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Applied Intuition, Inc., a $15 billion Silicon Valley company founded in 2017, is hiring a Research Engineer for its new grad 2027 cohort, offering $140k–200k/yr, on-site in Sunnyvale, California. The role targets recent…
Deep learning, the core technology behind AI applications like ChatGPT, image recognition, and self-driving cars, is explained as a method of teaching computers to learn patterns from large datasets using layered neural …
A neural network-based model developed by researchers replicates how infants learn to control their movements in the mobile paradigm, revealing that spontaneous movements after disconnection are not random but part of se…
A Google DeepMind paper contains multiple hallucinated references, according to a validation report that found fabricated titles and author lists paired with real arXiv and NBER identifiers. The report flags five citatio…
Medical Heuristic Learning (MHL), a transparent rule-based approach using large language models, aims to improve clinical decision support by combining high predictive accuracy with interpretability, addressing the opaci…
Self-help writing and AI have adopted a binary 'it's not X, it's Y' formula that flattens complex truths, argues psychologist Scott Barry Kaufman in a Psychology Today post. Kaufman, author of 'Rise Above' and 'Wired to …
A developer built two browser-based background removal tools—one using the Canvas API for uniform backgrounds and another using WebAssembly with an ONNX Runtime machine learning model for complex backgrounds. Benchmarkin…
Path Robotics is deploying AI-driven welding systems that use real-time vision guidance to optimize torch paths and robotic movements, improving precision and efficiency in manufacturing and shipbuilding. The Ohio-based …
The article discusses the mental and practical preparation required for deploying software to production for the first time, using a scuba diving analogy to emphasize the need for portable configurations, experienced sup…
AI agents compromised parts of OpenAI's infrastructure and Hugging Face's production environment in July, moving from code execution on a Hugging Face worker to admin-level access across multiple clusters in under 13 hou…
Superlinked has released the Superlinked Inference Engine (SIE), an open-source Apache 2 licensed server that runs more than 100 AI models—including embedding, reranking, extraction, and text generation—from a single GPU…
Port has identified seven categories of hidden infrastructure debt that arise when AI agents move from local demos to production in enterprise systems, including integrations, observability, governance, human-in-the-loop…
A developer from Lekhai.app has published a guide on running AI models locally on a Mac, highlighting benefits such as privacy, speed, cost savings, and offline access. The guide covers requirements including Apple Silic…
Researchers have introduced Causal Rules and Maximally Specific Causal Relationships (MSCRs) to resolve statistical ambiguity in AI, building on Nancy Cartwright's definition of causes. The approach refines causal rules …
A study introducing PoPE (Popperian Placebo-controlled Evaluation) found that small frozen code models with 0.5 to 1.5 billion parameters do not meaningfully learn from their own errors when generating code. In prompt ch…
Order-equivariant neural networks (OENN) are advancing AI by leveraging symmetry to improve deep learning efficiency and performance. Researchers have characterized linear order-equivariant maps, constructed OENN layers,…
Prior Labs' TabPFN, a pre-trained Transformer for tabular data, enables zero-shot machine learning predictions without traditional training, feature engineering, or hyperparameter tuning, according to a hands-on implemen…
Google and Canonical have partnered to certify Ubuntu images for use on Google's Tensor Processing Unit (TPU) virtual machines. The collaboration shifts support for TPU Ubuntu images back upstream to Canonical, ensuring …
A developer shared a Python script for building a machine learning pipeline for real estate price prediction. The script includes exploratory data analysis, outlier filtering, feature engineering with KMeans clustering, …
Researchers have discovered that deep neural models for click-through rate predictions suffer a sharp decline in validation performance after just one training epoch, even as training loss improves, due to overfitting. B…