Merge branch 'main' into main

.github/workflows/azure-static-web-apps-red-field-0a6ddfd03.yml

@@ -11,6 +11,9 @@ on:
 
 jobs:
   build_and_deploy_job:
+    permissions:
+      actions: write
+      checks: none
     if: github.event_name == 'push' || (github.event_name == 'pull_request' && github.event.action != 'closed')
     runs-on: ubuntu-latest
     permissions:

README.md

@@ -36,6 +36,21 @@ What we will not cover in this curriculum:
 
 For a gentle introduction to *AI in the Cloud* topics you may consider taking the [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-cacaste) Learning Path.
 
+
+## Announcement - New Curriculum on Generative AI was just released!
+
+We just released a 12 lesson curriculum on generative AI. Come learn things like:
+
+- prompting and prompt engineering
+- text and image app generation
+- search apps
+
+As usual, there's a lesson, assignments to complete, knowledge checks and challenges.
+
+Check it out:
+
+> https://aka.ms/genai-beginners
+
 ---
 # Content
 
@@ -171,8 +186,12 @@ Would you like to contribute a translation? Please read our [translation guideli
 
 Our team produces other curricula! Check out:
 
+- [AI for Beginners](https://aka.ms/ai-beginners)
+- [Data Science for Beginners](https://aka.ms/datascience-beginners)
+- [Generative AI for Beginners](https://aka.ms/genai-beginners)
 - [Web Dev for Beginners](https://aka.ms/webdev-beginners)
 - [IoT for Beginners](https://aka.ms/iot-beginners)
 - [Machine Learning for Beginners](https://aka.ms/ml-beginners)
-- [Data Science for Beginners](https://aka.ms/datascience-beginners)
-- [Generative AI for Beginners](https://aka.ms/genai-beginners)
+- [XR Development for Beginners](https://aka.ms/xr-dev-for-beginners)
+- [Mastering GitHub Copilot for AI Paired Programming](https://aka.ms/GitHubCopilotAI)
+

lessons/1-Intro/README.md

@@ -24,8 +24,14 @@ There are some tasks, however, that we do not explicitly know how to solve. Cons
 
 ## Weak AI vs. Strong AI
 
-The task of solving a specific human-like problem, such as determining a person's age from a photo, can be called **Weak AI**, because we are creating a system for only one task, and not a system that can solve many tasks, such as can be done by a human being. Of course, developing a generally intelligent computer system is also extremely interesting from many points of view, including for students of the philosophy of consciousness. Such system would be called **Strong AI**, or **[Artificial General Intelligence](https://en.wikipedia.org/wiki/Artificial_general_intelligence)** (AGI).
+Weak AI | Strong AI
+---------------------------------------|-------------------------------------
+Weak AI refers to AI systems that are designed and trained for a specific task or a narrow set of tasks.|Strong AI, or Artificial General Intelligence (AGI), refers to AI systems with human-level intelligence and understanding.
+These AI systems are not generally intelligent; they excel in performing a predefined task but lack true understanding or consciousness.|These AI systems have the ability to perform any intellectual task that a human being can do, adapt to different domains, and possess a form of consciousness or self-awareness.
+Examples of weak AI include virtual assistants like Siri or Alexa, recommendation algorithms used by streaming services, and chatbots that are designed for specific customer service tasks.|Achieving Strong AI is a long-term goal of AI research and would require the development of AI systems that can reason, learn, understand, and adapt across a wide range of tasks and contexts.
+Weak AI is highly specialized and does not possess human-like cognitive abilities or general problem-solving capabilities beyond its narrow domain.|Strong AI is currently a theoretical concept, and no AI system has reached this level of general intelligence
 
+for more infomation refer **[Artificial General Intelligence](https://en.wikipedia.org/wiki/Artificial_general_intelligence)** (AGI).
 ## The Definition of Intelligence and the Turing Test
 
 One of the problems when dealing with the term **[Intelligence](https://en.wikipedia.org/wiki/Intelligence)** is that there is no clear definition of this term. One can argue that intelligence is connected to **abstract thinking**, or to **self-awareness**, but we cannot properly define it.