Skip to main content

Posts

Showing posts with the label AI

Free Google courses for Generative AI

 Google just launched a free learning path for Generative AI. If you're in tech, business, or just curious, this is worth a look. 𝟏. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈: 👉 https://lnkd.in/g7eqXQ7H ↳ Explain how generative AI works ↳ Describe generative AI model types ↳ Describe generative AI applications 𝟐. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐋𝐋𝐌: 👉 https://lnkd.in/gijvaHyZ ↳ Define large language models (LLMs) ↳ Describe LLM use cases ↳ Explain prompt tuning ↳ Describe Google’s generative AI development tools 𝟑. 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 𝐀𝐈: 👉 https://lnkd.in/gWSjT4Zq ↳ Identify the need for a responsible AI practice within an organization ↳ Recognize that decisions made at all stages of a project make an impact in Responsible AI ↳ Recognize that organizations can design an AI infrastructure to fit their own business needs and values ♻️ Repost this to help your network get started 

I asked Perplexity Pro which is the best laptop for ai work & macbook is not in the list !!

 Suggest the best laptop for ai model training that can be bought in Bangalore Top Laptops for AI Model Training (2025, Bangalore) Model Name GPU/CPU RAM Key Features & Reasons to Buy Approx. Price (INR) Availability ASUS ROG Zephyrus G14 AMD Ryzen 9/7, RTX 40XX series 16/32GB Compact, powerful CPU/GPU for deep learning; reliable ventilation 1,60,000–2,10,000 Major electronics retailers[1][2] HP Victus 15-fb3025AX Ryzen 7, NVIDIA RTX 4050+ 16/32GB Good for large datasets and image/video tasks, gaming build for high performance 1,40,000–1,60,000 HP, Amazon, local stores[3][4] Holoware AI Laptop Intel Core Ultra 5/7, Intel Arc GPU 16/32GB DDR5 India’s dedicated AI laptop, optimized for ML workloads, DDR5 RAM, efficient cooling ~1,80,000+ Direct via Holoware, Bangalore[5] HP Omen/Acer Nitro/ASUS TUF series Ryzen 7/9, RTX 4070/4080 (NVIDIA) 16–32GB RTX 4070+ GPUs, high TGP, suited for prolonged ML/deep learning tasks 1,70,000–2,00,000+ Amazon sale, HP/ASUS stores[2][4] Lenovo IdeaP...

Google I/O 2025 summary

  Google just dropped their  biggest Al updates ever during Google I/O 2025.  Here are 13 new Al updates you can't miss: Gemini Live. You can now turn on your camera, point at anything, and talk to Gemini about it in real time Imagen. Google's best image model yet Veo 3. The first video model with native sound generation Deep Research Project Astra. A JARVIS-like research prototype exploring the capabilities of a universal Al assistant Google Flow. Al filmmaking tool for creators Agent Mode. A new feature in the Gemini app that lets you state a goal, and Gemini will handle the steps to achieve it Google Jules. Jules is an Al-powered coding assistant that can read your code, write tests, fix bugs, and update dependencies Al Mode in Search. Al Mode transforms Google Search into a conversational assistant Real-time speech translation in Google Meet Google Beam. An Al-first video communication platform that turns 2D video stream...

MCP vs RAG (Model Context Protocol vs Retrieval Augmented Generation)

RAG (Retrieval-Augmented Generation) focuses on enhancing AI responses by retrieving external data, while MCP (Model Context Protocol) standardizes how AI interacts with various data sources and tools. Overview of RAG Definition: RAG is an AI architecture that improves the accuracy and relevance of responses generated by large language models (LLMs) by pulling in up-to-date information from external sources, such as databases or APIs, before generating a reply. 2 Functionality: When a user submits a query, RAG retrieves relevant content from connected data sources and appends this information to the input prompt, enriching the model's context with real-world relevance. This helps reduce inaccuracies and hallucinations in AI responses by grounding them in verifiable sources. 2 Use Cases: RAG is particularly useful in scenarios where real-time data is crucial, such as customer support, news aggregation, and any application requiring current information. 3 Sources Overview of MCP Defi...

