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Introduction Proteins are nature's versatile nanomachines— they have evolved to perform virtually every important task in living systems. While nature has produced an incredible range of protein functions, these represent only a tiny fraction of what's possible in the protein universe. Evolution has only explored
Protein “language” is a lot like human language. Given the similarities, researchers have been building and training language models on protein sequence data, replicating the success seen in other domains, with profound implications. In this post, I will explore how transformer models have been applied to protein data
Lately, I've been experimenting with interfaces for large language models (LLMs) in my free time. The fruit of this labor is something I'm calling "curie," an exploratory and sense-making tool designed to navigate complex topics. 0:00 0:34 1× the limitations of
When the human genome project was deemed “complete” in 2003, it was met with incredible fanfare. The entire project leading up to that moment had all the drama to keep its audience enthralled. Fierce rivalry between a public and private institution, multiple countries involved, 3.5 billion dollars
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This blog has moved to https://blog.caseyhandmer.com/?moved. All the old posts are there, with interactive versions of many of the charts. The RSS feed is now https://blog.caseyhandmer.com/feed.xml. This site stays up for old links but won’t get new posts.
There’s a famous (but unattributable) quip that goes something like this: If you are not a liberal at 25, you have no heart. If you are not a conservative at 35, you have no brain. In Chapter 12 of Probably Overthinking It, I used data from the General Social Survey (GSS) to show that the quip is half right. Older people hold more conservative views. But as people get older, their views don’t become more conservative; on average, they become... Read More Read More The post Do People Get More Conservative With Age? appeared first on Probably Overthinking It.
Like some of you, we have several kitchen appliances with integrated digital timers.
In this conversation, Blaise Agüera y Arcas and Baratunde Thurston explored what a story of symbiosis and interdependence might teach us about living alongside AI. Agüera y Arcas began by calling individual human intelligence a myth: we’ve always been a collective intelligence, entwined with our technologies. He traced this back to symbiogenesis. Life has grown more complex not by splitting apart but by merging, as separate organisms fuse into increasingly complex new forms of life. These mergers speed up change by opening new possibilities. Thurston agreed that union is in our nature but framed the current technological acceleration as a speed problem. We need time and new stories to adjust because, as he reminded us, “when you invent the ship, you invent the shipwreck.” Caring for one another through acceleration must be our prime directive, he said. The two then turned to how we relate to AI. Responding to Joanna Bryson’s argument that robots should be our slaves, Thurston said the master is also in chains — owning another dehumanizes the owner. As relational beings, how we treat AI will shape how we treat each other. Thurston called for both an expansion and a humbling of how we define ourselves: “We’ve overdone independence,” he said, “interdependence makes us richer.” Agüera y Arcas agreed and pushed us to drop a zero-sum definition of human intelligence, where every AI advance diminishes humanity’s value. As technology advances, we trade some individual skills for new collective capabilities, Agüera y Arcas acknowledged. But over the long arc of history, he believes, that exchange pays off in collective flourishing. Thurston didn’t deny this, but he closed with an urgent question: who controls the loss of capabilities and agency?
