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 

AI tools for Software Engineers

 

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:

1. Gemini Live. You can now turn on your camera, point at anything, and talk to Gemini about it in real time
2. Imagen. Google's best image model yet
3. Veo 3. The first video model with native sound generation
4. Deep Research
5. Project Astra. A JARVIS-like research prototype exploring the capabilities of a universal Al assistant
6. Google Flow. Al filmmaking tool for creators
7. Agent Mode. A new feature in the Gemini app that lets you state a goal, and Gemini will handle the steps to achieve it
8. Google Jules. Jules is an Al-powered coding assistant that can read your code, write tests, fix bugs, and update dependencies
9. Al Mode in Search. Al Mode transforms Google Search into a conversational assistant
10. Real-time speech translation in Google Meet
11. Google Beam. An Al-first video communication platform that turns 2D video streams into realistic 3D experiences
12. Gemma 3n. A new open-source Al model optimized for mobile devices
13. Try-On. Google's Virtual Try-On feature lets you upload a photo of yourself to see how clothes would look on you

What are your thoughts on this?

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 Gradio to integrate Ollama models into your workflows. 

How to deploy open-webui

Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-compatible APIs, with built-in inference engine for RAG, making it a powerful AI deployment solution.

How to Install 🚀

Installation via Python pip 🐍

Open WebUI can be installed using pip, the Python package installer. Before proceeding, ensure you're using Python 3.11 to avoid compatibility issues.

1. Install Open WebUI: Open your terminal and run the following command to install Open WebUI:

   pip install open-webui

2. Running Open WebUI: After installation, you can start Open WebUI by executing:

   open-webui serve

This will start the Open WebUI server, which you can access at http://localhost:8080

To upgrade the Open-webui components

pip install open-webui --upgrade