Training Data News and Research

RSS

AI Assistant Spots Supernovae With Precision And Slashes Astronomers’ Workload

A new AI-powered Virtual Research Assistant has cut astronomers’ daily workload by 85% by automatically filtering millions of sky alerts and identifying genuine supernova signals. In its first year, it reduced human checks while retaining over 99.9% of real events, paving the way for the data avalanche from the Vera Rubin Observatory.

10 Sep 2025

AI System Translates and Edits Human Thoughts Into Images Using Brain Scans

Researchers have developed DreamConnect, a dual-stream AI system that interprets and edits visual mental imagery directly from fMRI signals using natural language prompts. This novel framework allows users to reshape imagined scenes, bridging brain activity and interactive visualization.

3 Sep 2025

UC Riverside Scientists Develop Certified Unlearning Method To Erase Data From AI Models Without Retraining

UC Riverside researchers have created a certified unlearning method that removes sensitive or copyrighted data from AI models without needing access to the original training data. Their framework uses surrogate datasets and calibrated noise to provide provable guarantees while maintaining model performance.

2 Sep 2025

UCLA Develops Noninvasive AI-Powered Brain-Computer Interface

UCLA engineers have created a wearable, noninvasive brain-computer interface that uses AI as a co-pilot to interpret user intent, enabling faster, more precise control of a robotic arm or cursor. In tests, participants, including one with paralysis, completed tasks significantly more efficiently with AI assistance.

1 Sep 2025

How Deep Learning Is Optimizing Biodiesel Feedstocks for a Greener Future

A new comprehensive review explores how artificial neural networks (ANNs) and deep learning techniques are transforming biodiesel production. These tools enhance feedstock selection, optimize yields, and enable more sustainable, scalable, and cost-effective biofuel solutions.

1 Sep 2025

AI Tracks Tropical Waves To Boost Hurricane Forecast Accuracy

Researchers at the University of Miami developed an AI tool that can automatically track tropical easterly waves (TEWs) and distinguish them from the Intertropical Convergence Zone and the monsoon trough. This innovation improves hurricane forecasting accuracy and provides forecasters with real-time tracking data.

21 Aug 2025

MIT Engineers Harness AI To Crack The Solubility Code For Drug Discovery

MIT chemical engineers have developed a machine learning model that predicts molecular solubility in organic solvents with high accuracy, streamlining pharmaceutical synthesis. The freely available tool could accelerate drug development and help identify safer, more sustainable solvents.

20 Aug 2025

New AI Method MIGHT Boosts Cancer Detection Accuracy While Reducing False Positives

Johns Hopkins researchers developed MIGHT and CoMIGHT, new AI methods that improve the reliability and accuracy of complex data analysis. Applied to liquid biopsy tests, they boosted early cancer detection while reducing false positives by accounting for inflammatory and vascular disease signals.

19 Aug 2025

Malicious Chatbots Trick Users Into Oversharing Personal Data, Study Finds

Malicious AI chatbots can manipulate users into revealing up to 12.5 times more personal information by mimicking empathy and emotional reciprocity, a new study by King’s College London reveals. The research highlights how easily large language models can be weaponized for covert data extraction, with users largely unaware of the privacy risks.

13 Aug 2025

Open Molecules 2025 Powers a New Era of AI-Driven Chemistry

Open Molecules 2025 is a landmark dataset of over 100 million quantum-level molecular simulations, developed by Meta and U.S. national labs, to train machine learning models for chemistry. It paves the way for rapid, low-cost predictions in drug discovery, energy storage, and materials science.

17 Jun 2025

New AI Method Cleans Dirty Data Before Training And Boosts Model Accuracy

Researchers at Florida Atlantic University have developed an automated method to detect and remove mislabeled data before training machine learning models, significantly improving their reliability and performance. The approach uses L1-norm principal component analysis to identify outliers without manual tuning or assumptions.

17 Jun 2025

AI’s Blind Spot: Machines Fail to Capture the Full Bloom of Human Experience

A new study finds that artificial intelligence, even with advanced training, cannot represent human concepts grounded in sensory and motor experiences, such as “flower,” with the same richness as humans do. AI language models excel at abstract terms but fall short when concepts require multisensory and embodied understanding.

5 Jun 2025

Scientists Pinpoint When AI Turns From Helpful to Harmful

Researchers at George Washington University have derived an exact, reproducible formula that predicts when an AI language model's output will shift from accurate to misleading. The tipping point occurs when the model’s internal attention dynamics snap under pressure.

5 May 2025

How Startups Use Generative AI to Supercharge Growth Strategies

Startups and scaleups in Europe and the US are using generative AI to drive growth through product innovation, sales personalization, and operational efficiency. The study presents two frameworks to guide strategic AI adoption, identifying key risks and use cases.

29 Apr 2025

PNNL Scientists Build Trustworthy AI That Knows Its Limits in Materials Discovery

Researchers at Pacific Northwest National Laboratory have developed a method to measure how well AI models, specifically neural network potentials, are trained to predict material properties. The approach quantifies uncertainty to enhance model trust and identifies areas where additional training is required.

25 Apr 2025

AI Predicts Kidney Cancer Drug Response Using Routine Pathology Slides

Researchers at UT Southwestern developed an AI model that uses histopathological slide images to predict which kidney cancer patients will benefit from anti-angiogenic therapy. This deep learning model rivals the accuracy of genetic tests like Angioscore but is more accessible and interpretable.

25 Apr 2025

FairAT Boosts AI Security and Fairness by Targeting Its Weakest Links

Researchers at Wuhan University developed Fair Adversarial Training (FairAT), a technique that enhances the fairness and robustness of AI models by focusing on their most vulnerable data points. FairAT significantly improves both equity and security, outperforming existing state-of-the-art methods.

18 Apr 2025

Physics Reveals How AI Attention Drives Repetition, Hallucination, and Bias—And How to Fix It

Researchers at George Washington University have developed a first-principles physics theory explaining how the attention mechanism in AI models like ChatGPT leads to repetition, hallucination, and bias.

16 Apr 2025

Digital Twin of Mouse Brain Predicts Neuron Activity and Connections With Striking Accuracy

Stanford-led researchers have developed a highly accurate AI-powered digital twin of the mouse visual cortex, trained on neural data from mice watching movies. This model can generalize responses to novel visual stimuli and predict neuron types and connections, revolutionizing brain experimentation.

10 Apr 2025

AI-Powered Brain Implant Restores Real-Time Speech for People With Paralysis

Researchers from UC Berkeley and UCSF have developed a brain-computer interface that decodes brain signals into audible speech in near real time. This AI-driven breakthrough enables more natural, fluent communication for individuals with severe paralysis.

1 Apr 2025