Wevolver | Human-Computer Interaction Articles

AI That Moves, Adapts, and Learns: The Future of Embodied Intelligence

Columbia AI Summit keynote speaker Sami Haddadin discusses AI that interacts with the physical world—and what it could mean for human potential.

Turning Beginners into Experts with Artificial Intelligence

New research uses AI to improve training of sensorimotor skills in human subjects, with potential applications ranging from performing surgery to perfecting tennis serves.

Researchers reduce bias in AI models while preserving or improving accuracy

A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.

Harnessing scalability, adaptability, and efficiency of biological neural networks through flexible brain-computer interfaces

Liu and team receive NSF EFRI grant for biocomputing research

RAG vs Fine-Tuning: Differences, Benefits, and Use Cases Explained

Fine-tuning large language models adapts pre-trained models to specific tasks or domains using tailored datasets, while Retrieval-Augmented Generation (RAG) combines retrieval systems with generative models to dynamically incorporate external, up-to-date knowledge into outputs.

A portable light system that can digitize everyday objects

When Nikola Tesla predicted we’d have handheld phones that could display videos, photographs, and more, his musings seemed like a distant dream. Nearly 100 years later, smartphones are like an extra appendage for many of us.

Interactive mouthpiece opens new opportunities for health data, assistive technology, and hands-free interactions

When you think about hands-free devices, you might picture Alexa and other voice-activated in-home assistants, Bluetooth earpieces, or asking Siri to make a phone call in your car. You might not imagine using your mouth to communicate with other devices like a computer or a phone remotely.

Honoring Innovation in Computational Sciences: Apply for The Heinrich Emanuel Merck Award

Recognizing Groundbreaking Research in AI, Quantum, and Neuro-Inspired Computing

podcast

Podcast: Karsten Roscher & The Need For Safe AI (Interview)

In this episode, we chat with Karsten Roscher - a renowned AI expert at the Fraunhofer Institute for Cognitive Systems IKS - about the importance of safety in AI products, the current challenges facing experts, and what the future holds.

Large Language Models feel the direction of time

Researchers have found that AI large language models, like GPT-4, are better at predicting what comes next than what came before in a sentence. This “Arrow of Time” effect could reshape our understanding of the structure of natural language, and the way these models understand it.