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When a Simple Scraper Changed Everything My first “real” task wasn’t glamorous: scrape some data. We all start at the bottom, and scraping is a rite of passage for data engineers — turning unstructured sources into structured signals. That first job taught me a lesson I’ve carried since 2014/15: access to the right data beats cleverness — and the right pattern beats the shiniest tool. Looking back at that moment — and...
Gil Feig, co-founder and CTO of Merge, joins the show to explore Merge’s approach for reducing third-party APIs to a single call, the complexities of and need for data normalization, and the role that AI and MCP plays in the future of API functionality.
See how we turned weekly accessibility grade signals into an automated, accountable remediation workflow—powered by GitHub Copilot and cross‑functional collaboration. The post How we automated accessibility compliance in five hours with GitHub Copilot appeared first on The GitHub Blog.
TheModel Context Protocol (MCP), introduced inlate 2024, is a significant move forward towards transformingthe agentic AIrevolution by providing a mechanism for them to connect with enterprise tools, APIs, and databases. The protocol presents a standardized way for large language models (LLMs) and business workflows to communicate with business systems, databases, APIs, and even development environments. Just as Open...
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In SQL Server, ledger tables offer powerful tamper-evident functionality, which is essential for systems that require high levels of trust and auditability. Two distinct types serve different needs: insert-only ledger tables and updatable ledger tables. Insert-only tables enforce strict immutability, allowing data to be added but never altered or deleted, making them ideal for transaction logs or event sourcing....
Building robust AI infrastructure requires understanding both the theoretical foundations and practical implementation details across multiple layers of technology. This comprehensive guide provides the definitive resource for architecting, deploying, and managing AI systems at any scale — from experimental prototypes to enterprise-grade production deployments serving millions of users. Modern AI applications demand...
Large-scale social networks face a universal challenge: maintaining safe and reliable environments as user traffic grows exponentially. Manual processes often break under load, while ad-hoc machine learning models frequently fail to generalize. This article explores how a large-scale platform could address the challenge by developing a comprehensive machine learning infrastructure. Single filters or stand-alone models...
In this handbook, you'll build a basic version of Claude Code using Google's free Gemini API. If you've ever used Cursor or Claude Code as an "agentic" AI code editor, then you should be familiar with what we'll be building here. As long as you have ...
When I started using LLMs for work and personal use, I picked up on some technical terms, such as "machine learning" and "deep learning," which are the main technologies behind these LLMs. I've always been interested in learning about the differences...
Creative campaigns are no longer modern marketing; data is. And not any data: clean, contextual, and timely data that fuels specific, personalised experiences that enable quantifiable outcomes. If you have dozens (or hundreds) of campaigns running across platforms such as Google Ads, Meta, and programmatic DSPs, the infrastructure that enables this orchestration is just as important as the insights themselves. Today,...
Large Language Models (LLMs) like LLaMA 2 and Mistral are often described as “black boxes”. This means that you can see the text you give them and the responses they produce, but their inner workings remain hidden. Inside the model, billions of weigh...
Large Language Models (LLMs) like LLaMA 2 and Mistral are often described as “black boxes”. This means that you can see the text you give them and the responses they produce, but their inner workings remain hidden. Inside the model, billions of weigh...
Relevance of the Study Modern organizations are increasingly turning to cloud technologies to improve the flexibility, scalability, and efficiency of their IT infrastructure. One important tool in this process is Infrastructure as Code (IaC), which allows organizations to describe their infrastructure using code, automate the deployment process, reduce the risk of human error, and ensure consistency across different...
We all know that the internet works by sending and receiving small chunks of data called packets. Back in the early days, when the internet was still in its infancy, packets were allowed to transfer freely across a connected world, however small that world was. Anyone could send packets to your system, and you could send packets to other connected systems. All services running on systems were exposed by default. As the...
Salesforce Data Cloud offers an integrated solution for ingesting and integrating information about customers to empower businesses to provide personalized experiences at scale. At the center of the platform lies the Ingestion API, which simplifies bringing information into Data Cloud. This piece goes into the technical aspects of the Ingestion API, such as its underlying patterns, implementation, and suggestions for...
