The Only Recursion Guide Most Beginners Will Ever Need
A beginner-friendly guide with simple examples and problems Continue reading on Towards AI »
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10 Questions About Project-Driven Organizations, Answered
Antonio Nieto-Rodriguez, author of “Powered by Projects,” on balancing operations with transformation, reducing hierarchy, and more.
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Leading the Human-AI Organization
Three CHROs on which skills matter most, how to build them at scale, and how to ensure leaders can guide organizations through rapid technological change.
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How Endava builds an agentic organization with Codex
Learn how Endava uses Codex to build an agentic organization, accelerating software delivery and reducing requirements analysis from weeks to hours.
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Quiz: BNF Notation: Dive Deeper Into Python’s Grammar
In this quiz, you’ll test your understanding of BNF Notation: Dive Deeper Into Python’s Grammar. By working through this quiz, you’ll revisit how to read Python’s grammar rules, recognize terminals and nonterminals, and interpret the BNF fragments that appear throughout the official documentation. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]
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YOLO11-LREP: A Lightweight Detection Method for Water-Surface Floating Objects on Inland Waterways Under Low-Light and Reflection Interference
Reliable visual detection of small floating objects on the water surface is a prerequisite for environmental monitoring and clean-up tasks performed by unmanned surface vehicles (USVs) on inland waterways. Such scenes are routinely degraded by low illumination at dawn and dusk, strong specular reflections, ripple-induced clutter, and large object-scale variations, which together cause missed detections, false alarms, and unstable localization. This paper proposes YOLO11-LREP, a lightweight detection framework built upon YOLO11n and tailored for water-surface floating-object recognition under […]
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A Unified Benchmark of Machine Learning and Deep Neural Networks for Tennis Match Prediction
Tennis match prediction has been studied extensively, yet the literature offers no controlled comparison of Elo ratings, classical machine learning, and deep neural networks under identical experimental conditions, leaving practitioners without clear guidance on model selection. We address this gap with a unified empirical study on 133,138 professional men’s tennis matches from the Association of Tennis Professionals tour (1968–2024). Four approaches are evaluated on the same temporally split data with a common 16-feature set and an aligned evaluation […]
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How flat is replacing fat in AWS data center networks
Routing in today’s data centers is usually governed by a data structure called a “fat tree”, which is similar to a corporate organizational chart, with nodes in each layer connecting to multiple nodes in the layer below. Here, however, the nodes of the bottom layer represent routers that want to send messages to each other, and the layers above them contain extra routers that simplify the routing procedure. A message sent by one bottom-layer router climbs the tree […]
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NBA plans AI system for automatic out-of-bounds calls
NBA Commissioner Adam Silver said the league plans to introduce an automated system for certain officiating decisions, including out-of-bounds calls. The system would use AI and cameras placed around the court to determine possession. Silver compared the approach to Hawk-Eye, the tracking technology used for line calls in tennis. Disputed call preceded Silver’s comments Silver’s appearance came after a disputed call in Game 5 of the Western Conference finals between the Oklahoma City Thunder and San Antonio Spurs. […]
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A Survey on Foundation Models for Structured Data: Tabular, Time Series, and Graphs
Foundation models have emerged as a dominant paradigm in machine learning, enabling broad generalization and efficient adaptation across diverse tasks and domains. While this paradigm has achieved remarkable success in language and vision data, its extension to structured data remains far less understood. Foundation models for structured data are an emerging yet highly impactful research area with a rapidly growing body of literature. In this survey, we provide a systematic analysis of foundation models for structured data, focusing […]
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