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#Genai Reel by @gartner_inc (verified account) - When it comes to GenAI, the more reinforcement learning with human feedback that is applied during model training, the higher quality the model's resp
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@gartner_inc
When it comes to GenAI, the more reinforcement learning with human feedback that is applied during model training, the higher quality the model’s responses become. Comment “GenAI” below to get the executive’s guide to understanding, planning, piloting, implementing and maintaining GenAI 🔗 #GenerativeAI #GenAI #Strategy #AI
#Genai Reel by @techbyruchi - Comment "AI" and I'll send them over. If you want an AI job in 2026, your edge isn't "I'm learning GenAI." Your edge is shipping something where a m
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@techbyruchi
Comment “AI” and I’ll send them over. If you want an AI job in 2026, your edge isn’t “I’m learning GenAI.” Your edge is shipping something where a model makes a decision (or generates output) inside a real workflow, you can explain why it’s useful, you can show how you evaluated it, and you can point to one number that improved because of it. January is the best month to do this. Budgets reset, teams reopen roles, and hiring managers actually have time to review portfolios. If you want to be in the mix for Q1 roles, build now. When you share your project, structure it like a real case study: who it’s for, the problem it solves, what you built (one sentence), how you measured success (one metric), and a link people can click (demo + repo). Ship one thing in January. Write about what worked, what you learned, and what you’d do next. By February, when shortlists form, you’ll have something recent that proves you can execute. #programming #jobsearch #fyp #explorepage #explore
#Genai Reel by @coding_with_deepa - Java Developer → Agentic AI Engineer (Complete Roadmap) Most Java devs stop at calling ChatGPT APIs. That's NOT Agentic AI. Comment "Link" for the p
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@coding_with_deepa
Java Developer → Agentic AI Engineer (Complete Roadmap) Most Java devs stop at calling ChatGPT APIs. That’s NOT Agentic AI. Comment "Link" for the perfect resource to learn from Zero to Hero Agentic AI. Here’s the real path 👇 1️⃣ Core Java stays (huge advantage) Concurrency • Spring Boot • System Design 2️⃣ AI basics (no heavy math) AI vs ML vs DL • LLMs • Transformers 3️⃣ Python (only what’s needed) Scripts • NumPy • Pandas • Requests 4️⃣ LLM fundamentals Tokens • Prompting • Context window • Hallucinations 5️⃣ Java + LLM integration Spring Boot APIs • Streaming • Cost optimization 6️⃣ Agentic AI core Goal → Plan → Act → Observe → Reflect 7️⃣ Tools & Memory (RAG) Embeddings • Vector DBs • Knowledge retrieval 8️⃣ Agent frameworks LangChain(Most Enterprise Ready) • AutoGen • CrewAI 9️⃣ Multi-agent systems Manager • Worker • Critic agents 🔟 Production-ready AI Guardrails • Monitoring • Security • Cost control 💡 Agentic AI = Distributed Systems + LLMs 💡 Java devs already know HALF of this Save this 📌 Share with your Java gang ☕ Comment "Link" for the perfect resource to learn from Zero to Hero Agentic AI. #systemdesign #engineers #developers #softwareengineering #genai [coding, system design, agentic ai, genAI , developers, software engineer, coders, java]
#Genai Reel by @sferro21 (verified account) - 🚀 Comment "AI" for the direct links to these! If you're looking for a one-time solution and use AI tools only occasionally, I'd highly recommend the
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@sferro21
🚀 Comment “AI” for the direct links to these! If you’re looking for a one-time solution and use AI tools only occasionally, I’d highly recommend these free alternatives 💡 to save money on multiple AI subscriptions. #freeai #genai #aiimage #aivideo
