Scientists reverse Alzheimer’s in mice and restore memory
Alzheimer’s has long been considered irreversible, but new research challenges that assumption. Scientists discovered that severe drops in the brain’s energy supply help drive the disease—and restoring that balance can reverse damage, even in advanced cases. In mouse models, treatment repaired brain...
Is Your Model Time-Blind? The Case for Cyclical Feature Encoding
How cyclical encoding improves machine learning prediction
The post Is Your Model Time-Blind? The Case for Cyclical Feature Encoding appeared first on Towards Data Science.
What we put on our plates may matter more for the climate than we realize. Researchers found that most people, especially in wealthy countries, are exceeding a “food emissions budget” needed to keep global warming below 2°C. Beef alone accounts for nearly half of food-related emissions in Canada. Sm...
Italy tells Meta to suspend its policy that bans rival AI chatbots from WhatsApp
Italy has ordered Meta to suspend its policy that bans companies from using WhatsApp's business tools to offer their own AI chatbots on the popular chat app.
AI supercharges scientific output while quality slips
AI writing tools are supercharging scientific productivity, with researchers posting up to 50% more papers after adopting them. The biggest beneficiaries are scientists who don’t speak English as a first language, potentially shifting global centers of research power. But there’s a downside: many AI...
Best OCR and vision language models you can run locally that transform documents, tables, and diagrams into flawless markdown copies with benchmark-crushing accuracy.
Large Language Models for EDA Cloud Job Resource and Lifetime Prediction
arXiv:2512.19701v1 Announce Type: new
Abstract: The rapid growth of cloud computing in the Electronic Design Automation (EDA) industry has created a critical need for resource and job lifetime prediction to achieve optimal scheduling. Traditional machine learning methods often struggle with the com...
Reducing Label Dependency in Human Activity Recognition with Wearables: From Supervised Learning to Novel Weakly Self-Supervised Approaches
arXiv:2512.19713v1 Announce Type: new
Abstract: Human activity recognition (HAR) using wearable sensors has advanced through various machine learning paradigms, each with inherent trade-offs between performance and labeling requirements. While fully supervised techniques achieve high accuracy, they...
Development and external validation of a multimodal artificial intelligence mortality prediction model of critically ill patients using multicenter data
arXiv:2512.19716v1 Announce Type: new
Abstract: Early prediction of in-hospital mortality in critically ill patients can aid clinicians in optimizing treatment. The objective was to develop a multimodal deep learning model, using structured and unstructured clinical data, to predict in-hospital mor...
Thermodynamic Focusing for Inference-Time Search: Practical Methods for Target-Conditioned Sampling and Prompted Inference
arXiv:2512.19717v1 Announce Type: new
Abstract: Finding rare but useful solutions in very large candidate spaces is a recurring practical challenge across language generation, planning, and reinforcement learning. We present a practical framework, \emph{Inverted Causality Focusing Algorithm} (ICFA)...
Synthetic Data Blueprint (SDB): A modular framework for the statistical, structural, and graph-based evaluation of synthetic tabular data
arXiv:2512.19718v1 Announce Type: new
Abstract: In the rapidly evolving era of Artificial Intelligence (AI), synthetic data are widely used to accelerate innovation while preserving privacy and enabling broader data accessibility. However, the evaluation of synthetic data remains fragmented across ...
PhysMaster: Building an Autonomous AI Physicist for Theoretical and Computational Physics Research
arXiv:2512.19799v1 Announce Type: new
Abstract: Advances in LLMs have produced agents with knowledge and operational capabilities comparable to human scientists, suggesting potential to assist, accelerate, and automate research. However, existing studies mainly evaluate such systems on well-defined...
A Branch-and-Price Algorithm for Fast and Equitable Last-Mile Relief Aid Distribution
arXiv:2512.19882v1 Announce Type: new
Abstract: The distribution of relief supplies to shelters is a critical aspect of post-disaster humanitarian logistics. In major disasters, prepositioned supplies often fall short of meeting all demands. We address the problem of planning vehicle routes from a ...
Interpolative Decoding: Exploring the Spectrum of Personality Traits in LLMs
arXiv:2512.19937v1 Announce Type: new
Abstract: Recent research has explored using very large language models (LLMs) as proxies for humans in tasks such as simulation, surveys, and studies. While LLMs do not possess a human psychology, they often can emulate human behaviors with sufficiently high f...
Zero-Shot Segmentation through Prototype-Guidance for Multi-Label Plant Species Identification
arXiv:2512.19957v1 Announce Type: new
Abstract: This paper presents an approach developed to address the PlantClef 2025 challenge, which consists of a fine-grained multi-label species identification, over high-resolution images. Our solution focused on employing class prototypes obtained from the t...
FGDCC: Fine-Grained Deep Cluster Categorization -- A Framework for Intra-Class Variability Problems in Plant Classification
arXiv:2512.19960v1 Announce Type: new
Abstract: Intra-class variability is given according to the significance in the degree of dissimilarity between images within a class. In that sense, depending on its intensity, intra-class variability can hinder the learning process for DL models, specially wh...
Can AI fix the operating room? This startup thinks so
There’s plenty of hype around AI and robots in healthcare, but the problem that’s actually costing hospitals money right now is operating room coordination. Two to four hours of OR time is lost every single day, not because of the surgeries themselves, but because of everything in between from manua...
The Machine Learning “Advent Calendar” Day 23: CNN in Excel
A step-by-step 1D CNN for text, built in Excel, where every filter, weight, and decision is fully visible.
The post The Machine Learning “Advent Calendar” Day 23: CNN in Excel appeared first on Towards Data Science.
John Carreyrou and other authors bring new lawsuit against six major AI companies
These authors rejected Anthropic's class action settlement, arguing that "LLM companies should not be able to so easily extinguish thousands upon thousands of high-value claims at bargain-basement rates."
This article is divided into two parts; they are: • What Is Perplexity and How to Compute It • Evaluate the Perplexity of a Language Model with HellaSwag Dataset Perplexity is a measure of how well a language model predicts a sample of text.
Lemon Slice nabs $10.5M from YC and Matrix to build out its digital avatar tech
Digital avatar generation company Lemon Slice is working to add a video layer to AI chatbots with a new diffusion model that can create digital avatars from a single image.