AI Characteristics, Computer Vision, and Cognitive Computing Overview

Study Notes

The session covers different types of AI characteristics, examples of computer vision, and cognitive computing.
The speaker, Akash Singh, is a software engineer specializing in natural language processing and a graduate from IIT Bombay.
AI characteristics include being autonomous, continuously learning, reactive to new conditions, and futuristic like self-driving cars.
Types of AI mentioned are data-driven AI (e.g., weather, stock, earthquake prediction), autonomous systems (e.g., self-driving cars, space probes), and recommendation systems (e.g., Netflix, Amazon, Spotify).
Recommendation systems work by finding users similar to the individual, such as a 22-year-old female, to provide tailored suggestions.- The text discusses how individuals in Delhi and Mumbai, as residents of major Indian cities, may have similar preferences, leading to similarities in movie choices in a recommendation system.
It mentions human-like AI, such as car production AI, that can work efficiently 24/7, outperforming humans in monotonous tasks.
Cognitive computing aims to mimic human thinking and reaction processes by enabling computers to understand and process sensory information like humans.
Microsoft's cognitive services involve processing signals and inputs to assist humans in decision-making.
Natural Language Processing (NLP) analyzes human language for computers to understand and perform tasks like text classification, question-answering, language translation, and spell checking.
NLP applications include text recognition (e.g., number plates) and text summarization to condense large documents into shorter formats.
NLP enables information extraction from texts quickly, helping extract key details efficiently.
AI interacts with humans through various languages, such as English, French, Punjabi, and computer language (binary), using NLP for translation and understanding.
Chatbots like Alexa, Siri, and Google Assistant utilize speech recognition technology to process human speech and provide responses accordingly.
Computer vision enables computers to interpret digital images, videos, and photos, with applications like app development, optical character recognition, and fingerprint recognition.
The process of computer vision involves acquiring images, extracting information, and making decisions based on image patterns and pixel values.
Computer vision techniques include image classification (identifying objects in images), localization (identifying object positions), and segmentation (dividing images into objects).

Description

Explore the characteristics of AI, examples of computer vision, and the concept of cognitive computing in this detailed session by software engineer Akash Singh. Learn about data-driven AI, autonomous systems, recommendation systems, NLP, and computer vision techniques.