SiMBA
Simplified Mamba-Based Architecture for Vision and Multivariate Time series.
Transformers have widely adopted attention networks for sequence mixing and MLPs for channel mixing, playing a pivotal role in achieving breakthroughs across domains.
Ok, that was an unexpected turn on my feed. Just had to share. Cool, portable robot that fits in a backpack.
Conquer the Wild | LimX Dynamics’ Biped Robot P1 ventured into Tanglang Mountain Based on Reinforcement Learning ⛰️
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Artificial human chromosomes that function within human cells hold the potential to revolutionize gene therapies, including treatments for certain cancers, and have numerous laboratory uses. However, significant technical challenges have impeded their progress.
Now a team led by researchers at the Perelman School of Medicine at the University of Pennsylvania has made a significant breakthrough in this field that effectively bypasses a common stumbling block.
In a study recently published in Science, the researchers explained how they devised an efficient technique for making HACs from single, long constructs of designer DNA. Prior methods for making HACs have been limited by the fact that the DNA constructs used to make them tend to join together—“multimerize”—in unpredictably long series and with unpredictable rearrangements. The new method allows HACs to be crafted more quickly and precisely, which, in turn, will directly speed up the rate at which DNA research can be done. In time, with an effective delivery system, this technique could lead to better-engineered cell therapies for diseases like cancer.
🦠💊🌍 https://www.news-medical.net/news/20240321/Rising-antimicrob…action.asp
Review delves into the rising challenge of antimicrobial resistance in sexually transmitted infections, underscoring the need for innovative treatments and the critical role of global surveillance in managing diseases like gonorrhea and syphilis.
Michel Talagrand innovative work has allowed others to tackle problems involving random processes.
The barren, dusty Red Planet was not always a lifeless mess. In fact, scientists have often theorized that Mars was once covered in vast waterways. There’s a lot of evidence to suggest that may be the case, too. However, new research involving that evidence suggests that it might not have been water that left those marks after all and that the chance of finding life on Mars is actually much slimmer than we hoped.
Mars is by far the planet that humanity has explored the most, with several rovers now having made their way across the barren surface of our neighboring planet. One of the key missions with those rovers has always been to find signs of life, or signs that life once existed on Mars. We’ve come close a couple of times, with some theorizing that NASA accidentally killed the only Martian life we’ve ever discovered on the planet.
Through it all, though, the hope that our chances to find life on Mars were high has relied on one key thing: the existence of water in Mars’s past. However, that watery past we believe the planet had may not have been as long or as extensive as we thought. New evidence suggests that places we thought had been carved out by water flowing through them could have actually been created by explosively evaporating carbon dioxide ice.
In a new paper published this month, Apple researchers reveal that they have developed new methods for training large language models using both text and visual information. According to Apple’s researchers, this represents a way to obtain state-of-the-art results.