#Genai Reel by @viktoria.semaan (verified account) - Ever wonder why your phone doesn't melt when you run a GenAI app? It's because you aren't just using 1 processor - you're using an entire symphony of
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@viktoria.semaan
Ever wonder why your phone doesn’t melt when you run a GenAI app? It’s because you aren’t just using 1 processor - you’re using an entire symphony of specialized silicon. In 2026, “compute” isn’t a monolith. Here is how the labor is actually divided: 1️⃣ 𝗖𝗣𝗨: 𝗦𝗲𝗾𝘂𝗲𝗻𝘁𝗶𝗮𝗹 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 Features powerful cores (typically 4-12) that handle diverse tasks with precision. It acts as the “General Manager,” managing system logic and complex branching that requires high single-thread speed. 2️⃣ 𝗚𝗣𝗨: 𝗠𝗮𝘀𝘀𝗶𝘃𝗲𝗹𝘆 𝗣𝗮𝗿𝗮𝗹𝗹𝗲𝗹 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 Contains thousands of smaller cores working simultaneously. This parallel throughput is what transformed AI training from a multi-week ordeal into a matter of hours. 3️⃣ 𝗧𝗣𝗨: 𝗦𝘆𝘀𝘁𝗼𝗹𝗶𝗰 𝗔𝗿𝗿𝗮𝘆 𝗳𝗼𝗿 𝗧𝗲𝗻𝘀𝗼𝗿 𝗠𝗮𝘁𝗵 Google’s custom cloud chip. Data flows in waves, reusing weights hundreds of times to minimize memory access. It powers Search and Gemini at massive scale with extreme efficiency. 4️⃣ 𝗡𝗣𝗨: 𝗢𝗻-𝗗𝗲𝘃𝗶𝗰𝗲 𝗜𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗘𝗻𝗴𝗶𝗻𝗲 The 2025 standard for edge computing. It runs AI locally—like Face ID and photo editing—preserving your privacy and battery life without needing the cloud. The future of AI isn’t just “faster” chips; it’s about architectural diversity. Share it with someone who is interested in learning AI. ___ 👋 Hi, I’m Viktoria, Principal AI Evangelist at Databricks and Educator. I make complex tech accessible. Follow for more AI insights! #AIExplained #GenAI #LearnAI #Tech #TechCareers
#Genai Reel by @theautomationguy.ai (verified account) - Google is teaching Gen AI for FREE! 🤯 Yes, you heard it right! Google has launched the Gen AI Academy (APAC Edition) for students and professionals.
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@theautomationguy.ai
Google is teaching Gen AI for FREE! 🤯 Yes, you heard it right! Google has launched the Gen AI Academy (APAC Edition) for students and professionals. 💻✨ What’s in it for you? ✅ Training directly from Google Cloud Engineers. ✅ Hands-on workshops with Vertex AI. ✅ Chance to win $10,000 in hackathons! 💰 ✅ Official Certificate & Exclusive Goodies. 🎁🎓 How to Apply? 1️⃣ Save this reel for later. 2️⃣ Comment “GOOGLE” below. 3️⃣ Check your DM for the registration link! 📩 Deadline: 31st March, 2026. Jaldi karo! ⏳ #explore #explorepage #foryou #fyp #claude
#Genai Reel by @datasciencebrain (verified account) - 🎯 Confused about which data career path to choose? Here's the REALITY of 4 major data roles in 2026: 📊 Data Analyst (₹5 LPA) Perfect for beginners
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@datasciencebrain
🎯 Confused about which data career path to choose? Here's the REALITY of 4 major data roles in 2026: 📊 Data Analyst (₹5 LPA) Perfect for beginners! Master SQL, Excel & Python basics to get started. 🔬 Data Scientist (₹12 LPA) The dream role! Requires ML, statistics & strong problem-solving skills. 💼 Business Analyst (₹7 LPA) Bridge between business & tech. Focus on requirements & process modeling. 🤖 GenAI Engineer (₹18 LPA) The hottest role right now! LLMs, RAG & prompt engineering are must-haves. 💡 The difficulty rating (⭐) shows learning curve, not your potential! Which role are you targeting? Drop a comment below! 👇 💾 Comment "RESOURCES" to get FREE learning roadmaps & resources for all these roles! 📲 Follow @datasciencebrain #datasciencebrain for Daily Notes 📝, Tips ⚙️ and Interview QA🏆 . . . . . . [dataanalytics, artificialintelligence, deeplearning, bigdata, agenticai, aiagents, statistics, dataanalysis, datavisualization, analytics, datascientist, neuralnetworks, 100daysofcode, llms, datasciencebootcamp, ai] #datascience #machinelearning #python #genai
