Researchers used AI to discover hundreds of genes linked to tobacco use disorder, alongside potential new treatments. Analyzing extensive health data, the team identified genetic variations that contribute to tobacco addiction, which affects 1.3 billion people globally ..read more

Researchers employed AI to fast-track the discovery of treatments for Parkinson's disease. They utilized machine learning techniques to screen millions of compounds and successfully identified five promising candidates that prevent the harmful clumping of alpha-synuclein, a key protein in Parkinson’s pathology ..read more

AI-generated messages can make recipients feel more "heard" compared to responses from untrained humans. The research demonstrates AI's superior ability to detect and respond to human emotions, potentially providing better emotional support ..read more

Researchers developed methods to predict emotions in spontaneous thoughts using fMRI and machine learning. They crafted personalized narratives that participants read while their brain activity was monitored, aiming to decode the emotional dimensions of thoughts ..read more

Researchers innovated a method to evolve diverse personality traits in dialogue AI using a language model and the prisoner's dilemma game. By simulating scenarios where AI agents choose between cooperation and self-interest, the study demonstrates the potential of AI to mimic complex human behaviors ..read more

Neural networks, regardless of their complexity or training method, follow a surprisingly uniform path from ignorance to expertise in image classification tasks. Researchers found that neural networks classify images by identifying the same low-dimensional features, such as ears or eyes, debunking the assumption that network learning methods are vastly different ..read more

Researchers developed an AI algorithm capable of predicting mouse movement with a 95% accuracy by analyzing whole-cortex functional imaging data, potentially revolutionizing brain-machine interface technology. The team's end-to-end deep learning method requires no data preprocessing and can make accurate predictions based on just 0.17 seconds of imaging data ..read more

Machine learning (ML) models can accurately identify emotions from brief audio clips, achieving a level of accuracy comparable to humans. By analyzing nonsensical sentences to remove the influence of language and content, the study found that deep neural networks (DNNs) and a hybrid model (C-DNN) were particularly effective in recognizing emotions such as joy, anger, sadness, and fear from clips as short as 1.5 seconds ..read more

Researchers made a significant leap in artificial intelligence by developing an AI capable of learning new tasks from verbal or written instructions and then verbally describing these tasks to another AI, enabling it to perform the same tasks. This development highlights a unique human-like ability in AI for the first time—transforming instructions into actions and communicating these actions linguistically to peers ..read more

Scientists are pioneering research into combating perfectionism in young people through artificial intelligence (AI)-enhanced Cognitive Behaviour Therapy for Perfectionism (CBT-P). The alarming rise of perfectionism among the youth, characterized by the relentless pursuit of high standards and significant mental health risks, has prompted the exploration of innovative treatment methods ..read more