Project Valhalla, Explained: How a Decade of Work Arrives in JDK 28
Project Valhalla introduces JEP 401: Value Classes and Objects into JDK 28, allowing developers to create classes that behave like primitives while maintaining readability and safety, with over 197,000 lines of code added to the OpenJDK repository.
GPT-5.5 hallucinates 3x more than MIT-licensed GLM-5.2
AI labs are shifting away from larger models, as evidenced by the US ban on Claude Fable 5, highlighting the risks associated with high parameter counts and the need for a more cautious approach to AI development.
To study how chips work, MIT researchers built their own operating system
Fractal, a new operating system kernel developed by MIT, provides unprecedented insights into processor behavior, revealing previously unknown vulnerabilities in Apple’s M1 chip, including evidence of Phantom speculation attacks.
Building a robotics research setup that lives next to my desk
Robotics research is now feasible for individuals with setups costing under €5,000, thanks to affordable hardware and accessible foundation models like Hugging Face’s LeRobot, enabling meaningful experimentation on real hardware.
DVD-JEPA: an open-source, fully-reproducible JEPA world model
DVD-JEPA demonstrates a novel approach to world modeling by predicting the 32-dimensional representation of future states rather than pixel-by-pixel, allowing for efficient learning from video data.
How does torch.compile() achieve massive speedups despite highly optimized NumPy functions?
torch.compile achieves massive speedups through operator fusion, which optimizes the execution of multiple operations into a single step, enhancing performance beyond that of highly optimized NumPy functions.
An open handbook on LLM inference at scale (GPU internals, KV cache, batching, vLLM/SGLang/TensorRT-LLM)
The handbook delves into GPU execution and memory internals, revealing that GPUs often remain idle during inference due to memory hierarchy constraints and throughput bottlenecks, with visual aids enhancing comprehension.
Built a Global AQ (PM2.5) Forecaster ML Model
The end-to-end Air Quality (PM2.5) forecasting pipeline utilizes over 1.6M rows of OpenAQ and NASA weather data, achieving a MASE below 1.0 globally by employing a Horizon aligned architecture to decouple forecasting horizons and mitigate variance issues.
Time Series Modeling Needs a Dynamical Systems Perspective