Authors: George Rajna
IBM Research launched the reduced-precision approach to AI model training and inference with a landmark paper describing a novel dataflow approach for conventional CMOS technologies to rev up hardware platforms by dramatically reducing the bit precision of data and computations. [24] Recent successful applications of deep learning include medical image analysis, speech recognition, language translation, image classification, as well as addressing more specific tasks, such as solving inverse imaging problems. [23] Researchers at Caltech have developed an artificial neural network made out of DNA that can solve a classic machine learning problem: correctly identifying handwritten numbers. [22] Researchers have devised a magnetic control system to make tiny DNA-based robots move on demand—and much faster than recently possible. [21] Humans have 46 chromosomes, and each one is capped at either end by repetitive sequences called telomeres. [20] Just like any long polymer chain, DNA tends to form knots. Using technology that allows them to stretch DNA molecules and image the behavior of these knots, MIT researchers have discovered, for the first time, the factors that determine whether a knot moves along the strand or "jams" in place. [19] Researchers at Delft University of Technology, in collaboration with colleagues at the Autonomous University of Madrid, have created an artificial DNA blueprint for the replication of DNA in a cell-like structure. [18] An LMU team now reveals the inner workings of a molecular motor made of proteins which packs and unpacks DNA. [17] Chemist Ivan Huc finds the inspiration for his work in the molecular principles that underlie biological systems. [16] What makes particles self-assemble into complex biological structures? [15]
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