Research Archives - Phonesnews.com

May 15, 2025

With AI, researchers predict the location of virtually any protein within a human cell

A protein located in the wrong part of a cell can contribute to several diseases, such as Alzheimer’s, cystic fibrosis, and cancer. But there are about 70,000 different proteins and protein variants in a single human cell, and since scientists can typically only test for a handful in one experiment, it is extremely costly and time-consuming to identify proteins’ locations manually.

A new generation of computational techniques seeks to streamline the process using machine-learning models that often leverage datasets containing thousands of proteins and their locations, measured across multiple cell lines. One of the largest such datasets is the Human Protein Atlas, which catalogs the subcellular behavior of over 13,000 proteins in more than 40 cell lines. But as enormous as it is, the Human Protein Atlas has only explored about 0.25 percent of all possible pairings of all proteins and cell lines within the database.

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May 14, 2025

Study shows vision-language models can’t handle queries with negation words

Imagine a radiologist examining a chest X-ray from a new patient. She notices the patient has swelling in the tissue but does not have an enlarged heart. Looking to speed up diagnosis, she might use a vision-language machine-learning model to search for reports from similar patients.

But if the model mistakenly identifies reports with both conditions, the most likely diagnosis could be quite different: If a patient has tissue swelling and an enlarged heart, the condition is very likely to be cardiac related, but with no enlarged heart there could be several underlying causes.

In a new study, MIT researchers have found that vision-language models are extremely likely to make such a mistake in real-world situations because they don’t understand negation — words like “no” and “doesn’t” that specify what is false or absent.

“Those negation words can have a very significant impact, and if we are just using these models blindly,

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May 13, 2025

How we think about protecting data

How should personal data be protected? What are the best uses of it? In our networked world, questions about data privacy are ubiquitous and matter for companies, policymakers, and the public.

A new study by MIT researchers adds depth to the subject by suggesting that people’s views about privacy are not firmly fixed and can shift significantly, based on different circumstances and different uses of data.

“There is no absolute value in privacy,” says Fabio Duarte, principal research scientist in MIT’s Senseable City Lab and co-author of a new paper outlining the results. “Depending on the application, people might feel use of their data is more or less invasive.”

The study is based on an experiment the researchers conducted in multiple countries using a newly developed game that elicits public valuations of data privacy relating to different topics and domains of life.

“We show that values attributed to data are combinatorial,

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May 12, 2025

If time is money, here’s one way consumers value it

As the saying goes, time is money. That’s certainly evident in the transportation sector, where people will pay more for direct flights, express trains, and other ways to get somewhere quickly.

Still, it is difficult to measure precisely how much people value their time. Now, a paper co-authored by an MIT economist uses ride-sharing data to reveal multiple implications of personalized pricing.

By focusing on a European ride-sharing platform that auctions its rides, the researchers found that people are more responsive to prices than to wait times. They also found that people pay more to save time during the workday, and that when people pay more to avoid waiting, it notably increases business revenues. And some segments of consumers are distinctly more willing than others to pay higher prices.

Specifically, when people can bid for rides that arrive sooner, the amount above the minimum price the platform can charge increases by 5.2 percent.

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May 11, 2025

Hybrid AI model crafts smooth, high-quality videos in seconds

What would a behind-the-scenes look at a video generated by an artificial intelligence model be like? You might think the process is similar to stop-motion animation, where many images are created and stitched together, but that’s not quite the case for “diffusion models” like OpenAl’s SORA and Google’s VEO 2.

Instead of producing a video frame-by-frame (or “autoregressively”), these systems process the entire sequence at once. The resulting clip is often photorealistic, but the process is slow and doesn’t allow for on-the-fly changes.

Scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Adobe Research have now developed a hybrid approach, called “CausVid,” to create videos in seconds. Much like a quick-witted student learning from a well-versed teacher, a full-sequence diffusion model trains an autoregressive system to swiftly predict the next frame while ensuring high quality and consistency. CausVid’s student model can then generate clips from a simple text prompt,

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May 11, 2025

Ping pong bot returns shots with high-speed precision

MIT engineers are getting in on the robotic ping pong game with a powerful, lightweight design that returns shots with high-speed precision.

The new table tennis bot comprises a multijointed robotic arm that is fixed to one end of a ping pong table and wields a standard ping pong paddle. Aided by several high-speed cameras and a high-bandwidth predictive control system, the robot quickly estimates the speed and trajectory of an incoming ball and executes one of several swing types — loop, drive, or chop — to precisely hit the ball to a desired location on the table with various types of spin.

In tests, the engineers threw 150 balls at the robot, one after the other, from across the ping pong table. The bot successfully returned the balls with a hit rate of about 88 percent across all three swing types. The robot’s strike speed approaches the top return speeds of human players and is faster than that of other robotic table tennis designs.

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May 11, 2025

Fine-tuning vs. in-context learning: New research guides better LLM customization for real-world tasks

By combining fine-tuning and in-context learning, you get LLMs that can learn tasks that would be too difficult or expensive for either methodRead More » Read More

May 11, 2025

System lets robots identify an object’s properties through handling

A human clearing junk out of an attic can often guess the contents of a box simply by picking it up and giving it a shake, without the need to see what’s inside. Researchers from MIT, Amazon Robotics, and the University of British Columbia have taught robots to do something similar.

They developed a technique that enables robots to use only internal sensors to learn about an object’s weight, softness, or contents by picking it up and gently shaking it. With their method, which does not require external measurement tools or cameras, the robot can accurately guess parameters like an object’s mass in a matter of seconds.

This low-cost technique could be especially useful in applications where cameras might be less effective, such as sorting objects in a dark basement or clearing rubble inside a building that partially collapsed after an earthquake.

Key to their approach is a simulation process that incorporates models of the robot and the object to rapidly identify characteristics of that object as the robot interacts with it.

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May 10, 2025

MIT engineering students crack egg dilemma, finding sideways is stronger

It’s been a scientific truth so universally acknowledged that it’s taught in classrooms and repeated in pop-science videos: An egg is strongest when dropped vertically, on its ends. But when MIT engineers actually put this assumption to the test, they cracked open a surprising revelation.

Their experiments revealed that eggs dropped on their sides — not their tips — are far more resilient, thanks to a clever physics trick: Sideways eggs bend like shock absorbers, trading stiffness for superior energy absorption. Their open-access findings, published today in Communications Physics, don’t just rewrite the rules of the classic egg drop challenge — they’re a lesson in intellectual humility and curiosity. Even “settled” science can yield surprises when approached with rigor and an open mind.

At first glance, an eggshell may seem fragile, but its strength is a marvel of physics. Crack an egg on its side for your morning omelet and it breaks easily.

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May 9, 2025

Biologists identify targets for new pancreatic cancer treatments

Researchers from MIT and Dana-Farber Cancer Institute have discovered that a class of peptides expressed in pancreatic cancer cells could be a promising target for T-cell therapies and other approaches that attack pancreatic tumors.

Known as cryptic peptides, these molecules are produced from sequences in the genome that were not thought to encode proteins. Such peptides can also be found in some healthy cells, but in this study, the researchers identified about 500 that appear to be found only in pancreatic tumors.

The researchers also showed they could generate T cells targeting those peptides. Those T cells were able to attack pancreatic tumor organoids derived from patient cells, and they significantly slowed down tumor growth in a study of mice.

“Pancreas cancer is one of the most challenging cancers to treat. This study identifies an unexpected vulnerability in pancreas cancer cells that we may be able to exploit therapeutically,” says Tyler Jacks,

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