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...“When I read it, I literally fell off my chair,” says Peltz. He had just written a grant proposal focused on the importance of epigenetic changes in liver fibrosis, and the AI had targeted the same theme for its proposed therapeutics.
The AI co-scientist suggested three drugs, and Peltz came up with two more (all of which are already approved to treat other conditions). Google paid Peltz to help accelerate lab testing, and over the next few months, Peltz’s lab tested all five drugs in its human organoid model. Two of the AI’s three suggestions showed promise for promoting liver regeneration and inhibiting fibrosis6, whereas neither of Peltz’s worked out.
The experience left him impressed, he says: “These LLMs are what fire was for early human societies.”...
I hadn't heard of this kind of use of AI. I've found it to excel at helping me in grant proposal writing, so I'm not too surprised. You know where to test it out?
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I'm not sure either. It seems that many companies are testing their advanced programs in laboratories with select researchers. Google, Microsoft, and pharmaceutical companies are all involved in this. Individual researchers are also creating their own agents using platforms that many AI models for a subscription fee.
My professor has a friend who uses Poe.com, which provides access to some of the best models at the cost of a ChatGPT Pro subscription. You can create agents that work very effectively and assign different models to them, such as Qwen, Claude, Liquide, Gemini, Palm, Deepseek, and more. I did tried their pro plan and created several teacher agents, which was a great experience. It's been a year, and I'm sure they have advanced even further. This might be one of the best ways to experience your agents.
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