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When I first tried building an Al agent, I spent three weeks reading documentation and watching YouTube tutorials. The result? Zero working agents. I was drowning in frameworks, paralyzed by choices, convinced I needed to master LangChain, AutoGen, and five other tools before writing a single line of code. Then I realized: I was doing … Read more

As credential theft surges 160% in 2025, VPN encryption alone can’t stop AI phishing, stolen logins, or malware-laced sites. X-VPN’s latest PC update transforms its VPN into a security hub, adding browser protection, dark web monitoring, and device cleanup tools. Even free users get unlimited bandwidth, 50+ servers, and a kill switch—making digital safety more … Read more

Engineer Veera Malisetty designed a custom smart home platform to unify devices across brands without cloud reliance. Using Home Assistant, Raspberry Pi, Zigbee, and Z-Wave, he built a local, private system controllable via Apple HomeKit. The platform enhances security, avoids outages, reduces fees, and adapts to his family’s routines — a model for efficient, resilient … Read more

Table of Links Abstract and 1. Introduction Preliminaries and 2.1 Factor Graphs and Parameterised Factor Graphs 2.2 The Colour Passing Algorithm The LIFAGU Algorithm Empirical Evaluation Conclusion, Acknowledgements, and References 4 Empirical Evaluation In this section, we present the results of the empirical evaluation for LIFAGU. To evaluate the performance of LIFAGU, we start with … Read more

Table of Links Abstract and 1. Introduction Preliminaries and 2.1 Factor Graphs and Parameterised Factor Graphs 2.2 The Colour Passing Algorithm The LIFAGU Algorithm Empirical Evaluation Conclusion, Acknowledgements, and References 3 The LIFAGU Algorithm As our goal is to perform lifted inference, we have to obtain a PFG where all potentials are known. To transform … Read more

How a “Kids Game” Changed How I Approach Software Development I remember when Minecraft launched in 2009. I had just graduated with a shiny New Media degree, chasing game dev dreams. My whole life was ahead of me, and it was incredibly exciting. With this new degree in hand, I had jetted off to Seattle, … Read more

London, United Kingdom, August 20th, 2025/Chainwire/–OpenServ, the leading full-stack AI app-building infrastructure in Web3, today named Joey Kheireddine as Head of Blockchain. Kheireddine joins OpenServ from his former role as Head of Engineering for Eliza Labs, bringing enterprise-scale experience at the intersection of agentic AI and crypto to accelerate OpenServ’s onchain roadmap. “OpenServ is doubling … Read more

The secret to unlocking viral content in the age of AI isn’t just about having a brilliant idea. It’s about articulating that idea to your artificial intelligence counterpart with masterful precision. This piece will dissect the anatomy of a superior AI prompt, demonstrating the stark contrast between a bland, manually created directive and a strategically … Read more

Table of Links Abstract and 1. Introduction Deep Reinforcement Learning Similar Work 3.1 Option Hedging with Deep Reinforcement Learning 3.2 Hyperparameter Analysis Methodology 4.1 General DRL Agent Setup 4.2 Hyperparameter Experiments 4.3 Optimization of Market Calibrated DRL Agents Results 5.1 Hyperparameter Analysis 5.2 Market Calibrated DRL with Weekly Re-Training Conclusions Appendix References 5 Results 5.1 … Read more

Table of Links Abstract and 1. Introduction Deep Reinforcement Learning Similar Work 3.1 Option Hedging with Deep Reinforcement Learning 3.2 Hyperparameter Analysis Methodology 4.1 General DRL Agent Setup 4.2 Hyperparameter Experiments 4.3 Optimization of Market Calibrated DRL Agents Results 5.1 Hyperparameter Analysis 5.2 Market Calibrated DRL with Weekly Re-Training Conclusions Appendix References 4 Methodology 4.1 … Read more

Table of Links Abstract and 1. Introduction Deep Reinforcement Learning Similar Work 3.1 Option Hedging with Deep Reinforcement Learning 3.2 Hyperparameter Analysis Methodology 4.1 General DRL Agent Setup 4.2 Hyperparameter Experiments 4.3 Optimization of Market Calibrated DRL Agents Results 5.1 Hyperparameter Analysis 5.2 Market Calibrated DRL with Weekly Re-Training Conclusions Appendix References 3 Similar Work … Read more

:::info Authors: (1) Reilly Pickard, Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Canada (reilly.pickard@mail.utoronto.ca); (2) F. Wredenhagen, Ernst & Young LLP, Toronto, ON, M5H 0B3, Canada; (3) Y. Lawryshyn, Department of Chemical Engineering, University of Toronto, Toronto, Canada. ::: Table of Links Abstract and 1. Introduction Deep Reinforcement Learning Similar Work 3.1 … Read more

Table of Links Abstract and 1. Introduction Related Work Proposed Dataset SymTax Model 4.1 Prefetcher 4.2 Enricher 4.3 Reranker Experiments and Results Analysis 6.1 Ablation Study 6.2 Quantitative Analysis and 6.3 Qualitative Analysis Conclusion Limitations Ethics Statement and References Appendix 6 Analysis We conduct extensive analysis to assess further the modularity of SymTax, the importance … Read more

Table of Links Abstract and 1. Introduction Related Work Proposed Dataset SymTax Model 4.1 Prefetcher 4.2 Enricher 4.3 Reranker Experiments and Results Analysis 6.1 Ablation Study 6.2 Quantitative Analysis and 6.3 Qualitative Analysis Conclusion Limitations Ethics Statement and References Appendix 5 Experiments and Results This section illustrates the various baselines, evaluation metrics and datasets used … Read more

