Introduction to Azure Artificial Intelligence (AI)

Introduction to Azure AI

• Aritificial Intelligence is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

• Types of AI:
  1. Strong AI
• Intelligence of machine = Intelligence of human
• A machine that can solve problems, learn, and plan for the future.
• An expert at everthing.
• Learns like a child, building on it’s own experiences.

1. Narrow/Weak AI
   • Focuses on specific task
   • Examples: Self driving cars and virtual assistants
   • Machine Learning: Learn from data

Building AI Solutions in Azure

1. Use Pre-Trained Models
   • Example: Azure Cognitive Services
   • Get intelligence from text, images, audio, video
2. Build Simple Models
   • Without needing data scientists
   • Example: Custom Vision
   • Example: Azure Machine Learning
   • Automated machine learning
3. Build Complex Models
   • Using data scientists and team
   • Build your own ML models from ZERO (code-experienced)
   • Example: Using Azure Machine Learning

Types of AI Workloads

1. Content Moderation & Personalization
   • Filtering inappropiate content on socoal media
   • Recommending products based on user history
   • Adjusting website content based on user preferences
2. Computer Vision Workloads
   • Facial recognition systems
   • Self-driving car navigation systems
   • Object detection in surveillance videos
   • Augmented reality applications
3. Natural Language Processing Workloads
   • Language translation services
   • Voice recongition and response systems
   • Sentiment analysis in customer feedback
4. Knowledge Mining Workloads
   • Analyzing large datasets to uncover trends
   • Extracting useful information from unstructured data
   • Mining customer data for insights
   • Predictive analytics in business intelligence
5. Document Intelligence Workloads
   • Automated invoice processing
   • Resume parsing for recruitment
   • Document classification and archiving
   • Data extraction from legel documents
6. Generative AI Workloads
   • Creating new images or text based on learned patterns
   • AI-generated music or art
   • Automated content generation for social media