Robotics has long been plagued by the need for precise, step-by-step directions, making them finicky learners. However, researchers at Cornell University have developed a revolutionary new framework called RHyME (Retrieval for Hybrid Imitation under Mismatched Execution) that allows robots to learn tasks by watching a single how-to video. This groundbreaking system supercharges a robotic system to use its own memory and connect the dots when performing tasks it has viewed only once, drawing inspiration from videos it has seen.

The RHyME system is powered by artificial intelligence and can significantly reduce the time, energy, and money needed to train robots. According to researchers, one of the annoying things about working with robots is collecting so much data on the robot doing different tasks. This new approach, a branch of machine learning called “imitation learning,” allows humans to look at other people as inspiration, just like we do in real life.

Home robot assistants are still a long way off because they lack the wits to navigate the physical world and its countless contingencies. To get robots up to speed, researchers like Kushal Kedia and Sanjiban Choudhury are training them with what amounts to how-to videos – human demonstrations of various tasks in a lab setting. The hope with this approach is that robots will learn a sequence of tasks faster and be able to adapt to real-world environments.

“Our work is like translating French to English — we’re translating any given task from human to robot,” said senior author Sanjiban Choudhury, assistant professor of computer science. This translation task still faces a broader challenge: Humans move too fluidly for a robot to track and mimic, and training robots with video requires gobs of it.

RHyME is the team’s answer – a scalable approach that makes robots less finicky and more adaptive. It supercharges a robotic system to use its own memory and connect the dots when performing tasks it has viewed only once by drawing on videos it has seen. For example, a RHyME-equipped robot shown a video of a human fetching a mug from the counter and placing it in a nearby sink will comb its bank of videos and draw inspiration from similar actions – like grasping a cup and lowering a utensil.

RHyME paves the way for robots to learn multiple-step sequences while significantly lowering the amount of robot data needed for training. RHyME requires just 30 minutes of robot data; in a lab setting, robots trained using the system achieved a more than 50% increase in task success compared to previous methods, the researchers said.

With the development of RHyME, we may soon see robots that can learn and adapt to real-world environments with greater ease. This breakthrough has the potential to revolutionize various industries and aspects of our lives, making robots more efficient and effective.

Scientists have made a groundbreaking discovery in the field of materials research, uncovering dozens of new “species” within the realm of quantum matter. A recent study published in Nature has added over a dozen states to the growing quantum zoo, shedding light on previously unknown phenomena.

Lead author Xiaoyang Zhu, Howard Family Professor of Nanoscience at Columbia University, explains that some of these states have never been seen before and were not expected to be discovered. Among them are potential candidates for creating topological quantum computers, which could overcome the errors plaguing current superconducting-based quantum computers.

The breakthrough lies in the discovery of a material called twisted molybdenum ditelluride, which can create the desired states without an external magnet. This material forms a honeycomb pattern when its layers are twisted, leading to unique properties that encourage electrons to join up and form larger wholes.

Researchers have been hunting for the fractional quantum Hall effect, a counterintuitive quirk of quantum mechanics where many electrons acting in concert create new particles with smaller charges than individual electrons. A major step forward occurred in 2023 when Xiaodong Xu discovered an anomalous, magnet-free, fractional quantum Hall effect in layers of molybdenum ditelluride.

Using pump-probe spectroscopy developed by Eric Arsenault, a team led by Yiping Wang was able to detect dozens of fractional charges, including those needed for building topological quantum computers. This discovery establishes pump-probe spectroscopy as the most sensitive technique in detecting quantum states of matter.

The research has entered new dimensions, time, and correlation, where scientists are now exploring the properties and applications of these novel materials. With so many discoveries to explore, it’s clear that the quantum zoo is indeed vast and full of surprises.

A team of researchers from Rice University has made a groundbreaking discovery in quantum physics by developing a 3D photonic crystal cavity that can control light interactions in unprecedented ways. This innovation paves the way for transformative advancements in quantum computing, quantum communication, and other quantum-based technologies.

Imagine standing in a room surrounded by mirrors, where a flashlight shines inside, bouncing back and forth endlessly. This is similar to how an optical cavity works – a tailored structure that traps light between reflective surfaces, allowing it to bounce around in specific patterns. These patterns, called cavity modes, can be used to enhance light-matter interactions, making them potentially useful in quantum information processing, developing high-precision lasers and sensors, and building better photonic circuits and fiber-optic networks.

The researchers built a complex 3D optical cavity and used it to study how multiple cavity modes interact with a thin layer of free-moving electrons exposed to a static magnetic field. The key question guiding their investigation was what happens when multiple cavity modes interact with the electrons simultaneously. They found that different cavity modes can interact with moving electrons in an ultrastrong coupling regime, where the exchange of energy between light and matter happens so fast it resists dissipation.

This phenomenon is known as ultrastrong coupling, which describes an unusual mode of interaction between light and matter where the two become deeply hybridized. The researchers used terahertz radiation to observe how the cavity modes and electrons couple inside the 3D optical cavity, navigating experimental challenges such as the need for ultracold temperatures and strong magnetic fields.

They discovered that depending on the polarization of the incoming light, the cavity modes either remain independent or mix together, forming completely new hybrid modes. This suggests that engineers can design materials where different cavity modes “talk” to each other through the electrons in a magnetic field, creating new correlated states.

The research findings pave the way for the development of hyperefficient quantum processors, high-speed data transmission, and next-generation sensors. Quantum phenomena or states are famously fragile, but this discovery provides a new approach to engineering light-matter interactions and ultrastrong photon-photon couplings.

This work was supported by the U.S. Army Research Office, the Gordon and Betty Moore Foundation, the W.M. Keck Foundation, and the Robert A. Welch Foundation. The content herein is solely the responsibility of the authors and does not necessarily represent the official views of the funding organizations and institutions.