A recent study published in Nature Communications introduces a multimodal AI test that utilizes routine breast cancer H&E slides to predict the likelihood of cancer recurrence across various invasive breast cancer subtypes. The research, which analyzed data from 8,161 patients, demonstrates that the AI test provides a more precise method for predicting disease-free intervals, achieving a C-index of 0.71 compared to the standard 21-gene assay's C-index of 0.61. The AI test's performance was particularly notable in triple-negative breast cancer, where existing guidelines lack recommended assays. The findings indicate the potential of AI-driven pathology tests to significantly improve risk stratification and personalized treatment decisions in breast cancer care.
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New Multimodal AI Test Enhances Breast Cancer Recurrence Risk Assessment
Nature Communications· Yann LeCun· Tuesday, July 7, 2026
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Tencent Launches Hy3, a 295B-Parameter Mixture-of-Experts Model for Agentic Workflows
Tencent has unveiled Hy3, a 295 billion-parameter Mixture-of-Experts model designed for reasoning and agentic workflows, positioning itself as a strong competitor to trillion-scale models. The model features 21 billion active parameters with 192 experts and offers a 256K context window aimed at long-horizon tasks such as coding, document processing, and financial analysis. Hy3 is built to mitigate hallucination issues by providing grounded responses and is available for commercial use under the Apache 2.0 license. Users can access a free API for two weeks, enhancing its affordability for various applications.