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Category: biotech/medical – Page 1,530

New method compares machine-learning model’s reasoning to that of a human

In machine learning, understanding why a model makes certain decisions is often just as important as whether those decisions are correct. For instance, a machine-learning model might correctly predict that a skin lesion is cancerous, but it could have done so using an unrelated blip on a clinical photo.

While tools exist to help experts make sense of a model’s reasoning, often these methods only provide insights on one decision at a time, and each must be manually evaluated. Models are commonly trained using millions of data inputs, making it almost impossible for a human to evaluate enough decisions to identify patterns.

Now, researchers at MIT and IBM Research have created a method that enables a user to aggregate, sort, and rank these individual explanations to rapidly analyze a ’s behavior. Their technique, called Shared Interest, incorporates quantifiable metrics that compare how well a model’s reasoning matches that of a human.

Could a computer ever learn the same way people and animals do?

Whether a computer could ever pass for a living thing is one of the key challenges for researchers in the field of Artificial Intelligence. There have been vast advancements in AI since Alan Turing first created what is now called the Turing Test—whether a machine could exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. However, machines still struggle with one of the fundamental skills that is second nature for humans and other life forms: lifelong learning. That is, learning and adapting while we’re doing a task without forgetting previous tasks, or intuitively transferring knowledge gleaned from one task to a different area.

Now, with the support of the DARPA Lifelong Learning Machines (L2M) program, USC Viterbi researchers have collaborated with colleagues at institutions from around the U.S. and the world on a new resource for the future of AI learning, defining how artificial systems can successfully think, act and adapt in the real world, in the same way that living creatures do.

The paper, co-authored by Dean’s Professor of Electrical and Computer Engineering Alice Parker and Professor of Biomedical Engineering, and of Biokinesiology and Physical Therapy, Francisco Valero-Cuevas and their research teams, was published in Nature Machine Intelligence, in collaboration with Professor Dhireesha Kudithipudi at the University of Texas at San Antonio, along with 22 other universities.

Peter Diamandis on When You’ll Stop Aging

ABOUT PETER DIAMANDIS

Peter is the founder and executive chairman of the XPRIZE Foundation, and has started over 20 companies in the areas of longevity, space, venture capital and education. He is also the New York Times bestselling author of several books, including his latest, Life Force, which he published early in 2020 with Tony Robbins.

Peter joined host Robert Glazer on the Elevate Podcast to discuss transformational changes needed in education, how the pandemic accelerated global trends, and the astonishing medical and health technologies he believes will be widely available, sooner than you think.

Why AGING Therapies Will Be AFFORDABLE To Us | Dr David Sinclair Interview Clips

The only way life extension would remain financially out of reach is if we vote ourselves into a dystopia.

Dr David Sinclair explains why aging therapies will be eventually affordable to us in this clip.

David Sinclair is a professor in the Department of Genetics and co-director of the Paul F. Glenn Center for the Biology of Aging at Harvard Medical School, where he and his colleagues study sirtuins—protein-modifying enzymes that respond to changing NAD+ levels and to caloric restriction—as well as chromatin, energy metabolism, mitochondria, learning and memory, neurodegeneration, cancer, and cellular reprogramming.

Dr David Sinclair has suggested that aging is a disease—and that we may soon have the tools to put it into remission—and he has called for greater international attention to the social, economic and political and benefits of a world in which billions of people can live much longer and much healthier lives.

Dr David Sinclair is the co-founder of several biotechnology companies (Life Biosciences, Sirtris, Genocea, Cohbar, MetroBiotech, ArcBio, Liberty Biosecurity) and is on the boards of several others.

Continue reading “Why AGING Therapies Will Be AFFORDABLE To Us | Dr David Sinclair Interview Clips” | >

Ginkgo Bioworks tightens DNA ties with Twist Bioscience to fuel expansion plans

After eating up about one billion base pairs to fuel its synthetic biology and cell programming efforts, Ginkgo Bioworks is going back for seconds, with another large order from the DNA weaver Twis | After eating up about one billion base pairs to fuel its synthetic biology and cell programming efforts, Ginkgo Bioworks is going back for seconds, with another large order from the DNA weaver Twist Bioscience.

Breakthrough Discovery of New Model for “Global” DNA Repair

Breakthrough techniques in living cells upend field.

Two studies provide a radically new picture of how bacterial cells continually repair damaged sections (lesions) in their DNA.

Led by researchers from NYU Grossman School of Medicine, the work revolves around the delicacy of DNA molecules, which are vulnerable to damage by reactive byproducts of cellular metabolism, toxins, and ultraviolet light. Given that damaged DNA can result in detrimental DNA code changes (mutations) and death, cells evolved to have DNA repair machineries. A major unresolved question in the field, however, is how do these machineries rapidly search for and find rare stretches of damage amid the “vast fields” of undamaged DNA.

Compound From Cardamom Spice Can Kill Aggressive Triple-Negative Breast Cancer Cells

Study shows that compound from cardamom shows promise for treating aggressive breast cancer.

Cardamonin — a natural compound found in the spice cardamom and other plants — could have therapeutic potential for triple-negative breast cancer, according to a new study using human cancer cells. The findings also show that the compound targets a gene that helps cancer cells elude the immune system.

About 10–15% of breast cancers are triple-negative, which means they don’t have receptors for estrogen or progesterone and don’t make excess amounts of a protein called HER2. These tumors are difficult to treat because they don’t respond to the hormone-based therapies used for other types of breast cancer. They also tend to be more aggressive and have a higher mortality rate than other breast cancers.

Loss of neurons, not lack of sleep, makes Alzheimer’s patients drowsy

The lethargy that many Alzheimer’s patients experience is caused not by a lack of sleep, but rather by the degeneration of a type of neuron that keeps us awake, according to a study that also confirms the tau protein is behind that neurodegeneration.

The study’s findings contradict the common notion that Alzheimer’s patients during the day to make up for a bad night of sleep and point toward potential therapies to help these patients feel more awake.

The data came from study participants who were patients at UC San Francisco’s Memory and Aging Center and volunteered to have their sleep monitored with electroencephalogram (EEG) and donate their brains after they died.

A new approach that could improve how robots interact in conversational groups

To effectively interact with humans in crowded social settings, such as malls, hospitals, and other public spaces, robots should be able to actively participate in both group and one-to-one interactions. Most existing robots, however, have been found to perform much better when communicating with individual users than with groups of conversing humans.

Hooman Hedayati and Daniel Szafir, two researchers at University of North Carolina at Chapel Hill, have recently developed a new data-driven technique that could improve how robots communicate with groups of humans. This method, presented in a paper presented at the 2022 ACM/IEEE International Conference on Human-Robot Interaction (HRI ‘22), allows robots to predict the positions of humans in conversational groups, so that they do not mistakenly ignore a person when their sensors are fully or partly obstructed.

“Being in a conversational group is easy for humans but challenging for robots,” Hooman Hedayati, one of the researchers who carried out the study, told TechXplore. “Imagine that you are talking with a group of friends, and whenever one of your friends blinks, she stops talking and asks if you are still there. This potentially annoying scenario is roughly what can happen when a robot is in conversational groups.”

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