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Researchers at the SMM4H-HeaRD 2026 conference used deep learning models to predict cancer stages from pathology reports, with LightGBM and TF-IDF achieving high AUROC scores. However, performance dropped significantly d…
Researchers at arXiv and Phys. Rev. Research have developed a training framework that ranks and paces quantum machine learning samples by informativeness, adapting classical curriculum learning and hard-example-mining to…
A developer tested Agno v2.6.17, a lightweight AI agent framework that rebranded from Phidata in early 2025, using Gemini 2.5 Flash and built-in tools. The framework supports model-agnostic, multimodal, and multi-agent o…
A software engineer hypothesizes that experienced developers achieve better AI results due to transferable skills like written communication, delegation techniques, and ability to evaluate AI outputs, while codebase qual…
A study accepted at the AGILE 2026 conference found that AI image generators like GPT and DALL-E produce geographically stereotypical and monotonous depictions of places, with newer models showing less diversity than old…
The OpenAI API is the most widely used interface for integrating AI models into products, offering features like chat completions, streaming, function calling, embeddings, image generation, and speech. The article provid…
Developers can demystify AI by understanding that AI, ML, deep learning, and LLMs are nested concepts, not synonyms, and that training and inference are the two halves of a model's life, with most app developers working …
Deep neural models for click-through rate predictions suffer a sharp decline in validation performance after the first training epoch, despite falling training loss, due to feature sparsity. Researchers found that removi…
Researchers introduced a novel regularizer based on conditional mutual information to enforce separation in deep learning models, balancing fairness and utility without sacrificing performance. The study characterizes th…
Researchers evaluating image disguising methods DisguisedNets and NeuraCrypt across four medical datasets found that while these techniques preserve utility for simple classification tasks, they falter on complex tasks l…
A new book, 'Modern GPU Programming For MLSys', teaches GPU kernel optimization for machine learning systems, focusing on Blackwell architecture and techniques like GEMM and FlashAttention. Developed from Carnegie Mellon…
Researchers introduced FlatManifold, a continual learning framework that uses a Nyström manifold flattening map to handle non-stationary streams and severe label noise. The method projects data onto an orthogonalized Rep…
British autonomous-vehicle software startup Wayve is launching a new research unit called Wayve Labs, led by chief scientist Jamie Shotton, to explore embodied intelligence systems beyond self-driving cars. The lab will …
AI lead scoring uses machine learning to help financial advisors prioritize prospective clients most likely to convert, replacing manual rule-based systems with models that analyze historical data and behavioral patterns…
A Swiss family doctor has developed shii • haa, a breathing app that uses a phone's microphone to provide live biofeedback on rhythm, depth, and regularity without uploading any speech or raw audio. The app processes all…
Landmark-based embeddings on inhomogeneous random graphs offer tighter dimension-distortion trade-offs than traditional worst-case bounds, improving distance preservation in graph machine learning. A GNN-augmented varian…
Programming undergoes a technology shift roughly every decade, but the engineering fundamentals remain unchanged, argues Fagner Brack in a Medium essay. Each cycle—from punch cards to AI agents—renames the same principle…
A machine learning algorithm has been used to invent new words, such as 'lognition', defined as 'the gradual recognition of one's own individuality', and to generate alternative definitions for existing words. The projec…
A debut novel has been pulled from publishing and film/TV consideration over concerns that AI was used in its creation, according to a Deadline report cited by author John Scalzi on his blog. The issue stems from potenti…
Researchers developed an incremental approximate message passing (IAMP) algorithm for empirical risk minimization under a multi-index model, achieving near-optimal training and test error in high-dimensional asymptotics.…