How Zak Brown Led the Revival of McLaren Racing
The CEO of the F1 champion-winning team discusses the hurdles he faced reversing McLaren’s negative momentum.
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Teaching robots to map large environments
A robot searching for workers trapped in a partially collapsed mine shaft must rapidly generate a map of the scene and identify its location within that scene as it navigates the treacherous terrain. Researchers have recently started building powerful machine-learning models to perform this complex task using only images from the robot’s onboard cameras, but even the best models can only process a few images at a time. In a real-world disaster where every second counts, a search-and-rescue […]
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The Machine Learning “Advent Calendar” Day 12: Logistic Regression in Excel
In this article, we rebuild Logistic Regression step by step directly in Excel. Starting from a binary dataset, we explore why linear regression struggles as a classifier, how the logistic function fixes these issues, and how log-loss naturally appears from the likelihood. With a transparent gradient-descent table, you can watch the model learn at each iteration—making the whole process intuitive, visual, and surprisingly satisfying. The post The Machine Learning “Advent Calendar” Day 12: Logistic Regression in Excel appeared […]
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Amazon’s Ring rolls out controversial, AI-powered facial-recognition feature to video doorbells
The feature lets you identify the people who regularly come to your door by creating a catalog of up to 50 faces. The company says the Ring feature is opt in and the biometric data isn’t used to train AI models.
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How Virgin Atlantic uses AI to enhance every step of travel
Virgin Atlantic CFO Oliver Byers shares how the airline is using AI to speed up development, improve decision-making, and elevate customer experience.
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🎃 A Full Month of Privacy Tips from EFF | EFFector 37.14
Instead of catching you off-guard with a jump scare this Halloween season, EFF is here to catch you up on the latest digital rights news with our EFFector newsletter! In this issue, we’re helping you take control of your online privacy with Opt Out October; explaining the UK’s attack on encryption and why it’s bad for all users; and covering shocking new details about an abortion surveillance case in Texas. Prefer to listen in? Check out our audio […]
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How to Maximize Agentic Memory for Continual Learning
Learn how to become an effective engineer with continual learning LLMs The post How to Maximize Agentic Memory for Continual Learning appeared first on Towards Data Science.
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As AI Grows More Complex, Model Builders Rely on NVIDIA
Unveiling what it describes as the most capable model series yet for professional knowledge work, OpenAI launched GPT-5.2 today. The model was trained and deployed on NVIDIA infrastructure, including NVIDIA Hopper and GB200 NVL72 systems. It’s the latest example of how leading AI builders train and deploy at scale on NVIDIA’s full-stack AI infrastructure. Pretraining: The Bedrock of Intelligence AI models are getting more capable thanks to three scaling laws: pretraining, post-training and test-time scaling. Reasoning models, which […]
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Google Colab Integrates KaggleHub for One Click Access to Kaggle Datasets, Models and Competitions
Google is closing an old gap between Kaggle and Colab. Colab now has a built in Data Explorer that lets you search Kaggle datasets, models and competitions directly inside a notebook, then pull them in through KaggleHub without leaving the editor. What Colab Data Explorer actually ships? Kaggle announced the feature recently where they describe a panel in the Colab notebook editor that connects to Kaggle search. From this panel you can: Search Kaggle datasets, models and competitions […]
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How to build AI scaling laws for efficient LLM training and budget maximization
When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions about, for instance, the model architecture, optimizers, and training datasets before committing to a model. To anticipate the quality and accuracy of a large model’s predictions, practitioners often turn to scaling laws: using smaller, cheaper models to try to approximate […]
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