AI Agents Are Moving Into the Real World

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Nathaniel Whittemore 0:00
On the one hand, people continue to debate about whether there is actually a market for personal agents. Some think that this is one where Silicon Valley entrepreneurs just have it wrong, that people don't actually want optimization and productivity in their personal lives. Others argue that that's a reductive view and that for all of the tasks that people actually enjoy, like certain types of shopping, there are a million other small, annoying tasks that they would love to have automated. Increasingly, that debate is getting new evidence, and as agents like Muse and Grokbot pick up steam, they are moving off of our screens and into the real world. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
Nathaniel Whittemore 0:45
Alright, friends, quick announcements before we dive in. First of all, thank you to today's sponsors KPMG, Blitzy, Robots and Pencils, and HyperAgent. To get an ad free version of the show, go to patreon.com slash AIDalybrief, or you can subscribe on Apple Podcasts. And if you want to learn more about sponsoring the show, send us a note at sponsors at aidalybrief.ai. Now, one other quick note there are a lot of new folks around these parts, and I'm trying to get a better handle on who you all are, what you're here for, and what you'd like to hear more and less of. If you go to the aidalybrief.ai website. There is a big link to a Fall Listener survey. It'll only take you a couple of minutes and would be incredibly valuable for me figuring out how to evolve this and potential other shows.
Nathaniel Whittemore 1:23
So again, I would be endlessly grateful if you would take two minutes to do that Fall Listener survey. You can find it on our webpage, aidailybrief.ai. Anthropic has announced what they are calling a big AI breakthrough in the biology field. Less than a week after confirming the existence of an AI-powered wet lab in the Bay Area, Anthropic has said, Claw discovered a novel enzyme system with properties reminiscent of CRISPR, with only high-level direction from our scientists. CRISPR is gene editing technology based on an enzyme sequence discovered in bacteria. It's used to mechanically cut DNA and splice in new. genes. Anthropic's Discovery looks similar to CRISPR in the way it features an array of repeated genomes.
Nathaniel Whittemore 2:02
They acknowledge that they don't yet know its function or level of significance, but these enzyme systems are relatively rare and have previously unlocked capabilities like cutting, copying, and inserting genes into DNA. They claim the discovery took a thousand CLOD agents, 21 hours, and around 210 million tokens, so somewhere on the order of $10,000 of compute. CEO Dario Amade, who has a PhD in biophysics, promoted the result on X. He wrote, It's easy to dismiss this as a one-off or curiosity, but we've repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023, models struggled to do math at the level of an average high school student.
Nathaniel Whittemore 2:41
In 2024, they started to do well on math competitions for the best high schoolers in the country. In 2025, they started to solve minor open problems. In early 2026, more significant open problems. And in late 2026, they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend. Amade said the need to confirm significant results using physical experiments is what led Anthropic to set up their wet lab. He disclosed that Claude isn't quite at the point of autonomously controlling lab equipment, but that's the end goal. He also mentioned that it's only a safety level 1 2 biolab, meaning it doesn't handle materials that are dangerous to humans.
Nathaniel Whittemore 3:16
Continuing, he wrote, In Machines of Loving Grace, I wrote about AI's potential to, quote, cure most diseases in 5 to 10 years, a goal that sounds impossible. Possible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with and then drive biological discoveries.

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