In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

These new models are specially trained to recognize when an LLM is potentially going off the rails. If they don’t like how an interaction is going, they have the power to stop it. Of course, every ...

Matrix-based optimizers have attracted growing interest for improving LLM training efficiency, with significant progress centered on orthogonalization/whitening based methods. While yielding ...

The optimization trap is tempting. Instinct says to lock in the winning formula. But the most resilient companies ...

A virtual assistant powered by AI supervised by a cardiologist can offer guideline-directed medical therapy optimization after hospitalization for heart failure with reduced ejection fraction.

Abstract: Improving transport efficiency is challenging for multimodal transport participants to improve cost-effectiveness. This paper proposes to select city nodes and establish a multi-objective ...

Step aside, LLMs. The next big step for AI is learning, reconstructing and simulating the dynamics of the real world. Barbara is a tech writer specializing in AI and emerging technologies. With a ...

Abstract: With the widespread application of automatic speech recognition (ASR) systems, their vulnerability to adversarial attacks has been extensively studied. However, most existing adversarial ...

Long sales cycles, low conversion volume, and multi-stage purchase journeys make measurement and attribution harder, creating real obstacles to campaign optimization. For B2Bs and brands selling ...

Each year when MD+DI editors sit down to discuss Medtech Company of the Year prospects, the companies that rise to the top for us tend to be those that have had a transformational year either through ...