BiggB

EXERCISES FOR VISUAL ACUITY Eye exercises work wonders if done regularly for 10 minutes a day. 1. Blink frequently for two minutes. 2. Slant your eyes to the right and then move your gaze in a straight line. Do the same in the opposite direction. 3. Move your gaze in different directions: right-left, up-down, circle, figure eight. 4. Close your eyes for 3-5 seconds, then open your eyes. Repeat 7 times. 5. Press on the upper eyelids with your fingers, but without much effort, hold in this position for about two seconds. Perform in series - 4-5 times each. 6. Stand near a window, focus on an object located in the immediate vicinity (a point on the glass), and then shift your gaze to a distant object. Repeat 10 times. 7. Close your eyes and slowly move your eyeballs up and down 5-10 times. 8. With open eyes draw in the air first simple geometric figures, and then complex objects and large-scale compositions.

New release from @PacktDataML available at: amzn.to/40Sp4O9 "Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based Agentic AI Framework with tool use, memory, and multi-agent workflows" Table of Contents: 🟠Introduction to Generative AI and AI agents ⚫️Understanding How AI Agents Work 🟠A Hands on Walk-Through of a Simple AI Agent ⚫️Building a Tool-Based Agentic AI Framework 🟠Implementing Custom Tools ⚫️Creating Chat Interfaces Using Slack and Chainlit 🟠Integrating with the Model Context Protocol Ecosystem ⚫️Designing Multi-Agent Systems 🟠Implementing Multi-Agent Systems with A2A ⚫️Testing, Debugging, & Troubleshooting Multi-Agent Systems 🟠Deploying Multi- Agent Systems ⚫️Advanced Topics and Future Directions

Instead of just watching an hour of Netflix, why not dive into this 2-hour Stanford lecture on AI careers? It’s packed with insights that could give you a real edge in the AI race, more than all the AI content you’ve seen this year.

Local AI for #PowerBI medium.com/microsoft-powe… #MachineLearning #ChatGPT

30 Agents Every AI Engineer Must Build — Build production-ready agent systems using proven architectures and patterns: amzn.to/41ckg6z v/ @PacktDataML — What you will learn: 1️⃣Deploy production-ready agent systems that scale securely and reliably 2️⃣Use LangChain and LangGraph to build autonomous agents with modular architectures 3️⃣Implement agents with sophisticated memory, planning, and reasoning capabilities 4️⃣Seamlessly integrate tools, APIs, and external data into agent workflows 5️⃣Establish robust evaluation frameworks to measure and optimize agent performance 6️⃣Implement guardrails and explainability features to ensure ethical and safe deployment 7️⃣Build multi-agent systems for complex, collaborative task orchestration 8️⃣Apply specific agent architectures across healthcare, finance, and legal domains

DevOps Journey – From Easy to Extreme 🔥 • 🐧 Linux Basics → 🟢 Easy • 🌿 Git & GitHub → 🟢 Easy • 📦 Package Managers → 🟢 Easy • ⚙️ Basic Scripting (Bash) → 🟢 Easy • 🔁 CI/CD Pipelines → 🟡 Easy–Medium • 🐳 Docker → 🟡 Easy–Medium • ☁️ Cloud Basics → 🟡 Easy–Medium • 🔐 Basic Security Practices → 🟡 Easy–Medium • 🌐 Networking Concepts → 🟠 Medium • 📊 Monitoring (Logs/Metrics) → 🟠 Medium • ⚖️ Load Balancing → 🟠 Medium • 🏗️ Infrastructure as Code (Terraform) → 🟠 Medium • ☸️ Kubernetes → 🔴 Hard • 🔑 IAM & Access Control → 🔴 Hard • 🔄 High Availability Systems → 🔴 Hard • 🧠 System Design → 🟣 Very Hard • 🔍 Debugging Distributed Systems → 🟣 Very Hard • ☠️ Production Outage Handling → 💀 Extreme Most people learn tools. Top 1% understand systems. #DevOps #Cloud #SRE

Building Enterprise-Level RAG Systems with #Azure From Blob to AI Search levelup.gitconnected.com/building-enter… #MachineLearning #ChatGPT

PCB Secret Codes Explained

@RH_views @KhawajaMAsif Give promise that you Dont call Trump

*اگر بھارت نے حملہ کیا تو کسی بیرونی ملک کا پریشر برداشت کریں گے نہ کسی کی کال سنیں گے منھ توڑ جواب دیں گے وزیر دفاع @KhawajaMAsif

@mark_slapinski My best guess immediately after hearing trump

Serious question Do people ACTUALLY THINK Donald Trump would fake an assassination just so he could justify building a ballroom And to distract away from the Epstein files?

