CybAI news - - Page 2170

12 Aug

Overlay-based Decentralized Federated Learning in Bandwidth-limited Networks

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arXiv:2408.04705v1 Announce Type: new Abstract: The emerging machine learning paradigm of decentralized federated learning (DFL) has the promise of greatly boosting the deployment of artificial intelligence (AI) by directly learning across distributed agents without centralized coordination. Despite significant efforts on improving the communication efficiency of DFL, most existing solutions were based on the simplistic assumption that neighboring agents are physically adjacent in the underlying communication network, which fails to correctly capture the communication cost when learning over a general bandwidth-limited network, as encountered in many edge networks. In this work, we address this gap by leveraging recent advances in network…

12 Aug

Data-Driven Pixel Control: Challenges and Prospects

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arXiv:2408.04767v1 Announce Type: new Abstract: Recent advancements in sensors have led to high resolution and high data throughput at the pixel level. Simultaneously, the adoption of increasingly large (deep) neural networks (NNs) has lead to significant progress in computer vision. Currently, visual intelligence comes at increasingly high computational complexity, energy, and latency. We study a data-driven system that combines dynamic sensing at the pixel level with computer vision analytics at the video level and propose a feedback control loop to minimize data movement between the sensor front-end and computational back-end without compromising detection and tracking precision. Our contributions are threefold:…

12 Aug

Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspective

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arXiv:2408.04638v1 Announce Type: new Abstract: Affective Computing (AC), integrating computer science, psychology, and cognitive science knowledge, aims to enable machines to recognize, interpret, and simulate human emotions.To create more value, AC can be applied to diverse scenarios, including social media, finance, healthcare, education, etc. Affective Computing (AC) includes two mainstream tasks, i.e., Affective Understanding (AU) and Affective Generation (AG). Fine-tuning Pre-trained Language Models (PLMs) for AU tasks has succeeded considerably. However, these models lack generalization ability, requiring specialized models for specific tasks. Additionally, traditional PLMs face challenges in AG, particularly in generating diverse and emotionally rich responses. The emergence of…

12 Aug

Developer Marketing Strategy for Software Developers

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Explore the latest software development trends and challenges in this insightful blog. Learn how to navigate the complexities of cloud-based technologies, artificial intelligence, and machine learning. Discover best practices for developer marketing, including hosting webinars, workshops, and partnering with industry leaders. Perfect for Developer Marketing Managers and Developer Relations professionals aiming to stay ahead in the fast-paced digital economy. Software Development Trends and ChallengesAs technology continues to evolve at a rapid pace, the field of software development is constantly changing. In order to stay ahead of the curve, it is crucial for Developer Marketing Managers and Developer Relations professionals to…

12 Aug

Taylor Swift once said her ‘biggest fear’ was a terror attack during one of her concerts

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Taylor Swift once called a potential terror attack during her concert her "biggest fear."In an Elle article in 2019 — which resurfaced over the weekend following the cancellation of her three Vienna shows — Swift shared her fears of going on tour following a slew of terrorist attacks that had killed dozens of concertgoers."After the Manchester Arena bombing and the Vegas concert shooting, I was completely terrified to go on tour this time because I didn't know how we were going to keep 3 million fans safe over seven months," Swift wrote. "There was a tremendous amount of planning, expense,…

12 Aug

Exploring Scalability in Large-Scale Time Series in DeepVATS framework

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[Submitted on 8 Aug 2024] View a PDF of the paper titled Exploring Scalability in Large-Scale Time Series in DeepVATS framework, by Inmaculada Santamaria-Valenzuela and 2 other authors View PDF HTML (experimental) Abstract:Visual analytics is essential for studying large time series due to its ability to reveal trends, anomalies, and insights. DeepVATS is a tool that merges Deep Learning (Deep) with Visual Analytics (VA) for the analysis of large time series data (TS). It has three interconnected modules. The Deep Learning module, developed in R, manages the load of datasets and Deep Learning models from and to the Storage module.…

12 Aug

‘Heavy lifter’ drones could soon solve Mount Everest’s trash problem

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Mount Everest looks more like a landfill every year as crowds of adventurous climbers flock to its slopes.Visitors have left an estimated 50 metric tons of waste on Everest. The mountain is so full of garbage that people have called it "the world's highest garbage dump."Nepal has tried all kinds of solutions, including a mandate that climbers collect and carry out 18 pounds of garbage every time they visit or pay a fee of thousands of dollars.It has mostly, however, fallen on the literal shoulders of the Sherpa people, who live in the high mountainous regions of the Himalayas. Sherpa…

12 Aug

Novel adaptation of video segmentation to 3D MRI: efficient zero-shot knee segmentation with SAM2

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[Submitted on 8 Aug 2024] View a PDF of the paper titled Novel adaptation of video segmentation to 3D MRI: efficient zero-shot knee segmentation with SAM2, by Andrew Seohwan Yu and 5 other authors View PDF HTML (experimental) Abstract:Intelligent medical image segmentation methods are rapidly evolving and being increasingly applied, yet they face the challenge of domain transfer, where algorithm performance degrades due to different data distributions between source and target domains. To address this, we introduce a method for zero-shot, single-prompt segmentation of 3D knee MRI by adapting Segment Anything Model 2 (SAM2), a general-purpose segmentation model designed to…

12 Aug

APE: Active Learning-based Tooling for Finding Informative Few-shot Examples for LLM-based Entity Matching

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arXiv:2408.04637v1 Announce Type: new Abstract: Prompt engineering is an iterative procedure often requiring extensive manual effort to formulate suitable instructions for effectively directing large language models (LLMs) in specific tasks. Incorporating few-shot examples is a vital and effective approach to providing LLMs with precise instructions, leading to improved LLM performance. Nonetheless, identifying the most informative demonstrations for LLMs is labor-intensive, frequently entailing sifting through an extensive search space. In this demonstration, we showcase a human-in-the-loop tool called APE (Active Prompt Engineering) designed for refining prompts through active learning. Drawing inspiration from active learning, APE iteratively selects the most ambiguous examples…

12 Aug

cypress-cucumber-preprocessor

stp2y0 CommentsNewscoding, community, development, engineering, inclusive, software

npm i @bahmutov/cypress-esbuild-preprocessor -D npm i @badeball/cypress-cucumber-preprocessor -D Enter fullscreen mode Exit fullscreen mode cypress.config.js const { defineConfig } = require('cypress') const createBundler = require('@bahmutov/cypress-esbuild-preprocessor') const addCucumberPreprocessorPlugin = require('@badeball/cypress-cucumber-preprocessor').addCucumberPreprocessorPlugin const createEsbuildPlugin = require('@badeball/cypress-cucumber-preprocessor/esbuild').createEsbuildPlugin module.exports = defineConfig({ e2e: { async setupNodeEvents(on, config) { const bundler = createBundler({ plugins: [createEsbuildPlugin(config)], }) on('file:preprocessor', bundler) await addCucumberPreprocessorPlugin(on, config) return config }, specPattern: 'cypress/e2e/**/*.feature', // 设置 .feature 文件的路径 }, }) Enter fullscreen mode Exit fullscreen mode Source link lol