Lifeboat Foundation

Researchers at Freie Universität Berlin, University of Maryland and NIST, Google AI, and Abu Dhabi set out to robustly estimate the free Hamiltonian parameters of bosonic excitations in a superconducting quantum simulator. The protocols they developed, outlined in a paper pre-published on arXiv, could contribute to the realization of highly precise quantum simulations that reach beyond the limits of classical computers.

All proteins are composed of chains of amino acids, which generally fold up into compact globules with specific shapes. The folding process is governed by interactions between the different amino acids—for example, some of them carry electrical charges—so the sequence determines the structure. Because the structure in turn defines a protein’s function, deducing a protein’s structure is vital for understanding many processes in molecular biology, as well as for identifying drug molecules that might bind to and alter a protein’s activity.

Protein structures have traditionally been determined by experimental methods such as x-ray crystallography and electron microscopy. But researchers have long wished to be able to predict a structure purely from its sequence—in other words, to understand and predict the process of protein folding.

For many years, computational methods such as molecular dynamics simulations struggled with the complexity of that problem. But AlphaFold bypassed the need to simulate the folding process. Instead, the algorithm could be trained to recognize correlations between sequence and structure in known protein structures and then to generalize those relationships to predict unknown structures.

“This makes the scam much harder to spot, as the information provided is personally relevant to the victims, arrives via the expected communication channel, and the linked, fake websites look as expected.”

What’s more, the diversification of the victimology footprint has been complemented by improvements to the toolkit that allow the scammer groups to speed up the scam process using automated phishing page generation, improve communication with targets via interactive chatbots, protecting phishing websites against disruption by competitors, and other goals.

Telekopye’s operations have not been without their fair share of hiccups. In December 2023, law enforcement officials from Czechia and Ukraine announced the arrest of several cybercriminals who are alleged to have used the malicious Telegram bot.

Would you buy a $16,000 Unitree G1 for your home assistant? Share your thoughts in the comments.

The pressure is on for Elon Musk to accelerate the mass production of Tesla’s Optimus robot as Unitree Robotics announced that its $16,000 G1 humanoid robot is ready for mass production. Initially focused on four-legged robots, Unitree shifted to humanoid designs and quickly developed the G1, which now boasts impressive capabilities like leaping, climbing stairs, and adjusting its gait in real time. Standing at 1.32 meters tall and weighing 35 kg, the G1 features 3D LiDAR, a RealSense depth camera, and a 9,000-mAh battery for two hours of use. While it’s ready for production, Unitree hasn’t confirmed if mass production has begun.

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In a recent study published in the journal Cell, researchers developed a deep learning model, “LucaProt,” a transformer-based AI model to detect highly divergent ribonucleic acid (RNA)-dependent RNA polymerase (RdRP) sequences in meta-transcriptomes from diverse ecosystems. They identified 180 RNA virus supergroups and 161,979 putative RNA virus species, showing that RNA viruses are widespread and present even in extreme environments.

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Continue reading “AI model LucaProt uncovers 251,000 new RNA viruses, revealing hidden diversity worldwide” »

Listen now (47 mins) | At the Interface of biomedical science and A.I.

Discover superhero abilities with I-XRAY, AI glasses that reveal anyone’s personal info like address, name, and phone number with a glance.

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We’re not actually specifically focused on AGI.

I’m simply saying that AGI seems likely to be an emergent property of what we’re doing, because we’re creating all these autonomous cars and autonomous humanoids that are actually a truly gigantic data stream that’s coming in and being processed.