Daily AI News

Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.

A new approach can reveal the features AI models use to predict proteins that might make good drug or vaccine targets.

MIT engineers used a machine-learning model to design nanoparticles that can deliver RNA to cells more efficiently.

The team used two different AI approaches to design novel antibiotics, including one that showed promise against MRSA.

As large language models increasingly dominate our everyday lives, new systems for checking their reliability are more important than ever.

A research team has created a quantum logic gate that uses fewer qubits by encoding them with the powerful GKP error-correction code. By entangling quantum vibrations inside a single atom, they achieved a milestone that could transform how quantum computers scale.

Researchers have unveiled a new quantum material that could make quantum computers much more stable by using magnetism to protect delicate qubits from environmental disturbances. Unlike traditional approaches that rely on rare spin-orbit interactions, this method uses magnetic interactions—common in many materials—to create robust topological excitations. Combined with a new computational tool for finding such materials, this breakthrough could pave the way for practical, disturbance-resistant quantum computers.

Scientists have designed swarms of microscopic robots that communicate and coordinate using sound waves, much like bees or birds. These self-organizing micromachines can adapt to their surroundings, reform if damaged, and potentially undertake complex tasks such as cleaning polluted areas, delivering targeted medical treatments, or exploring hazardous environments.

Researchers at Harvard have created a groundbreaking metasurface that can replace bulky and complex optical components used in quantum computing with a single, ultra-thin, nanostructured layer. This innovation could make quantum networks far more scalable, stable, and compact. By harnessing the power of graph theory, the team simplified the design of these quantum metasurfaces, enabling them to generate entangled photons and perform sophisticated quantum operations — all on a chip thinner than a human hair. It’s a radical leap forward for room-temperature quantum technology and photonics.