IBM’s Granite 4.2 Models Learn to Think and Act Inside Environments
IBM released Granite 4.2, its first family of reasoning language models available in 3B, 8B, and 30B parameter sizes with switchable thinking mode. The two larger models underwent reinforcement learning training inside real software-engineering, terminal, and web-search environments.
Read full story →Liquid AI Open-Sources Pipette: A Reproducible Benchmarking Suite That Measures On-Device Models, Quantization, Runtime and Hardware Together
Liquid AI released Pipette, an open-source benchmarking platform that measures how foundation models perform on edge devices rather than server conditions. The tool evaluates on-device behavior by testing models, quantization methods, runtime, and hardware together as interconnected factors.
AI Method Reveals What Genomic Models Learn From DNA and Exposes Hidden Experimental Bias
Researchers developed PISA, an interpretation method that identifies base-by-base patterns learned by deep-learning models analyzing DNA sequences. The technique revealed and removed hidden experimental bias from genomic data used in sequence-to-function neural networks.
Perplexity Ships Portable Computer on NVIDIA DGX Spark: Local Harness, OS-Enforced Sandbox, and Zero Per-Token Cost for Local Steps
Perplexity released Portable Computer, a system combining local models, a harness, sandbox, and connectors that runs on NVIDIA DGX Spark hardware. The system incurs zero per-token cost for local processing steps and uses OS-enforced sandboxing.