Table of Links Abstract and 1. Introduction Related Work Proposed Dataset SymTax Model 4.1 Prefetcher 4.2 Enricher 4.3 Reranker Experiments and Results Analysis 6.1 Ablation Study 6.2 Quantitative Analysis and 6.3 Qualitative Analysis Conclusion Limitations Ethics Statement and References Appendix 4 SymTax Model We discuss the detailed architecture of our proposed model – SymTax, as … Read more

Table of Links Abstract and 1. Introduction Related Work Proposed Dataset SymTax Model 4.1 Prefetcher 4.2 Enricher 4.3 Reranker Experiments and Results Analysis 6.1 Ablation Study 6.2 Quantitative Analysis and 6.3 Qualitative Analysis Conclusion Limitations Ethics Statement and References Appendix 2 Related Work Local citation recommendation has drawn comparatively less interest than its global counterpart … Read more

:::info Authors: (1) Karan Goyal, IIIT Delhi, India (karang@iiitd.ac.in); (2) Mayank Goel, NSUT Delhi, India (mayank.co19@nsut.ac.in); (3) Vikram Goyal, IIIT Delhi, India (vikram@iiitd.ac.in); (4) Mukesh Mohania, IIIT Delhi, India (mukesh@iiitd.ac.in). ::: Table of Links Abstract and 1. Introduction Related Work Proposed Dataset SymTax Model 4.1 Prefetcher 4.2 Enricher 4.3 Reranker Experiments and Results Analysis 6.1 … Read more

Table of Links Abstract and 1 Introduction Related works Preliminaries Method: Open-YOLO 3D Experiments Conclusion and References A. Appendix 5 Experiments Datasets: We conduct our experiments using the ScanNet200 [38] and Replica [40] datasets. Our analysis on ScanNet200 is based on its validation set, comprising 312 scenes. For the 3D instance segmentation task, we utilize … Read more

Table of Links Abstract and 1 Introduction Related works Preliminaries Method: Open-YOLO 3D Experiments Conclusion and References A. Appendix 3 Preliminaries Problem formulation: 3D instance segmentation aims at segmenting individual objects within a 3D scene and assigning one class label to each segmented object. In the open-vocabulary (OV) setting, the class label can belong to … Read more

Table of Links Abstract and 1 Introduction Related works Preliminaries Method: Open-YOLO 3D Experiments Conclusion and References A. Appendix 2 Related works Closed-vocabulary 3D segmentation: The 3D instance segmentation task aims at predicting masks for individual objects in a 3D scene, along with a class label belonging to the set of known classes. Some methods … Read more

:::info Authors: (1) Mohamed El Amine Boudjoghra, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) (mohamed.boudjoghra@mbzuai.ac.ae); (2) Angela Dai, Technical University of Munich (TUM) (angela.dai@tum.de); (3) Jean Lahoud, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) ( jean.lahoud@mbzuai.ac.ae); (4) Hisham Cholakkal, Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) (hisham.cholakkal@mbzuai.ac.ae); (5) Rao Muhammad Anwer, Mohamed … Read more

$350K for a Rust developer? In crypto, that’s normal. While Big Tech is cutting jobs and slashing bonuses, blockchain companies keep burning millions to hunt down engineers and auditors. This article breaks down where the biggest paychecks are and which roles will be in highest demand in 2025. Crypto salaries remain exceptionally high because companies … Read more

The AI boom has an ugly side to it. All of the major Large Language Models (LLMs) are run on sweatshop-style labor. Millions of low-wage workers have put together billions of work hours to help scrape the internet for this revolution, and yet they never got credited or earned any noteworthy amount to make ends … Read more

How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## Two Hours With Cursor Changed How I See AI Coding By @scastiel [ 4 Min read ] For the first time … Read more

Table of Links Abstract and 1. Introduction Background and 2.1. Related Work 2.2. The Impact of XP Practices on Software Productivity and Quality 2.3. Bayesian Network Modelling Model Design 3.1. Model Overview 3.2. Team Velocity Model 3.3. Defected Story Points Model Model Validation 4.1. Experiments Setup 4.2. Results and Discussion Conclusions and References 2.2. The … Read more

Table of Links Abstract and 1. Introduction Background and 2.1. Related Work 2.2. The Impact of XP Practices on Software Productivity and Quality 2.3. Bayesian Network Modelling Model Design 3.1. Model Overview 3.2. Team Velocity Model 3.3. Defected Story Points Model Model Validation 4.1. Experiments Setup 4.2. Results and Discussion Conclusions and References 2. BACKGROUND … Read more

Introduction Let’s be honest: the journey looks almost the same for everyone. At first, you open ChatGPT and think: “Wow, this is magic!” A couple of lines of text and suddenly you’ve got code, a marketing blurb, or even a recipe suggestion. Then comes the next stage. The magic slowly turns into chaos. Prompts get … Read more

Table of Links Abstract and 1. Introduction Background and 2.1. Related Work 2.2. The Impact of XP Practices on Software Productivity and Quality 2.3. Bayesian Network Modelling Model Design 3.1. Model Overview 3.2. Team Velocity Model 3.3. Defected Story Points Model Model Validation 4.1. Experiments Setup 4.2. Results and Discussion Conclusions and References ABSTRACT A … Read more

Such a promise is so seductive: with new technology, it would be possible to save the climate without sacrificing growth. Solar panels, “clean” batteries, electric vehicles, green hydrogen, artificial intelligence to optimize energy flows, etc. The narrative of a seamless transition (compatible with consumer society) dominates political and industrial discourse today. It may be based … Read more

Alex Chiniborch, founder of Alluca Group, champions gold as the safest long-term asset. Unlike equities, fiat, or crypto, gold carries intrinsic worth, free from counterparty risk. With central banks buying record amounts and global debt topping $315T, he calls gold “generational armor” and the ultimate hedge against systemic collapse, economic uncertainty, and monetary decay.