In 2024 the Nobel Prize in Chemistry went to researchers who built an AI that predicts the shape of proteins. That’s a problem biologists had been chipping away at for about 50 years. The shape of a protein determines what it does in your body and figuring it out used to take years of lab work for a single protein. Drug companies are already using it to design new medications. That same year the Nobel Prize in Physics went to the researchers whose work made neural networks possible.
Two Nobels and AI is sitting in the middle of both of them. That’s worth paying attention to.
Something that changed how I think about all of this is learning about how the brain actually processes reality. Your brain isn’t trying to give you an accurate picture of the world. It’s trying to keep you alive and those are completely different goals. We see color because it helped our ancestors figure out which food was safe to eat. Your brain fills in gaps in your vision constantly without you noticing, running on shortcuts and assumptions because they’re usually good enough, not because they’re accurate.
A computer vision system doesn’t work anything like that. It just sees a grid of numbers. No shortcuts from millions of years of evolution, no instinct telling it what to pay attention to. It picks up on patterns a human would never catch but put a sticker on a stop sign and some of these systems won’t recognize it anymore. The way it fails looks nothing like the way a human fails.
One of the Nobel winners said something pretty honest after winning. AI research is hitting a real data problem. These models need enormous amounts of training data and there’s only so much quality human generated content out there. Some researchers think models will start training on AI generated data which sounds like it could get weird pretty fast. Nobody has a clean answer for what comes next.
Coming into this semester I thought digital just meant technology in some vague general sense. Going through everything from ancient writing systems to transistors to how a large language model actually generates text, it means something more specific now. Digital is about taking something from the real world and breaking it into discrete pieces so it can be stored and copied without falling apart. That same basic idea connects a Sumerian scribe pressing symbols into clay to the chips being built today.
Nobody knows exactly where this is heading. But knowing how it works feels a lot better than not knowing.
Grammar checked with Claude (claude-sonnet-4-6, Anthropic, May 2026, claude.ai/chat). Prompt: “Please check the following blog post for any grammar, spelling, and punctuation errors. Do not change the meaning, tone, or structure of the writing. Only fix errors.”
Sources
https://www.technologyreview.com/2024/10/09/1105335/google-deepmind-wins-joint-nobel-prize-in-chemistry-for-protein-prediction-ai/
https://www.technologyreview.com/2024/10/15/1105533/a-data-bottleneck-is-holding-ai-science-back-says-new-nobel-winner/
https://www.scientificamerican.com/article/ai-comes-to-the-nobels-double-win-sparks-debate-about-scientific-fields/
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