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“For the first time we have shown that even a tiny fraction of cellular material could be identified by a mass spectrometer onboard a spacecraft,” said Dr. Fabian Klenner.


How will we find life on Jupiter’s icy moon, Europa, and Saturn’s icy moon, Enceladus? This is what a recent study published in Science Advances hopes to address as a team of international researchers investigate how ice grains that are discharged from the active plumes of these small moons could possess enough organic material for life to exist. This study holds the potential to help astrobiologists develop the necessary instruments and methods to find life on these small moons, specifically with NASA’s Europa Clipper scheduled to launch this October, whose goal will be to investigate Europa’s habitability potential.

Artist’s illustration of Saturn’s moon, Enceladus, seen here upside down as the plumes are on the south pole. (Credit: NASA/JPL-Caltech)

Image of Jupiter’s moon, Europa, obtained in natural light by NASA’s Juno spacecraft. (Credit: NASA/JPL-Caltech/SwRI/MSSS/Kevin M. Gill)

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Welcome back to Coding with Qiskit! Join research scientist Dr. Derek Wang as he walks you through the exciting capabilities of Qiskit 1 for utility scale quantum computing.

He’ll show you how to install Qiskit version 1 from scratch and how to run quantum circuits–both unitary and dynamic, all based on some of the latest research papers by IBM Quantum–on devices with over 100 qubits using the latest error suppression and mitigation techniques. He’ll also be learning how to contribute to the Qiskit ecosystem with the help of open-source extraordinaire Abby Mitchell.

Remember to subscribe to get notified when the first episode is out!

Read more about Qiskit 1 here: https://www.ibm.com/quantum/blog/qisk

AI is driving a dramatic new need for electricity, and while tech execs have long trumpeted their commitment to a green energy future, the urgency of that need presents them with a difficult path forward.

Questions about fueling the AI boom took center stage earlier this month at the CERAWeek by S&P Global, The Wall Street Journal reported. The annual energy conference draws thousands of executives to Houston to discuss topics ranging from geopolitics to the energy transition.

No one knows how much electricity will be needed to power the AI boom. AI requires massive computing power and energy loads and has triggered an explosion of data centers. Microsoft cofounder Bill Gates said at the conference that the amount of power AI is bound to consume is mind-blowing.

Princeton researchers have trained an AI to predict and prevent a common problem arising during nuclear fusion reactions — and they think it might be able to solve other problems, too.

The challenge: If the Spice Girls were physicists, their song “2 Become 1” might have been about nuclear fusion, a reaction that occurs when two atoms merge.

Fusion releases a tremendous amount of energy in the form of heat — it’s what powers the sun and other stars — and if we could harness the reaction here on Earth, we would have a near limitless source of clean energy.

Stanford and McMaster University researchers created an artificial intelligence (AI) model to design molecules that inhibit the growth of Acinetobacter baumannii, a common drug-resistant bacteria. They synthesized and validated six structurally novel molecules that demonstrated antibacterial activity against A. baumannii and other phylogenetically diverse bacterial pathogens. This study represents a significant step toward the practical application of generative AI approaches for antibiotic discovery and drug discovery in general.

The research article, “Generative AI for designing and validating easily synthesizable and structurally novel antibiotics,” was published in Nature Machine Intelligence.

Among the most critical issues in contemporary medicine is the worldwide spread of factors contributing to antibiotic resistance. In 2019, drug-resistant infections were responsible for an estimated 4.95 million deaths. As new antibiotics are being developed slower than the spread of antimicrobial resistance determinants, this figure is expected to reach 10 million annually by 2050.