@MansurQr do you think US would like this move?

🚨BREAKING: Pakistan has approved a major trade facilitation move for Iran, allowing Tehran to conduct trade with third countries through Pakistan.

@DeItaone But hold on, as per him, US already won the war. Why again?

TRUMP: THINK IRAN WAR WILL COME TO END VERY SOON AND WE WILL BE VICTORIOUS

@RapidResponse47 Was this staged to favour the ballroom?

🚨 SON DAKİKA: Yapay zekâ ses araçları için bir daha asla para ödemeyin! MICROSOFT, yapay zekâ ses aracını açık kaynaklı hale getirdi. Bir zamanlar güvenlik kontrolleri için filigranlı olan en güçlü yapay zekâ ses aracını ücretsiz olarak yeniden yayınladılar. > 10 saniyelik sesten herhangi bir sesi kopyalayın > 90 dakikalık ses oluşturun > 50'den fazla dili destekler > Gerçek zamanlı akış > Yerel olarak çalışır %100 Açık Kaynak ve Ücretsiz. github.com/microsoft/Vibe…

AI Engineering stack 👇👇 > Python — model development > Jupyter Notebook — experimentation > PyTorch — model training > Hugging Face — models & inference > Docker — packaging > Kubernetes — scaling inference > MLflow — model tracking > Apache Kafka — data pipelines > Prometheus — model metrics > Grafana — observability Learn how to deploy all of these and you’re closer to AI systems engineering than prompt tinkering.

A must read for anyone interested in building practical AI systems in 2026: Dive into Claude Code: The Design Space of Today's and Future AI Agent Systems The paper explains the architecture of a modern production-grade AI agent system (Claude Code) by analyzing its source code. This is what they call a "harness" of an agentic coding system. Learn by reading with an AI tutor: chapterpal.com/s/9b6bb47a/div… PDF: arxiv.org/pdf/2604.14228

n8n (Step by Step) - Visual Guide

Free Certification Courses to Learn Data Analytics in 2026: 1. Python 🔗 imp.i384100.net/5gmXXo 2. SQL 🔗 edx.org/learn/relation… 3. Statistics and R 🔗 edx.org/learn/r-progra… 4. Data Science: R Basics 🔗edx.org/learn/r-progra… 5. Excel and PowerBI 🔗 learn.microsoft.com/en-gb/training… 6. Data Science: Visualization 🔗edx.org/learn/data-vis… 7. Data Science: Machine Learning 🔗edx.org/learn/machine-… 8. R 🔗imp.i384100.net/rQqomy 9. Tableau 🔗imp.i384100.net/MmW9b3 Rt and Follow me and take these free courses. Will keep on sharing such resources. 10. PowerBI 🔗 lnkd.in/dpmnthEA 11. Data Science: Productivity Tools 🔗 lnkd.in/dGhPYg6N 12. Data Science: Probability 🔗mygreatlearning.com/academy/learn-… 13. Mathematics 🔗matlabacademy.mathworks.com 14. Statistics 🔗 lnkd.in/df6qksMB 15. Data Visualization 🔗imp.i384100.net/k0X6vx 16. Machine Learning 🔗 imp.i384100.net/nLbkN9 17. Deep Learning 🔗 imp.i384100.net/R5aPOR 18. Data Science: Linear Regression 🔗pll.harvard.edu/course/data-sc… 19. Data Science: Wrangling 🔗edx.org/learn/data-sci… 20. Linear Algebra 🔗 pll.harvard.edu/course/data-an… 21. Probability 🔗 pll.harvard.edu/course/data-sc… 22. Introduction to Linear Models and Matrix Algebra 🔗edx.org/learn/linear-a… 23. Data Science: Capstone 🔗 edx.org/learn/data-sci… 24. Data Analysis 🔗 pll.harvard.edu/course/data-an… 25. IBM Data Science Professional Certificate imp.i384100.net/9gxbbY 26. Neural Networks and Deep Learning imp.i384100.net/DKrLn2 27. Supervised Machine Learning: Regression and Classification imp.i384100.net/g1KJEA Rt and Follow me and take these free courses. Will keep on sharing such resources.