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Category: robotics/AI – Page 12

Degrees of intelligence: Where Meta’s top AGI scientists studied and why it matters

Meta’s Superintelligence Lab has assembled a world-class team of AI researchers from institutions like OpenAI, DeepMind, and Google. Their educational paths—often beginning in top universities in China or India and leading to elite Western institutions—reflect the global and interdisciplinary nature of AGI development. This article explores their academic journeys, highlighting how rigorous training in mathematics, computer science, and safety research underpins the next frontier of artificial intelligence.

A couple tried for 18 years to get pregnant. AI made it happen

After trying to conceive for 18 years, one couple is now pregnant with their first child thanks to the power of artificial intelligence.

The couple had undergone several rounds of in vitro fertilization, or IVF, visiting fertility centers around the world in the hopes of having a baby.

The IVF process involves removing a woman’s egg and combining it with sperm in a laboratory to create an embryo, which is then implanted in the womb.

AI predicts patients likely to die of sudden cardiac arrest

A new AI model is much better than doctors at identifying patients likely to experience cardiac arrest. The linchpin is the system’s ability to analyze long-underused heart imaging, alongside a full spectrum of medical records, to reveal previously hidden information about a patient’s heart health.

The work, led by Johns Hopkins University researchers, could save many lives and also spare many people unnecessary medical interventions, including the implantation of unneeded defibrillators.

“Currently, we have patients dying in the prime of their lives because they aren’t protected and others who are putting up with defibrillators for the rest of their lives with no benefit,” said senior author Natalia Trayanova, a researcher focused on using artificial intelligence in cardiology. “We have the ability to predict with very high accuracy whether a patient is at very high risk for or not.”

Unique method enables simulation of error-correctable quantum computers

Quantum computers still face a major hurdle on their pathway to practical use cases: their limited ability to correct the arising computational errors. To develop truly reliable quantum computers, researchers must be able to simulate quantum computations using conventional computers to verify their correctness—a vital yet extraordinarily difficult task.

Now, in a world-first, researchers from Chalmers University of Technology in Sweden, the University of Milan, the University of Granada, and the University of Tokyo have unveiled a method for simulating specific types of error-corrected quantum computations—a significant leap forward in the quest for robust quantum technologies.

Quantum computers have the potential to solve complex problems that no supercomputer today can handle. In the foreseeable future, ’s computing power is expected to revolutionize fundamental ways of solving problems in medicine, energy, encryption, AI, and logistics.

AI predicts material properties using electron-level information without costly quantum mechanical computations

Researchers in Korea have developed an artificial intelligence (AI) technology that predicts molecular properties by learning electron-level information without requiring costly quantum mechanical calculations. The research was presented at ICLR 2025.

A joint research team led by Senior Researcher Gyoung S. Na from the Korea Research Institute of Chemical Technology (KRICT) and Professor Chanyoung Park from the Korea Advanced Institute of Science and Technology (KAIST) has developed a novel AI method—called DELID (Decomposition-supervised Electron-Level Information Diffusion)—that accurately predicts using electron-level information without performing quantum mechanical computations.

The method achieved state-of-the-art prediction accuracy on real-world datasets consisting of approximately 30,000 experimental molecular data.

New imaging technique reconstructs the shapes of hidden objects

A new imaging technique developed by MIT researchers could enable quality-control robots in a warehouse to peer through a cardboard shipping box and see that the handle of a mug buried under packing peanuts is broken.

Their approach leverages millimeter wave (mmWave) signals, the same type of signals used in Wi-Fi, to create accurate 3D reconstructions of objects that are blocked from view.

The waves can travel through common obstacles like plastic containers or interior walls, and reflect off hidden objects. The system, called mmNorm, collects those reflections and feeds them into an algorithm that estimates the shape of the object’s surface.

Open House

Have you heard about the crazy guys who bought an entire tower to convert it into a vertical village? Yes, that’s us.

Do you want to walk the 16-floor tower and explore the space? Still on the fence, if you should become a citizen? Do you have questions about how you can get involved and co-create? Wanna hear updates on what happened in the last 2 weeks? This event is for you! 👩‍🚀

About us: We are transforming a 16-floor tower in the heart of San Francisco into a self-governed vertical village —a hub for frontier technologies and creative arts. 8 themed floors will be dedicated to creating tier-one labs, spanning AI, Ethereum, biotech, neuroscience, longevity, robotics, human flourishing, and arts & music. These floors will house innovators and creators pushing the boundaries of human potential in a post-AI-singularity world.