LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.

NVIDIA diffusion language model Nemotron TwoTower achieves 2.42x LLM inference throughput without a full retraining run, ...

Tom Fenton moves from local AI concepts to hands-on tools for matching LLMs to hardware, running local chatbots with Ollama and benchmarking AI performance.

A new development in data science has given one popular machine learning tool an improved sense of place, enabling it to make ...

Explore how AI phenotypic screening transforms image-based drug discovery through advanced phenotypic data analysis and ML-driven cell-based assays.

@InProceedings{pstone_simba, author = {Hojoon Lee and Youngdo Lee and Takuma Seno and Donghu Kim and Peter Stone and Jaegul Choo}, title = {Hyperspherical Normalization for Scalable Deep Reinforcement ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you’ve ever built a predictive model, worked on a ...

Finding the “perfect batch” does not have to be like a search for the Holy Grail. Today’s batch control systems supplemented with AI/ML make the arduous task of perfecting a batch and precisely ...

A U.S. Postal Service employee died after he became stuck inside a mail handling machine at a distribution center in Allen Park, Michigan, according to officials. Nicholas John Acker, 36, was stuck in ...

Abstract: Batch normalization (BN) has proven to be a critical component in speeding up the training of deep spiking neural networks in deep learning. However, conventional BN implementations face ...