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@adrian_schmidt started using tool Amazon S3 , 1 month ago.

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@adrian_schmidt started using tool Amazon EC2 , 1 month ago.

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@adrian_schmidt started using tool Amazon Cloudfront , 1 month ago.

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@adrian_schmidt started using tool Amazon ALB , 1 month ago.

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@laura_garcia shared a post, 1 month, 1 week ago

Software Developer, RELIANOID

𝗕𝗲𝘁𝘁 𝗕𝗿𝗮𝘀𝗶𝗹 𝟮𝟬𝟮𝟲

📍 São Paulo, Brazil 📅 May 5–8, 2026 𝗥𝗘𝗟𝗜𝗔𝗡𝗢𝗜𝗗 is heading to 𝗕𝗲𝘁𝘁 𝗕𝗿𝗮𝘀𝗶𝗹 𝟮𝟬𝟮𝟲 — 𝘵𝘩𝘦 𝘭𝘢𝘳𝘨𝘦𝘴𝘵 𝘌𝘥𝘛𝘦𝘤𝘩 𝘦𝘷𝘦𝘯𝘵 𝘪𝘯 𝘓𝘢𝘵𝘪𝘯 𝘈𝘮𝘦𝘳𝘪𝘤𝘢. 🚀 46,000+ professionals 💡 270+ companies 🌍 One shared goal: transforming education Let’s talk about secure, scalable, and high-performance digital learning. 👉 See you at Expo Cen..

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@koukibadr shared a link, 1 month, 1 week ago

Mobile Developer, Nventive

LiveData vs StateFlow

LiveData and StateFlow both stream data reactively, but differ in two key ways:

Initialization — LiveData needs no initial value; StateFlow requires one.

Lifecycle — LiveData is lifecycle-aware by default; StateFlow is not, so you need to wrap it in repeatOnLifecycle to avoid memory leaks.

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@pramod_kumar_0820 shared a post, 1 month, 1 week ago

Software Engineer, Teknospire

How To Crack Senior Java Interviews (6–10 YOE) In 4 Weeks

#system-... #Intervi... #spring ... #java #Microse...

A practical 4-week roadmap to crack Senior Java Developer interviews (6–10 YOE), covering Core Java, Spring Boot internals, Microservices, System Design, and real-world interview strategies.

Senior Java Interviews (6–10 YOE) In 4 Weeks

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@smh started using tool TypeScript , 1 month, 1 week ago.

Story WPWeb Infotech Team

@rafidbottler shared a post, 1 month, 1 week ago

Full Stack Engineer, WPWeb Infotech

Angular vs React: Which Framework Is Better for Web Development?

Angular vs React: discover the main differences, performance, and use cases to choose the best framework for modern web development projects in 2026.

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@viktoriiagolovtseva shared a post, 1 month, 1 week ago

How to Make Your Jira Sprint Planning Really Agile

You know the drill:build a product roadmap in Jira, create your product backlog, review it, update the user stories, come up with a sprint goal before the meeting, and finally, review every story to decide which ones need to be completed this sprint. Easier said than done, right? Well-planned sprint..

Vertex AI is Google Cloud’s end-to-end machine learning and generative AI platform, designed to help teams build, deploy, and operate AI systems reliably at scale. It unifies data preparation, model training, evaluation, deployment, and monitoring into a single managed environment, reducing operational complexity while supporting advanced AI workloads.

Vertex AI supports both custom models and foundation models, including Google’s Gemini model family. It enables organizations to fine-tune models, run large-scale inference, orchestrate agentic workflows, and integrate AI into production systems with strong security, governance, and observability controls.

The platform includes tools for AutoML, custom training with TensorFlow and PyTorch, managed pipelines, feature stores, vector search, and online and batch prediction. For generative AI use cases, Vertex AI provides APIs for text, image, code, multimodal generation, embeddings, and agent-based systems, including support for Model Context Protocol (MCP) integrations.

Built for enterprise environments, Vertex AI integrates deeply with Google Cloud services such as BigQuery, Cloud Storage, IAM, and VPC, enabling secure data access and compliance. It is widely used across industries like finance, healthcare, retail, and science for applications ranging from recommendation systems and forecasting to autonomous research agents and AI-powered products.