the complete set of proteins expressed by our species. DeepMind then launched the AlphaFold Protein Structure Database, giving researchers free access to over 200 million protein structure predictions. Why is there no information on corroborations of the predictions? Anyone can make predictions. Surely there must have been teams picking predicted structures out of the database and comparing them to actual molecules?
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