Deep learning model predicts how individual cells influence disease outcomes

A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to patient outcomes using widely available bulk RNA sequencing data. The approach ...
InfoWorld

The ‘toggle-away’ efficiencies: Cutting AI costs inside the training loop

You don't need the newest GPUs to save money on AI; simple tweaks like "smoke tests" and fixing data bottlenecks can slash ...

Nvidia shrinks LLM memory 20x without changing model weights

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.

[Comprehensive Interview] Tencent Unveils 3 Core AI Technologies at GDC 2026… “Integrated into the Production Pipeline”

Tencent showcased its three core AI solutions to the world: ‘MagicDawn,’ ‘VISVISE,’ and ‘ACE.’ According to Tencent, the most decisive shift in its AI technology this year, compared to last year, is ...
Scientific Research Publishing

A Lightweight Self-Supervised Representation Learning Framework for Depression Risk Profiling from Synthetic Daily Behavioural Trajectories ()

Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...