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.
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.
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.
Meta AI Introduces MetaRoCE: A Clean-Sheet RDMA Transport Built for AI-Scale Ethernet
Meta developed MetaRoCE, a new RDMA transport protocol designed for Ethernet networks supporting AI-scale training. The protocol addresses network bottlenecks in collective operations like all-reduce and all-to-all that synchronize thousands of accelerators during model training.