Fundamental AI concepts

What is AI ? Software that imitates human behaviour and capabilities.

Key workloads

• Machine learning - Foundation for AI system. Teach a model to make predictions and draw conclusions
• Computer vision - AI to interpret visually through camera, video and images
• Natural Language Processing - AI to intepret written or spoken languages and respond accordingly
• Document Inteligence - AI managing , processing using high volumes of data from documents and forms.
• Knowlege mining - AI extracting information from large volume of unstructured data to create a knowledge store
• Generative AI - AI to create variety of formats including natural language, image , code etc.,

Let us learn briefly about these key topics:

MACHINE LEARNING:

Lots of data in our everyday lives - Text messages, emails, social media, photos, videos , sensors in our homes, cars ,factories etc.,

Machine learning models capture the relationship between these data.

For instance - To train the AI model to identify a dog breed involves gathering a diverse dataset of dog breed images and labelling them. The labeled data is processed using an algorithm that finds relationships between the features of the breed and the labeled ones.The results of the algorithm are encapsulated in a model.When new breed is found, the model can identify the correct label.

Machine learning in Microsoft Azure

Microsoft Azure provides the Azure Machine Learning service - a cloud-based platform for creating, managing, and publishing machine learning models.

Azure Machine Learning Studio offers multiple authoring experiences such as:

• Automated machine learning - Create ML model from data
• Azure Machine Learning designer - graphical interface with no-code for ML
• Data metric visualization - Analyse and optimize with visualization
• Notebooks - Write and run a code to integrate with studio

COMPUTER VISION:

Designed for blind and low vision community. Image classfication. Object detection , semantic segmentation, Image analysis, face detection, OCR.

For instance, Seeing AI app

Computer vision services in Microsoft Azure

Microsoft's Azure AI Vision to develop computer vision solutions. The service features are available for use and testing in the Azure Vision Studio and other programming languages.Some features of Azure AI Vision include:

• Image Analysis
• Face
• Optical Character recognition

NATURAL LANGUAGE PROCESSING

Analyse and interpret text in documents , interpret spoke language, Auto translate of spoken or written phrases, interpret the user command and act accordingly.

For instance, Starship Commander app

Natural language processing in Microsoft Azure

Microsoft's Azure AI Language to build natural language processing solutions.Explore using Azure Language studio.

Microsoft's Azure AI Speech is another service that can be used to build natural language processing solutions. Explore using Azure Speech studio.

DOCUMENT INTELLIGENCE

Can automate processing for contracts, health documents, financial forms and more.

Document intelligence in Microsoft Azure

Microsoft's Azure AI Document Intelligence to accelerate data collection from scanned documents. Explore using Document Intelligence Studio.

KNOWLEDGE MINING

Analyse from large volumes of unstructured data to create knowledge store.

Knowledge mining in Microsoft Azure:

Using Azure AI search that has tools for building indexes. Using these indexes, previously searched documents are quickly retrieved .

GENERATIVE AI

Take the natural language as input, and return appropriate responses in a variety of formats including natural language, image, code, and audio.

Generative AI in Microsoft Azure:

Azure OpenAI service - Recommended for deploying, customizing, and hosting generative AI models

Therefore, AI empowers the development of robust solutions for a wide range of issues. AI systems possess the ability to mimic human attributes, enabling them to scrutinize their surroundings, formulate predictions or deductions, and execute actions in manners previously unimaginable.