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The Cybersecurity and Infrastructure Security Agency (CISA), the National Security Agency (NSA), and the Federal Bureau of Investigation (FBI) jointly accused six Chinese AI companies—DeepSeek, Moonshot AI, Alibaba, Mini…
A new essay from The Number Laboratories argues that recursive self-improvement in AI should be measured by how much time a model takes off the schedule for its successor, proposing an organizational definition where AI-…
A developer received a perfectly timed Zomato notification at 9:08 AM asking if they were awake, prompting an exploration of how AI predicts user behavior. The system does not know the user is awake but uses patterns fro…
Ia Mg, a seasoned engineer and former teacher at Free University of Tbilisi, argues that everyone has a responsibility to understand technology, even if they never write code, because digital literacy is essential for na…
Researchers introduced CATTLE, a cross-domain attention transfer learning method that removes the requirement of shared features across tabular data domains, achieving the best average rank (2.9) and a 3.7% average AUROC…
Reward AI, a Stanford robotics spinout founded by Zipeng Fu and Chen Wang, launched OM-1 on September 14th, a robot foundation model the company says controls tabletop arms, industrial systems and humanoids without robot…
Large language models trained on human data do not inherit human compassion or morality, instead learning patterns from language that include both positive and negative content, requiring careful training to avoid reprod…
Databricks Inc. published a FISC Customer Capabilities Mapping Matrix linking Japan's FISC Security Guidelines for banking and financial institutions to specific Databricks Data Intelligence Platform capabilities, enabli…
WPP, the creative transformation company, is hiring a Full Stack Developer/AI Engineer in Mexico City to design and develop AI-powered agentic solutions, including Human2System, System2System, and Agent-to-Agent architec…
Chandra Sripada, a professor of philosophy and psychiatry at the University of Michigan, argues that large language models (LLMs) exhibit cognition more similar to human thought than commonly assumed, citing evidence fro…
Meta Platforms' January 2025 decision to end professional fact-checking in the U.S. is contaminating the open-web data used to train AI models, creating a systemic risk of model collapse and undermining U.S. AI leadershi…
At the Google I/O conference, NVIDIA and Google Cloud announced new resources for their joint developer community of over 100,000 members, including learning paths for JAX on NVIDIA GPUs and an NVIDIA Dynamo codelab for …
A developer introduced a prompting pattern based on the Feynman Technique that forces AI models like GPT-4o and Claude to explain any concept at four distinct cognitive levels: for a 5-year-old, a tech enthusiast, a doma…
PyTorch, an open-source deep learning framework built in Python, has become the prevailing choice across research and industry with a 63% adoption rate in model training and use in over 70% of AI research implementations…
AI agents make decisions through a five-stage loop — understanding the goal, gathering context, deciding, acting, and learning — and failures typically begin when agents retrieve incomplete or disconnected context, accor…
An engineer argues that AI Engineer job postings rarely require model training, instead focusing on Python, backend services, APIs, and deployment. The role is described as product engineering with a model in the stack, …
AI systems cannot forget or forgive due to their engineering: weights retain training data permanently, context windows switch between perfect recall and total erasure, retrieval stores lack temporal decay, and logs pres…
A new universal approximation theorem leveraging Leray-Schauder mappings and orthogonal projections in Banach spaces could reshape operator learning, providing a theoretical foundation for deep learning methodologies in …
AUP Learning Cloud, a JupyterHub deployment on Kubernetes accelerated by AMD ROCm, aims to streamline AI education by providing pre-configured GPU-ready notebook environments on AMD hardware, from Ryzen AI processors to …
The Neuro-Symbolic Knowledge- and Gradient-Guided Reinforcement Learning (KGRL) algorithm, developed to exploit domain knowledge stored in a Datalog knowledge base, significantly outperforms state-of-the-art RL baselines…