
Researchers cobbled together funding and time to show how quantum computing could aid in the development of drugs to help underserved populations and combat rare diseases.
Researchers at a university combined quantum computing with artificial intelligence to generate new peptides, short chains of amino acids that can bind to specific proteins in the body, which is a crucial step in vaccine development. The team worked on weekends using leftover funding from other projects because most innovative science is considered too risky by traditional funding sources. When they tested their discoveries in the laboratory, the quantum-enhanced AI model produced more successful peptides than a classical computer alone, with the strongest improvements in cases where training data was scarce. The research matters because it demonstrates a near-term practical use for quantum computing in drug discovery, particularly for developing treatments for underserved populations and rare diseases where medical research data is limited.

Robbyant, the embodied AI unit inside Ant Group, has released the LingBot-VA 2.0.The first embodied-native foundation model. It describes a video-action foundation model for generalist robot manipulation. The research team pretrains the whole stack for embodiment instead of fine-tuning a video generator. What is LingBot-VA 2.0? Most video-action models reuse two components built for digital content creation. One is a reconstruction-oriented VAE. The other is a bidirectional video-diffusio

Automatic Music Transcription (AMT) converts an audio recording into symbolic notes, usually MIDI. Single-instrument transcription already works reasonably well. However, transcribing a full multi-instrument mix stays difficult. Kyutai and Mirelo team now release MuScriptor to close that gap. It is an open-weight model trained on real, multi-instrument recordings across many genres. This article explains how MuScriptor works, what the benchmarks show, and how to run it. What is MuScriptor
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