How to deply Ollama & open web-ui on your laptop

How to deploy Ollama  Installation: Download Ollama:   Get the Ollama package from the  GitHub repository .   Install Dependencies:   Ensure you have any required dependencies, including libraries for your specific model.   Verify Installation:   Use  ollama --version  to confirm Ollama is installed correctly.   2. Model Deployment and Usage: Pull the Model:   Use the  ollama pull <model_name>  command to download the desired model.   Run the Model:   Use  ollama run <model_name>  to initiate the model's execution.   Interacting with the Model:   Ollama provides an API at  http://localhost:11434/api/generate  for interacting with the model.   Optional: Web UI:   Explore  Open WebUI  for a user-friendly interface to manage and interact with models.   Optional: Custom Applications:   Build custom applications using libraries like FastAPI and Gr...

DeepSeek R1: A Technical Deep Dive into the Next-Gen AI Search and Conversational Tool

 Artificial intelligence has become a cornerstone of modern technology, with tools like DeepSeek R1 and ChatGPT leading the charge in transforming how we interact with machines. While both are powered by advanced AI, they cater to different use cases and employ distinct technical architectures. In this article, we’ll explore the technical underpinnings of DeepSeek R1, compare it with ChatGPT, and highlight their unique capabilities. --- What is DeepSeek R1? DeepSeek R1 is an AI-driven search and conversational platform designed to deliver real-time, context-aware, and highly personalized results. Unlike traditional search engines, which rely on keyword matching and static datasets, DeepSeek R1 leverages cutting-edge natural language processing (NLP), machine learning (ML), and real-time data integration to provide dynamic and accurate responses. The "R1" in its name stands for Real-time, Relevance, and Reliability, reflecting its core strengths. It is built to handle complex ...

Power of AI - Podcast about my tech blog techbytes-madhukar.com

The podcast is auto-generated by https://notebooklm.google.com   Techbytes-madhukar.com is a blog created by Madhukar Rupakumar where he shares his insights and findings on various technology-related topics. [1] The blog features articles categorized by labels such as ".NET", "AI", "Apple products", "Blockchain", "Cloud technology", and many more. [2] Rupakumar, a Principal Systems Engineer at Hewlett Packard Enterprise with expertise in storage products, uses his platform to discuss a wide array of subjects related to technology and software. [1] The blog contains posts covering topics like:Linux commands for beginners. [3] Interview preparation guides for software engineers. [4] Free AI/ML LLM Fundamentals Courses. [5] Cloud computing and data storage terminology. [6] Free courses on various topics such as Generative AI, React, Angular, SEO, and data science. [7] Learning resources for data structures and algorithms. [8] The blog also...

Free AI/ML LLM Fundamentals Course

  Free AI/ML LLM Fundamentals Course Save 1000s of dollars. Bookmark this and follow the curriculum below. You want to learn AI/ML LLM? I have curated the Best FREE AI/ML roadmap that covers essential knowledge about maths, Python, NNs with hands-on projects Learning. 🙏 Help me spread the free courses! Kindly like, repost and comment! ♻️ Google Courses https://www.cloudskillsboost.google/?qlcampaign=6y-in1-event-90 𝟭. 𝗠𝗮𝘁𝗵𝗲𝗺𝗮𝘁𝗶𝗰𝘀 𝗳𝗼𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 • Linear Algebra - 3Blue1Brown: https://lnkd.in/ejApha3z • Immersive Linear Algebra: https://lnkd.in/ekaUs4Wz • Linear Algebra - KA: https://lnkd.in/emCEHTq5 • Calculas - KA: https://lnkd.in/emCEHTq5 • Statistics and Probability - KA: https://lnkd.in/e6_SirMr 𝟮. 𝗣𝘆𝘁𝗵𝗼𝗻 𝗳𝗼𝗿 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 • Real Python: https://realpython.com • Learn Python - freecodecamp: https://lnkd.in/ejfBftNf • Python Data Science: https://lnkd.in/g4ZysfEe • ML for Everybody: https://lnkd.in/ehR6xaG...