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A brain, a DNA strand, and binary code shine across a bluish, glowing background (Credit: Adobe Stock).
CSAIL article

Most people recognize Alzheimer’s from its devastating symptoms such as memory loss, while new drugs target pathological aspects of disease manifestations, such as plaques of amyloid proteins. Now a sweeping new study in the Sept. 4 edition of Cell by MIT researchers shows the importance of understanding the disease as a battle over how well brain cells control the expression of their genes..  The study paints a high-resolution picture of a desperate struggle to maintain healthy gene expression and gene regulation where the consequences of failure or success are nothing less than the loss or preservation of cell function and cognition.

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"VaxSeer" can predict dominant flu strains and identify the most protective vaccine candidates. The tool uses deep learning models trained on decades of viral sequences and lab test results to simulate how the flu virus might evolve and how the vaccines will respond (Image: Alex Gagne).
CSAIL article

Every year, global health experts are faced with a high-stakes decision: which flu strains should go into the next seasonal vaccine? The choice must be made months in advance, long before flu season even begins, and it can often feel like a race against the clock. If the selected strains match those that circulate, the vaccine will likely be highly effective. But if the prediction is off, protection can drop significantly, leading to (potentially preventable) illness and strain on healthcare systems.

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“Solving robotics is a long-term agenda,” MIT professor Russ Tedrake reflected. “It may take decades. But the debate itself is healthy. It means we’re testing our assumptions and sharpening our tools. The truth is, we’ll probably need both data and models - but which takes the lead, and when, remains unsettled” (Credit: ChatGPT).
CSAIL article

When the IEEE International Conference on Robotics and Automation (ICRA) first convened 40 years ago, the robotics community shared a clear vision: robots would one day combine elegant mathematical models with advanced computation to handle complex tasks. Four decades later, the community is divided over how to reach that goal. That divide was on full display this May in Atlanta, where ICRA marked its anniversary with a unique closing keynote: a live Oxford-style debate on whether “data will solve robotics and automation.”