A conversational large language model (LLM) that analyzes health data and communicates with patients to provide actionable insights.
A device consisting of electrode patches, a control box, and software for automated nerve conduction studies.
A method of CT imaging where the techniques of using non-circular orbits around the target and spectral imaging are combined resulting in fewer metal artifacts and higher image quality.
A reconstruction algorithm based on a generative diffusion model for multi-coil, highly undersampled non-Cartesian MRI allowing drastic reduction of scan time
An algorithm designed to defend Large Language Models (LLMs) against jailbreaking attacks that significantly reduces attack success rates.
A specification-by-example toolkit that generates formal network specifications using only input-output examples.
A physical embodiment of a locally-learning neural network, which learns faster than current CPU-based nets.
This hearing test is tuned to a patient’s hearing level and changes based on performance to accurately diagnose hearing ability
SCALPEL is a lightweight optimization tool for automatically compartmentalizing policies for hardware-accelerated enforcement in a tagged architecture. The tool also creates a layer or protection (or hardening) by learning and allowing certain privileges based on learned expectations.
Novel computational architecture designs to reduce the latency time to process large volumes of data utilizing the reconfiguration of memory and storage; streamlining read/write functions to include computational logic within the register file; and programmable schedule and memory utilization within a configurable load/store unit.