Four Red Lines.

Polar night.

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1. A biology startup called EvolutionaryScale is training its AI on the published sequences of every protein the company’s researchers can get their hands on, and all that we know about them. Using that data, and with no assistance from human engineers, his AI is able to determine the relationship between a given sequence of molecular building blocks, and how the protein that it creates functions in the world. Already, EvolutionaryScale has created one proof-of-concept molecule. It’s a protein that functions like the one that makes jellyfish light up, but its AI-invented sequence is radically different than anything nature has yet to invent.  The company’s eventual goal is to enable all sorts of companies—from pharmaceutical makers producing new drugs to synthetic chemistry companies working on new enzymes—to come up with substances that would be impossible without their technology. That could include bacteria equipped with novel enzymes that could digest plastic, or new drugs tailored to individuals’ particular cancers. (Source: wsj.com, italics mine)

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2. Dr. Adam Rodman, an expert in internal medicine at Beth Israel Deaconess Medical Center in Boston, confidently expected that chatbots built to use artificial intelligence would help doctors diagnose illnesses. He was wrong. Instead, in a study Dr. Rodman helped design, doctors who were given ChatGPT-4 along with conventional resources did only slightly better than doctors who did not have access to the bot. And, to the researchers’ surprise, ChatGPT alone outperformed the doctors. “I was shocked,” Dr. Rodman said. The chatbot, from the company OpenAI, scored an average of 90 percent when diagnosing a medical condition from a case report and explaining its reasoning. Doctors randomly assigned to use the chatbot got an average score of 76 percent. Those randomly assigned not to use it had an average score of 74 percent. (Source: nytimes.com)

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