Elon Musk made the claim in January 2026, then declared in October that “longevity is coming,” a view that OpenAI’s Brockman now echoes.
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An AI-native experimental laboratory for autonomous biomolecular operations
China built an AI that runs an entire biology lab on it’s own.
Researchers from Shangha published a paper that feels like a massive leap toward artificial scientists.
They built AutoDNA, an “AI-native experimental laboratory”
Until now, if you asked an AI to design a biology experiment, it could give you a great protocol. But a human still had to walk into a lab, hold the pipettes, run the thermal cyclers, and tweak the process when things inevitably went wrong.
AutoDNA removes the human.
You just type a natural language prompt, and a swarm of specialized AI agents takes over.
Here’s how wild this multi-agent architecture is:
Scientists spot elusive particle decay in search for ‘Zeptoverse’
Scientists have found evidence for a rare particle decay occurring once in 10 billion particles at the LHCb experiment at CERN.
Connecting artificial intelligence with the tools of astrophysical research
Investigating a scientific question is often a complex process. As an astrophysicist studying some of the most energetic phenomena in the universe, I know that finding answers requires much more than reading scientific papers or understanding existing theories. Astrophysical research involves collecting observations, analyzing data, building physical models and comparing their predictions with observations. These tasks require different scientific tools, databases and modeling software and can take considerable time even for experienced researchers.
This challenge motivated the development of AstroGenesis, a multi-agent AI system designed to connect different stages of astrophysical research within a single environment. Our goal is to make scientific investigations faster and more accessible. A paper describing the work is posted to the arXiv preprint server.
Scientists discover a surprising pattern in one of the deadliest brain cancers
Researchers have discovered a surprising growth pattern in glioblastoma, one of the most aggressive and difficult-to-treat brain cancers.
MIT students build combat robots designed to survive brutal battles
MIT students upgraded the ARES and KRATOS combat robots with enhanced armor and improved weapon systems.
An AI model has found a new ‘CRISPR-like’ biological system. Here’s what it means for science
After coding, mathematics and chatbots, AI companies are setting their sights on the messy world of biology.
Virtual modeling reveals safety measures for battery-powered mining systems
The mining industry is shifting toward battery-powered equipment to improve efficiency, but lithium-ion batteries pose risks due to their high energy density. They can fail, overheat and, in some cases, catch fire, releasing toxic emissions.
By combining three modeling approaches to build virtual mining systems, Penn State researchers now more comprehensively understand how to predict and mitigate lithium-ion battery fires in mines before they spread, endangering miners and halting operations.
Lung cancer: Can a new blood test warn of recurrence early on?
Now, a new blood test that detects traces of lung cancer DNA could help identify patients at risk of recurrence months before the disease becomes visible on scans. The findings may pave the way for more personalized follow-up care and treatment after surgery.
The study, published in The Journal of Molecular Diagnostics, suggests that liquid biopsies could eventually complement standard imaging and help doctors tailor follow-up care according to each patient’s risk of recurrence. However, further research is necessary to establish how best to use these tests in routine clinical practice and whether acting on their results improves long-term survival.
Ultrathin films that overcome ‘dead layer’ effect could enable energy-efficient microchips for AI
Multiferroics are a promising class of materials for making computer chips and other electronic components that can operate at much lower power than today’s devices. The materials have coupled electrical and magnetic properties that can be manipulated simultaneously with a relatively tiny electrical voltage.
Engineers are hopeful that multiferroics could help reduce the energy burden associated with the rise of AI, but there’s a problem known as the “dead layer” effect: When these materials are made thin enough to use in a computer chip, they lose the electrical and magnetic properties that make them so interesting.
Now, a team of Brown University researchers has developed a technique for making thin films of the multiferroic bismuth ferrite that retain their key properties and have some emergent properties that make them even more useful.