createLiveAI

📄 Towards Data Science

Dec 3, 2025

The Machine Learning Advent Calendar Day 3: GNB, LDA and QDA in Excel

The article highlights the implementation of fundamental machine learning classifiersGaussian Naive Bayes (GNB), Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis (QDA)within Microsoft Excel, making these advanced algorithms accessible without specialized software. This development enables users to perform probabilistic classification tasks by translating local distance metrics into global probability estimates directly in a familiar spreadsheet environment, thereby broadening the practical application of machine learning techniques for data analysis and decision-making.

Microsoft Machine Learning

Business

📄 AI News

Dec 3, 2025

AI in manufacturing set to unleash new era of profit

Manufacturing executives are significantly increasing their investment in AI, allocating nearly half of their modernization budgets to AI-driven systems with the expectation of boosting profits within two years. According to the Future-Ready Manufacturing Study 2025 by Tata Consultancy Services (TCS) and AWS, 88% of manufacturers anticipate AI will contribute at least 5% to operating margins, with a quarter expecting gains exceeding 10%, highlighting a strategic shift to position AI as the primary driver of financial performance. However, despite the substantial financial commitment, there is a notable gap between these ambitions and the current state of factory infrastructure.

📄 Towards Data Science

Dec 3, 2025

How to Turn Your LLM Prototype into a Production-Ready System

Recent developments highlight the transition of large language models (LLMs) from experimental prototypes to production-ready systems, emphasizing the importance of turning initial "wow effect" applications into scalable, reliable solutions. While viral posts showcase rapid development of AI-powered tools that perform specific tasks in minutes, the focus now shifts toward engineering robust infrastructure and workflows that support deployment at scale, ensuring consistent performance and integration into real-world environments. This evolution underscores the need for best practices in model optimization, system architecture, and operational management to bridge the gap between innovative prototypes and practical, enterprise-grade AI solutions.

Ethics

📄 AI News

Dec 3, 2025

EY and NVIDIA to help companies test and deploy physical AI

EY has developed a comprehensive physical AI platform leveraging NVIDIA's Omniverse, Isaac, and AI Enterprise software to facilitate the deployment and management of AI-driven robots, drones, and edge devices in real-world environments. This platform enables organizations to create digital twins for modeling and testing physical systems before deployment, enhancing safety, efficiency, and operational continuity across sectors such as manufacturing, energy, and healthcare. The platform is structured around three core components: synthetic data generation for diverse physical scenarios, digital twins and robotics training for real-time performance monitoring, and governance frameworks to ensure safety, ethics, and compliance. By establishing

NVIDIA Robotics

Technology

📄 AI News

Dec 3, 2025

Amidst the Ongoing AI Infrastructure Crunch, Singularity Compute Launches Swedish GPU Cluster

Singularity Compute, the infrastructure division of decentralized AI pioneer SingularityNET, has launched its first enterprise-grade NVIDIA GPU cluster in Sweden, featuring next-generation H200 and L40S GPUs in a high-density, renewable energy-powered data center operated by Conapto. This deployment addresses the critical shortage and high cost of AI computational resources by providing affordable, cutting-edge GPU infrastructure to support both traditional enterprise AI workloads and projects within the Artificial Superintelligence (ASI) Alliance decentralized ecosystem.

NVIDIA

📄 AI News

Dec 3, 2025

Singularity Compute launches Swedish GPU cluster amid the AI infrastructure crunch

Singularity Compute, the infrastructure division of decentralized AI pioneer SingularityNET, has launched its first enterprise-grade NVIDIA GPU cluster in a renewable energy-powered data center in Stockholm, Sweden, addressing the current AI infrastructure shortage. This high-density cluster features cutting-edge NVIDIA hardware, including H200 and L40S GPUs, and aims to provide more affordable, scalable computational power for AI research and enterprise workloads, contrasting sharply with the high costs of traditional cloud GPU instances like AWSs $98/hour 8-GPU servers.

NVIDIA

📄 Towards Data Science

Dec 2, 2025

The Machine Learning Advent Calendar Day 2: k-NN Classifier in Excel

The article discusses the implementation and enhancement of the k-Nearest Neighbors (k-NN) classifier, highlighting various variants and improvements to optimize its performance. Notably, it demonstrates how the k-NN algorithm can be effectively applied within Excel, making it accessible for users without advanced programming skills, and explores modifications such as weighted voting and distance metrics to improve classification accuracy.

Machine Learning

VentureBeat AI

Ethics

📈 VentureBeat AI

Dec 2, 2025

AWS goes beyond prompt-level safety with automated reasoning in AgentCore

AWS has announced significant advancements in its AgentCore platform during re:Invent, leveraging math-based verification techniques to enhance the capabilities of agentic AI. The new featurespolicy, evaluations, and episodic memoryare designed to give enterprises greater control over autonomous agent behavior, enabling more precise regulation and performance monitoring. Additionally, AWS introduced a new class of autonomous, scalable "frontier agents," marking a shift toward more independent AI systems that can operate with minimal human intervention. A key innovation is the policy capability, which acts as an intermediary between the agent and its tools, ensuring compliance with enterprise guidelines even

GPT Claude +2

📄 Towards Data Science

Dec 1, 2025

The Machine Learning Lessons Ive Learned This Month

The article discusses recent insights into machine learning, emphasizing the importance of strategic decision-making and cost management in deploying AI solutions like GitHub Copilot. It highlights that while tools like Copilot offer significant productivity benefits, their associated costs and the necessity for careful evaluation of their impact are critical considerations for effective AI integration.

Microsoft Machine Learning

📄 Towards Data Science

Dec 1, 2025

The Machine Learning Advent Calendar Day 1: k-NN Regressor in Excel

The article introduces the k-Nearest Neighbors (k-NN) regressor as a fundamental distance-based machine learning model, demonstrating its implementation and analysis using Excel. It emphasizes the importance of feature scaling and the challenges posed by heterogeneous variables, which can distort distance calculations, thereby affecting prediction accuracy. Through practical examples involving the California Housing and Diamonds datasets, the discussion highlights both the strengths of k-NNsuch as simplicity and interpretabilityand its limitations, underscoring the critical need to carefully define the distance metric to accurately capture real-world data structures.

Machine Learning

📄 Towards Data Science

Dec 1, 2025

Why AI Alignment Starts With Better Evaluation

Effective AI alignment hinges on the ability to accurately evaluate AI systems, emphasizing that without robust assessment methods, alignment efforts are fundamentally limited. The article advocates for developing improved evaluation frameworks as a foundational step toward ensuring AI behaviors align with human values and intentions.