Bitcoiner vs CBDCoiner kid

Knock knock. “Who is it. Come in”. Enters the young grad student. “Good morning Dr. Ben”. “Good morning Vincent”. “I have brought my paper Doctor. I am finished”. “But it has only been three months!” “Whoa!!  That is awesome!” Some kids are playing outside. “I know Doctor. But I had been thinking about this for … Read more

How My Neighbor Alice Plans to Airdrop $500K in $ALICE Tokens Over 4 Months

What happens when a blockchain game combines rewards, competition, and social tasks to re-engage its community? That is the premise behind My Neighbor Alice’s $500K airdrop, announced as part of its in-game birthday celebration. Starting June 3, the campaign is rolling out the largest airdrop in the game’s history, with 500,000 $ALICE tokens earmarked for … Read more

How Developers Struggle with Copilot (And What GitHub Has Fixed)

Table of Links Abstract and 1. Introduction 2. Methodology and 2.1. Research Questions 2.2. Data Collection 2.3. Data Labelling 2.4. Data Extraction 2.5. Data Analysis 3. Results and Interpretation and 3.1. Type of Problems (RQ1) 3.2. Type of Causes (RQ2) 3.3. Type of Solutions (RQ3) 4. Implications 4.1. Implications for the Copilot Users 4.2. Implications … Read more

How Researchers Used Grounded Theory to Decode Copilot Issues

Table of Links Abstract and 1. Introduction 2. Methodology and 2.1. Research Questions 2.2. Data Collection 2.3. Data Labelling 2.4. Data Extraction 2.5. Data Analysis 3. Results and Interpretation and 3.1. Type of Problems (RQ1) 3.2. Type of Causes (RQ2) 3.3. Type of Solutions (RQ3) 4. Implications 4.1. Implications for the Copilot Users 4.2. Implications … Read more

What Developers Wish GitHub Copilot Did Better

Table of Links Abstract and 1. Introduction 2. Methodology and 2.1. Research Questions 2.2. Data Collection 2.3. Data Labelling 2.4. Data Extraction 2.5. Data Analysis 3. Results and Interpretation and 3.1. Type of Problems (RQ1) 3.2. Type of Causes (RQ2) 3.3. Type of Solutions (RQ3) 4. Implications 4.1. Implications for the Copilot Users 4.2. Implications … Read more

What Developers Really Think About GitHub Copilot

:::info Authors: (1) Xiyu Zhou, School of Computer Science, Wuhan University, Wuhan, China (xiyuzhou@whu.edu.cn); (2) Peng Liang (Corresponding Author), School of Computer Science, Wuhan University, Wuhan, China (liangp@whu.edu.cn); (3) Beiqi Zhang, School of Computer Science, Wuhan University, Wuhan, China (zhangbeiqi@whu.edu.cn); (4) Zengyang Li, School of Computer Science, Central China Normal University, Wuhan, China (zengyangli@ccnu.edu.cn); (5) … Read more

Cloudbet Opens CS2 Austin Major Odds Following s1mple’s Loan Move To FaZe

Willemstad, Curaçao, June 3rd, 2025/GamingWire/–Odds are now live on Cloudbet for the BLAST Austin Major — with an explosive storyline already unfolding: FaZe Clan announced Oleksandr “s1mple” Kostyliev joins the roster on loan from Natus Vincere for the tournament. The switch comes on the back of benching Helvijs “broky” Saukants. s1mple’s reputation is enough to … Read more

The Infinite Jackpot No One Ever Pays For

To all the math-crunching engineers and devs out there… let’s play a game. You flip a coin. The pot starts at $2. Every time it lands tails, the pot doubles. The game ends when you hit heads—and you take home whatever’s in the pot. First toss is heads? Cool, you win $2. Tails, then heads? … Read more

Gen AI in Action: Streamlining the Product Development Lifecycle for Greater Efficiency

In product development, Gen AI solution accelerates ideation by generating innovative concepts and designs, while in manufacturing, it optimizes production through predictive modeling and process simulations. This transformative technology improves efficiency and enables businesses to explore new possibilities, fostering a shift from reactive problem-solving to proactive innovation. The future of product development belongs to those who embrace … Read more

Meet Torram, Winner of Startups of The Year 2024 in Toronto / Developer Tools

Torram takes the number 1 spot in two categories: Startup of the Year, Toronto – https://hackernoon.com/startups/north-america/north-america-toronto-canada?embedable=true Start up of the Year, Developer Tools – https://hackernoon.com/startups/industry/developer-tools?stup=671bc2b8680441f5b22d481c&embedable=true Tell us about you. Torram is building the first unified complete middleware infrastructure stack for institutional use cases on the Bitcoin network. We do this by enabling data infrastructure, institutional-grade … Read more

