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alt="DNA strands (Credit: Pixabay)."
CSAIL article

When you’re trying to understand which diseases or physical traits you’re predisposed to, the answers are sprinkled across your DNA. One powerful method for decoding this genetic forecast is polygenic scores, which give patients estimates of their risk for a condition and the likelihood of having physical characteristics (phenotypes, like being tall). Researchers seek to improve the accuracy of these cumulative predictions to account for most of the known genetic contributions.

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MIT News Heart Dissection
CSAIL article

Your heart is a tireless organ that beats about 3 billion times over an average lifetime and is simply essential for life. Unsurprisingly, cardiovascular disease is the leading cause of death worldwide, costing millions of lives each year. This relentless condition primarily damages the heart, which is divided into four main chambers: the right atrium, left atrium, right ventricle, and left ventricle. Understanding the functions and vulnerabilities of these chambers is crucial in the fight against heart disease.

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Using machine learning, MIT CSAIL and Project CETI researchers revealed complex, language-like structure in sperm whale communication with context-sensitive and combinatorial elements (Credits: Alex Shipps/MIT CSAIL).
CSAIL article

The allure of whales has stoked human consciousness for millennia, casting these ocean giants as enigmatic residents of the deep seas. From the biblical Leviathan to Herman Melville's formidable Moby Dick, whales have been central to mythologies and folklore. And while cetology, or whale science, has improved our knowledge of these marine mammals in the past century in particular, studying whales has remained a formidable a challenge.

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To close the gap with classical computers, researchers created the quantum control machine — an instruction set for a quantum computer that works like the classical idea of a virtual machine (Credits: Alex Shipps/MIT CSAIL).
CSAIL article

When MIT professor and now Computer Science and Artificial Intelligence Laboratory (CSAIL) member Peter Shor first demonstrated the potential of quantum computers to solve problems faster than classical ones, he inspired scientists to imagine countless possibilities for the emerging technology. Thirty years later, though, the quantum edge remains a peak not yet reached.

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Researchers from MIT and elsewhere found that complex large language machine-learning models use a simple mechanism to retrieve stored knowledge when they respond to a user prompt. The researchers can leverage these simple mechanisms to see what the model knows about different subjects, and also possibly correct false information that it has stored (Credits: iStock).
CSAIL article

Large language models, such as those that power popular artificial intelligence chatbots like ChatGPT, are incredibly complex. Even though these models are being used as tools in many areas, such as customer support, code generation, and language translation, scientists still don’t fully grasp how they work.

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With their DMD method, MIT researchers created a one-step AI image generator that achieves image quality comparable to StableDiffusion v1.5 while being 30 times faster (Credits: Illustration by Alex Shipps/MIT CSAIL using six AI-generated images developed by researchers).
CSAIL article

In our current age of artificial intelligence, computers can generate their own “art” by way of diffusion models, iteratively adding structure to a noisy initial state until a clear image or video emerges. Diffusion models have suddenly grabbed a seat at everyone’s table: Enter a few words and experience instantaneous, dopamine-spiking dreamscapes at the intersection of reality and fantasy. Behind the scenes, it involves a complex, time-intensive process requiring numerous iterations for the algorithm to perfect the image.