Latest

Machine Learning

·November 7, 2024·7 min read

Can Language Models Really Understand? Study Uncovers Limits in AI Logic

A recent study questions if large language models (LLMs) truly form coherent world models, despite their accurate outputs in complex tasks like generating directions or playing games. Researchers found that while LLMs provide nearly flawless driving directions, they fail with unexpected changes, suggesting the models don't grasp underlying rules.

Featured Neuroscience

·November 3, 2024·5 min read

Building Better Brain Imaging Models for Broader Clinical Use

New research shows that predictive models linking brain activity and behavior need to generalize across diverse datasets to be useful in clinical settings. By training models on varied brain imaging datasets, researchers found that effective models can still perform accurately when tested on different datasets with unique demographic and regional characteristics.

This shows computers and people in an office.

Featured Neuroscience

·October 28, 2024·6 min read

When Human-AI Teams Thrive and When They Don’t

A new study reveals that while human-AI collaboration can be powerful, it depends on the task. Analysis of hundreds of studies found that AI outperformed human-AI teams in decision-making tasks, while collaborative teams excelled in creative tasks like content generation. This research suggests organizations may overestimate the benefits of human-AI synergy. Instead, strategic use of AI’s strengths in data processing and humans’ creativity may yield the best results.

This shows computer code and a molecule.

Featured Neuroscience

·October 24, 2024·6 min read

AI Predicts Chemical Compounds for Dual-Target Medications

Researchers have developed an AI system that predicts chemical compounds capable of targeting two proteins simultaneously, potentially creating more effective medications. By training the AI with a chemical language model, it was able to generate novel molecular structures with dual-target activity, an essential feature for treating complex diseases like cancer.

This shows a brain and a network of images.

Featured Neuroscience Psychology

·October 22, 2024·5 min read

How AI is Reshaping Human Thought and Decision-Making

A new study introduces "System 0," a cognitive framework where artificial intelligence (AI) enhances human thinking by processing vast data, complementing our natural intuition (System 1) and analytical thinking (System 2). However, this external thinking system poses risks, such as over-reliance on AI and a potential loss of cognitive autonomy.

This shows robotic hands using a keyboard.

Featured Neuroscience Psychology

·October 22, 2024·3 min read

AI-Written Stories Rated Lower Due to Bias, Not Quality

New research shows that stories generated by AI, such as ChatGPT, are almost as good as those written by humans. However, when people are told a story is AI-generated, they rate it more negatively, revealing a bias against AI-created content.

Featured Genetics Neuroscience Psychology

·October 21, 2024·6 min read

AI Uncovers DNA Variants Linked to Psychiatric Disorders

Researchers developed an AI algorithm, ARC-SV, to detect complex structural variants in the human genome that previous methods missed. Analyzing over 4,000 genomes, researchers discovered thousands of complex variants, many affecting brain-related genes and linked to schizophrenia and bipolar disorder.

Featured Neuroscience

·October 19, 2024·4 min read

Enhancing AI Accuracy and Confidence in Answer Generation

Researchers have introduced a novel method called Answer-prefix Generation (ANSPRE) to improve the precision and reliability of large language models (LLMs) in open-domain question answering. ANSPRE helps LLMs generate concise answers while providing more reliable confidence scores, a critical feature for high-stakes fields like healthcare, law, and education.

Featured Neuroscience Psychology

·October 17, 2024·6 min read

People Empathize with Bullied AI Bots

People empathize with AI bots excluded from a virtual game, treating them like social beings in need of fairness. Participants favored giving the AI bot a fair chance in play, with older adults showing a stronger inclination to rectify the perceived unfairness.

This shows the outline of a computerized head.

Featured Neuroscience

·October 15, 2024·3 min read

Vulnerability Found in AI Image Recognition

A new study reveals a vulnerability in AI image recognition systems due to their exclusion of the alpha channel, which controls image transparency. Researchers developed "AlphaDog," an attack method that manipulates transparency in images, allowing hackers to distort visuals like road signs or medical scans in ways undetectable by AI. Tested across 100 AI models, AlphaDog exploits this transparency flaw, posing significant risks to road safety and healthcare diagnostics.

Featured Neurology Neuroscience

·October 15, 2024·3 min read

AI-Enhanced MRIs Show Potential for Brain Abnormality Detection

Researchers have developed a machine learning model that upgrades 3T MRI images to mimic the higher-resolution 7T MRI, providing enhanced detail for detecting brain abnormalities. The synthetic 7T images reveal finer features, such as white matter lesions and subcortical microbleeds, which are often difficult to see with standard MRI systems. This AI-driven approach could improve diagnostic accuracy for conditions like traumatic brain injury (TBI) and multiple sclerosis (MS), though clinical validation is needed before wider use.

This is a drawing of a doctor looking at a computer monitor.

Featured Neuroscience

·October 15, 2024·4 min read

Integrating Machine Learning Boosts Disease Prediction Accuracy

A recent review explored how integrating machine learning with traditional statistical models can enhance disease risk prediction accuracy, a key tool in clinical decision-making. While traditional models like logistic regression are limited by certain assumptions, machine learning offers flexibility but has inconsistent results in some cases. The study revealed that combined models, especially stacking methods, outperform individual methods by harnessing each approach’s strengths and addressing their weaknesses.