General
A CMU study shows AI-assisted coding yields only a brief uptick in code generation, but code quality worsens overall. Static analysis warnings rise by about 30% and code complexity increases by over 40%, with no sustained improvement after adoption. The author notes limitations of applying results to production code and emphasizes the ongoing need for human guardrails and governance when using AI coding tools.
ABC News reports on a study of 16,000 Australians that explores how working from home affects mental health, with nuanced findings by gender and work arrangement. The research sugg…
An argument that AI systems need hard, deterministic rules rather than relying on probabilistic vibes or LLM-based judgments. It introduces Steer, a Python library that enforces gu…
Apex-GPU proposes a method to run CUDA-based workloads on AMD GPUs without recompilation, enabling cross-vendor portability for AI and data workflows. The project highlights potent…
A BBC report highlights how energy-demand from data centres in London is delaying new housing developments, pointing to electricity capacity constraints and grid planning challenge…