Tokenized Real Estate is Great for Investors, but Even Better for DeFi

Crypto’s a wild beast. Bitcoin rockets, altcoins crash, and decentralized finance (DeFi) protocols chase yield in a market that swings like a pendulum. But tokenized real estate—a massive, underrated asset class—is poised to change the game. While barely recognized as a sector, tokenized real estate is a goldmine for investors. And for DeFi, it is … Read more

When Robot Shows Human-Like Recovery and Safety Behaviors

Table of Links Abstract and 1 Introduction 2 Preliminaries 3 TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correction and 3.1 Learning Base Policies in Simulation with RL 3.2 Learning Residual Policies from Online Correction 3.3 An Integrated Deployment Framework and 3.4 Implementation Details 4 Experiments 4.1 Experiment Settings 4.2 Quantitative Comparison on Four Assembly … Read more

Multi-Token Prediction: Architecture for Memory-Efficient LLM Training

Table of Links Abstract and 1. Introduction 2. Method 3. Experiments on real data 3.1. Benefits scale with model size and 3.2. Faster inference 3.3. Learning global patterns with multi-byte prediction and 3.4. Searching for the optimal n 3.5. Training for multiple epochs and 3.6. Finetuning multi-token predictors 3.7. Multi-token prediction on natural language 4. … Read more

TRANSIC Demolishes Competition: 81% Success Rate vs 45% for Best Baseline

Table of Links Abstract and 1 Introduction 2 Preliminaries 3 TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correction and 3.1 Learning Base Policies in Simulation with RL 3.2 Learning Residual Policies from Online Correction 3.3 An Integrated Deployment Framework and 3.4 Implementation Details 4 Experiments 4.1 Experiment Settings 4.2 Quantitative Comparison on Four Assembly … Read more

The TRANSIC Challenge: Furniture Assembly vs Every Other Robot Learning Method

Table of Links Abstract and 1 Introduction 2 Preliminaries 3 TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correction and 3.1 Learning Base Policies in Simulation with RL 3.2 Learning Residual Policies from Online Correction 3.3 An Integrated Deployment Framework and 3.4 Implementation Details 4 Experiments 4.1 Experiment Settings 4.2 Quantitative Comparison on Four Assembly … Read more

The TRANSIC Recipe: Mix Simulation, Add Human Touch, Deploy Successfully

Table of Links Abstract and 1 Introduction 2 Preliminaries 3 TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correction and 3.1 Learning Base Policies in Simulation with RL 3.2 Learning Residual Policies from Online Correction 3.3 An Integrated Deployment Framework and 3.4 Implementation Details 4 Experiments 4.1 Experiment Settings 4.2 Quantitative Comparison on Four Assembly … Read more

AI Tutor Is Real, And It’s Already Here

:::info Authors: (1) Yunfan Jiang, Department of Computer Science; (2) Chen Wang, Department of Computer Science; (3) Ruohan Zhang, Department of Computer Science and Institute for Human-Centered AI (HAI); (4) Jiajun Wu, Department of Computer Science and Institute for Human-Centered AI (HAI); (5) Li Fei-Fei, Department of Computer Science and Institute for Human-Centered AI (HAI). … Read more

Testing USB Hub Throughput

I recently purchased several USB hubs advertised as supporting 10 Gbps speeds and decided to test their actual performance. Abstract: I bought some USB hubs that declare 10 Gbps and wanted to test them. In my experience, USB-related equipment often fails to deliver the advertised speeds, leading to slower-than-expected data transfers. 1 Purchasing Auxiliary USB … Read more

How I Super-Charged My LangChain-MySQL Agent: Part 2

Insert a RAG layer to My Project, and My Experience with Cursor TL;DR My first article for the LangChain-MySQL project showed how a multi‑stage LangChain agent lets you ask natural‑language questions over MySQL. Heavy prompts and repeated LLM calls, however, made the system sluggish and prone to OpenAI “429 Too Many Requests” errors. What’s new in Part … Read more

InternationalDriversAssociation.com Implicated in Bizarre PR Spam Frenzy 

InternationalDriversAssociation.com Hijacks Privacy Paradox to Sling Backlinks Because nothing says “trustworthy international driver’s license provider” like hijacking academic discussions on digital privacy to spam the internet with backlinks. That’s right, folks — InternationalDriversAssociation.com is currently associated with a “What in God’s Name Is This PR Campaign?” hall of fame. Let’s unpack this absurdity. Some ghost … Read more

Evaluating GPT and Open-Source Models on Code Mutation Tasks

:::info Authors: (1) Bo Wang, Beijing Jiaotong University, Beijing, China (wangbo_cs@bjtu.edu.cn); (2) Mingda Chen, Beijing Jiaotong University, Beijing, China (23120337@bjtu.edu.cn); (3) Youfang Lin, Beijing Jiaotong University, Beijing, China (yflin@bjtu.edu.cn); (4) Mike Papadakis, University of Luxembourg, Luxembourg (michail.papadakis@uni.lu); (5) Jie M. Zhang, King’s College London, London, UK (jie.zhang@kcl.ac.uk). ::: Table of Links Abstract and 1 Introduction … Read more

