Netherlands’ MavLab (TU Delft) finished the race faster than the human-controlled drone.

An autonomous drone carrying water to help extinguish a wildfire in the Sierra Nevada might encounter swirling Santa Ana winds that threaten to push it off course. Rapidly adapting to these unknown disturbances inflight presents an enormous challenge for the drone’s flight control system.

To help such a drone stay on target, MIT researchers developed a new, machine learning-based adaptive control algorithm that could minimize its deviation from its intended trajectory in the face of unpredictable forces like gusty winds.

The study is published on the arXiv preprint server.

Astronomers use brokers to identify which signals to pursue in an endless stream of alerts.

The emerging field of neurosymbolic AI could solve these issues, while also reducing the enormous amounts of data required for training LLMs. So what is neurosymbolic AI and how does it work?

LLMs work using a technique called deep learning, where they are given vast amounts of text data and use advanced statistics to infer patterns that determine what the next word or phrase in any given response should be. Each model—along with all the patterns it has learned—is stored in arrays of powerful computers in large data centers known as neural networks.

LLMs can appear to reason using a process called chain-of-thought, where they generate multi-step responses that mimic how humans might logically arrive at a conclusion, based on patterns seen in the training data.

In recent years, scientists discovered something strange: When mice with Alzheimer’s disease inhale menthol, their cognitive abilities improve.

It seems the chemical compound can stop some of the damage done to the brain that’s usually associated with the disease.

In particular, researchers noticed a reduction in the interleukin-1-beta (IL-1β) protein, which helps to regulate the body’s inflammatory response – a response that can offer natural protection but one that leads to harm when it’s not controlled properly.

Can AI speed up aspects of the scientific process? Microsoft appears to think so.

At the company’s Build 2025 conference on Monday, Microsoft announced Microsoft Discovery, a platform that taps agentic AI to “transform the [scientific] discovery process,” according to a press release provided to TechCrunch. Microsoft Discovery is “extensible,” Microsoft says, and can handle certain science-related workloads “end-to-end.”

“Microsoft Discovery is an enterprise agentic platform that helps accelerate research and discovery by transforming the entire discovery process with agentic AI — from scientific knowledge reasoning to hypothesis formulation, candidate generation, and simulation and analysis,” explains Microsoft in its release. “The platform enables scientists and researchers to collaborate with a team of specialized AI agents to help drive scientific outcomes with speed, scale, and accuracy using the latest innovations in AI and supercomputing.”

In a world-first, scientists have figured out how to reprogram cells to fight — and potentially reverse — brain diseases like Alzheimer’s.

Researchers at the University of California, Irvine created lab-grown immune cells that can track down toxic brain buildup and clear it away, restoring memory and brain function in mice.

They did this by turning stem cells — which can become any cell in the body — into brain immune cells called microglia.

Scientists have developed oral nanorobots that target damaged heart tissue, deliver energy, and repair mitochondrial function, offering a novel approach to treating ischemic heart disease.

A photonic processor capable of running advanced artificial intelligence models with near-electronic precision is introduced, marking a substantial step towards post-transistor computing technologies.

To grow, cancer tumors must hijack the immune system for their needs. One of the main tricks that most tumors use is to manipulate a type of immune cell called a macrophage, causing it to protect the tumor from the rest of the immune system, recruit blood vessels and help the cancer spread to other tissues.

Now researchers in Prof. Ido Amit’s lab at the Weizmann Institute of Science have used state-of-the-art gene editing and single-cell and AI technologies to identify a master switch that turns macrophages into cancer helpers.

Based on this discovery, the team developed a new therapy that was shown to be effective in mice with bladder tumors, one of the most common types of cancer in humans and one for which only limited therapeutic innovations are currently available. The discovery is presented in a paper published in the journal Cancer Cell.