Some applications may not respond during heavy load. These outages are due to out of memory and high CPU utilization when many requests are piled up at the application entry point since the back end is not available. In this article, we will solve this problem using Red Hat OpenShift Service Mesh, which provides a way to stop sending requests to the application or API if it is unhealthy. This article shows how to...
It’s pretty impressive how apps like Discord and WhatsApp can handle millions of concurrent users, while some others struggle with just a few thousand. Today, we’ll take a look at how Erlang makes it possible to handle a massive workload while keeping the system alive and stable. submitted by /u/NoBarber9673 [link] [comments]
This episode provides insights and strategies to successfully navigate AI adoption in engineering teams. Learn how to build developer confidence and create environments that drive real results beyond the hype.
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What if you could learn what you need to know to become a full stack developer in just one video. We just published a 48-hour course on the freeCodeCamp.org YouTube channel that will take you from square one to being a hireable full-stack developer. ...
We’ve just posted a full-stack course on the freeCodeCamp.org YouTube channel that will teach you to build a complete, production-ready movie streaming application named MagicStream, complete with AI-powered movie recommendations. This course is desi...
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In Agile projects, decisions come fast and often: Which story should we pull next? Is this bug critical enough to stop the sprint? Do we ship the feature now or wait for another test cycle? Every time a Scrum team stops to analyze, debate, or wait for more data, the sprint clock keeps ticking. Delays accumulate — missed commitments, context switching, and mental fatigue ensue.Bounded Rationality, a concept introduced...
Traditional keyword-based search systems are inherently limited, as they operate on exact word matching rather than contextual understanding. For instance, a query such as “physician appointment” may fail to retrieve results containing “doctor visit”, despite their semantic equivalence. Recent advances in natural language processing, particularly through sentence transformers, address this gap by generating semantic...
I ran into some surprising issues working on my desktop Rust application when dealing with a network drive. Blogged about it. I hope it may be interesting to you. submitted by /u/urandomd [link] [comments]
The Problem: When One Big Model Falls Short Imagine you’re building an AI assistant that’s supposed to handle everything: answer customer questions, do research, write code, plan schedules, all in one go. Very likely, it will start to fall apart when things get more nuanced and complex. A single model that tries to be a jack-of-all-trades often becomes master of none. And if you need to update or improve one aspect of...
Seed7 is based on ideas from my diploma and doctoral theses about an extensible programming language (1984 and 1986). In 1989 development began on an interpreter and in 2005 the project was released as open source. Since then it is improved on a regular basis. Seed7 is about maintainability, portability, performance and memory safety. There is an automatic memory management, but there is no garbage collection process,...
Database migration is a normal, albeit crucial, task when working with Laravel applications. Database schema will be updated in this process; new columns might be added, indexes might be changed, and the table itself might be modified, all to accommodate new features or improvements in the baseline code. But database migration in a live production application is inadvisable since doing migrations can lead to...
Why Does It Matter? When we talk about a regulated workload, we talk about compliance. These compliances are industry standards that govern how data is processed, stored, and managed. That is why these workloads need to be clean and should be assessed based on controls we can prove. Examples of such practices are Least-Privilege access, encryption at rest, clear network boundaries, and auditability, to name a few. And...
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In the previous article, we learned how vLLM can yield dramatic performance gains by delivering 14x throughput as compared to traditional LLM serving systems. vLLM is important for efficient GPU utilization. But how can companies manage their vLLM instances across all of their production services? This would require a system that can manage the vLLM engine lifecycle and provide a way for applications to communicate...
In this article, you’ll learn about an important concept: Cross-Origin Resource Sharing (CORS) policy. As a developer, you might encounter a situation where a client request to the server fails, and the browser displays a red error like "CORS policy ...
Alex and Chris hop on the show to talk about a bit of technology that Alex calls “The 2nd best technological choice he’s ever made.” That technology is called Tree-sitter. It’s a code parsing tool for building ASTs (Abstract Syntax Trees) out of code. GitHub uses it to power search and “go to” functionality. The […]
Why Lead Data Quality Fails So Often In a perfect tech world, every phone number or email that flows into your product would belong to a real, reachable person. In practice, sales and marketing teams know the story is very different. Recently, two of our clients — unrelated and in different industries — came to us with a strikingly similar issue: their lead pipelines were full of contacts that looked valid but went...