How Prompt Complexity Affects GPT-3.5 Mutation Generation Accuracy

:::info Authors: (1) Bo Wang, Beijing Jiaotong University, Beijing, China (wangbo_cs@bjtu.edu.cn); (2) Mingda Chen, Beijing Jiaotong University, Beijing, China (23120337@bjtu.edu.cn); (3) Youfang Lin, Beijing Jiaotong University, Beijing, China (yflin@bjtu.edu.cn); (4) Mike Papadakis, University of Luxembourg, Luxembourg (michail.papadakis@uni.lu); (5) Jie M. Zhang, King’s College London, London, UK (jie.zhang@kcl.ac.uk). ::: Table of Links Abstract and 1 Introduction … Read more

Comparing Costs, Usability and Results Diversity of Mutation Testing Techniques

:::info Authors: (1) Bo Wang, Beijing Jiaotong University, Beijing, China (wangbo_cs@bjtu.edu.cn); (2) Mingda Chen, Beijing Jiaotong University, Beijing, China (23120337@bjtu.edu.cn); (3) Youfang Lin, Beijing Jiaotong University, Beijing, China (yflin@bjtu.edu.cn); (4) Mike Papadakis, University of Luxembourg, Luxembourg (michail.papadakis@uni.lu); (5) Jie M. Zhang, King’s College London, London, UK (jie.zhang@kcl.ac.uk). ::: Table of Links Abstract and 1 Introduction … Read more

Experiment Design and Metrics for Mutation Testing with LLMs

:::info Authors: (1) Bo Wang, Beijing Jiaotong University, Beijing, China (wangbo_cs@bjtu.edu.cn); (2) Mingda Chen, Beijing Jiaotong University, Beijing, China (23120337@bjtu.edu.cn); (3) Youfang Lin, Beijing Jiaotong University, Beijing, China (yflin@bjtu.edu.cn); (4) Mike Papadakis, University of Luxembourg, Luxembourg (michail.papadakis@uni.lu); (5) Jie M. Zhang, King’s College London, London, UK (jie.zhang@kcl.ac.uk). ::: Table of Links Abstract and 1 Introduction … Read more

Using LLMs to Mutate Java Code

:::info Authors: (1) Bo Wang, Beijing Jiaotong University, Beijing, China (wangbo_cs@bjtu.edu.cn); (2) Mingda Chen, Beijing Jiaotong University, Beijing, China (23120337@bjtu.edu.cn); (3) Youfang Lin, Beijing Jiaotong University, Beijing, China (yflin@bjtu.edu.cn); (4) Mike Papadakis, University of Luxembourg, Luxembourg (michail.papadakis@uni.lu); (5) Jie M. Zhang, King’s College London, London, UK (jie.zhang@kcl.ac.uk). ::: Table of Links Abstract and 1 Introduction … Read more

We Designed a Study to See If AI Can Imitate Real Software Bugs

:::info Authors: (1) Bo Wang, Beijing Jiaotong University, Beijing, China (wangbo_cs@bjtu.edu.cn); (2) Mingda Chen, Beijing Jiaotong University, Beijing, China (23120337@bjtu.edu.cn); (3) Youfang Lin, Beijing Jiaotong University, Beijing, China (yflin@bjtu.edu.cn); (4) Mike Papadakis, University of Luxembourg, Luxembourg (michail.papadakis@uni.lu); (5) Jie M. Zhang, King’s College London, London, UK (jie.zhang@kcl.ac.uk). ::: Table of Links Abstract and 1 Introduction … Read more

Mutation Testing with GPT and CodeLlama

:::info Authors: (1) Bo Wang, Beijing Jiaotong University, Beijing, China (wangbo_cs@bjtu.edu.cn); (2) Mingda Chen, Beijing Jiaotong University, Beijing, China (23120337@bjtu.edu.cn); (3) Youfang Lin, Beijing Jiaotong University, Beijing, China (yflin@bjtu.edu.cn); (4) Mike Papadakis, University of Luxembourg, Luxembourg (michail.papadakis@uni.lu); (5) Jie M. Zhang, King’s College London, London, UK (jie.zhang@kcl.ac.uk). ::: Table of Links Abstract and 1 Introduction … Read more

Study Finds AI Code Mutations Help Developers Catch Bugs Faster

:::info Authors: (1) Bo Wang, Beijing Jiaotong University, Beijing, China (wangbo_cs@bjtu.edu.cn); (2) Mingda Chen, Beijing Jiaotong University, Beijing, China (23120337@bjtu.edu.cn); (3) Youfang Lin, Beijing Jiaotong University, Beijing, China (yflin@bjtu.edu.cn); (4) Mike Papadakis, University of Luxembourg, Luxembourg (michail.papadakis@uni.lu); (5) Jie M. Zhang, King’s College London, London, UK (jie.zhang@kcl.ac.uk). ::: Table of Links Abstract and 1 Introduction … Read more