#Genai Reel by @aiwithapoorvaa - Spend another day with me as an AI Engineer 👩‍💻🏡 Today we are using Fastapi and streamlit 👩‍💻 FastAPI + Streamlit explained (bookmark this) ⬇️ Fa
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@aiwithapoorvaa
Spend another day with me as an AI Engineer 👩‍💻🏡 Today we are using Fastapi and streamlit 👩‍💻 FastAPI + Streamlit explained (bookmark this) ⬇️ FastAPI is used to build high-performance backend APIs • Request/response validation with Pydantic • Auto-generated Swagger docs • Perfect for ML, GenAI, and microservices Streamlit is used to build interactive dashboards fast • No frontend complexity • Ideal for demos, internal tools & ML apps. #artificialintelligence #datascience #aiwithapoorva
#Genai Reel by @anakinmonkey - genAI is literally dismantling your critical thinking skills… you're better then that << 🧠 follow @anakinmonkey for more • #antiai #chatgpt #aisuc
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@anakinmonkey
genAI is literally dismantling your critical thinking skills… you’re better then that << 🧠 follow @anakinmonkey for more • #antiai #chatgpt #aisucks #creator #cosplayer
#Genai Reel by @trumpy.tales - Putin fall for Trump 😆😆 || #trump #funny #comedy #putin #maduro Make Free AI images and Videos with Memegen AI 👇 https://meme-gen.ai/?ref=8G9672U
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@trumpy.tales
Putin fall for Trump 😆😆 || #trump #funny #comedy #putin #maduro Make Free AI images and Videos with Memegen AI 👇 https://meme-gen.ai/?ref=8G9672UL
#Genai Reel by @fellowtechiebuddy - Agentic AI is the hottest space in tech right now. Companies are hiring like crazy. But most candidates can't even explain the basics. 1. Tool Use /
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@fellowtechiebuddy
Agentic AI is the hottest space in tech right now. Companies are hiring like crazy. But most candidates can’t even explain the basics. 1. Tool Use / Function Calling: Letting the agent use external tools like APIs, search, or databases to take real actions. 2. ReAct Pattern: The agent thinks (reasons) first, then acts, then observes the result, and repeats. 3. Multi-Agent Orchestration: Multiple agents working together, each handling a different part of the task. 4. Human-in-the-Loop: A human reviews or approves the agent’s action before it actually executes. 5. Agent Memory (Short-term vs Long-term): Short-term is the current conversation context. Long-term is what the agent remembers across sessions. 6. Guardrails & Safety Layers: Rules and checks that stop the agent from doing something harmful or going off track. 7. Planning & Task Decomposition: Breaking a big complex task into smaller steps the agent can handle one by one. 8. MCP (Model Context Protocol): A standard way for agents to connect with external tools and data sources. 9. A2A (Agent-to-Agent Protocol): A standard way for agents built by different teams or companies to talk to each other. 10. Agent Evaluation & Benchmarking: Testing how well your agent actually performs on real tasks, not just vibes. 11. Reflection & Self-Correction: The agent looks at its own output, realizes it made a mistake, and fixes it. 12. Context Window Management: Smartly managing what information fits inside the model’s limited input window. 13. Retrieval Augmented Generation (RAG): Pulling relevant info from external documents and feeding it to the model before it responds. 14. Agent Handoffs & Routing: Passing the task from one agent to another based on what the task needs. 15. Observability & Tracing: Tracking every step the agent took so you can debug when things go wrong.​​​​​​​​​​​​​​​​ Save this for your interview prep. You’ll thank me later. Follow along for more! [ai, tech, GenAI, ChatGPT, interviewprep, career, agents, LLMs, OpenAI, anthropic, job search, agentic AI, machine learning, AI] #tech #ai #genai #explore #career

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