Artificial Intelligence

Artificial Intelligence

1. 1. Branch of Computer Science

2. 2. Refers to software of particular model developed that can perform complex tasks without human assistance.

3. 3. Simple terms- System or machines that mimic like human to perform tasks on its own and to iteratively improve itself based on the information they collect.

4. Types of AI

   • ANI (Artificial Narrow Intelligence)
     • Specializes in a particular area and can solve one problem.
   • AGI(Artificial General Intelligence)
     • Computer that is as smart as human brain across the board
   • ASI(Artificial Super Intelligence)
     • Intellect that is smarter than the best human brain in every field.

5. Sub field of AI

   • MACHINE LEARNING
     • DEEP LEARNING
       • Subset of ML; It is essentially a neural network with three or more layers, these neural networks attempt to stimulate the behavior of human brain, albeit far from matching its ability - allowing it to "learn" from large amount of data
       • Applications of Deep Learning
         • Virtual assitant
           • translating speech and language of humans
         • Facial recognition
         • Translations
           • translating speech automatically
         • Service and chatbot
           • tricky questions; continuous interactions
         • Autonomous cars
           • Understanding road scenarios, working of signals, pedestrians, significance of different signs, speed limits, etc
         • Shopping and Entertainment
     • Focuses on the use of data and algorithm to imitate the way humans learn and gradually improves itself
     • Types of ML
       • Supervised Learning
         • Under direct supervision of the model developer
         • Uses labelled data
       • Unsupervised learning
         • No answer key or human operator to provide instructions.
         • Feeds on unlabeled data
       • Reinforcement learning
         • Self sustained systems that throughout contifuous tries and fails, improve itself based ont he labeled data and interaction with incoming data
       • Semi-supervised learning
         • Similar to supervised learning but it uses both labeled and unlabed data
         • Machine learning algorithm can learn to label unlabeled data
     • Applications of ML
       • Image Recognition
         • Automatic friend tagging suggestion in FB
       • Speech Recognition
         • Google assistant, Siri, Cortana, Alexa
       • Traffic prediction
         • Google map
       • Product recommendation
         • Amazon , Netflix
       • Self driving cars
         • Tesla
       • Medical diagnosis
         • predict exact location of lesions in brain; helps in finding brain tumours
       • Automatic language translation
         • Google's GNMT ( Google Neural Machine Translation)
   • Computer vision; Natural Language Processing; Neural Networks

6. Applications of AI

   • 1. Healthcare
     • Managing Medical Reports and other data
       • Data Management application to collect, store, re-format, trace data (faster and constant access)
     • Doing repetitive jobs
       • Analyzing tests, X-rays, CT-Scans, Data entry and other mundane tasks
     • Digital consultation
       • ex: Babylon (app) in UK uses AI to give medical consultation
     • Virtual Nurses
       • ex: Sensely has developed Molly, a digital nurse to help monitor patients
     • Health Monitoring
       • wearables health trackers from fitbit, apple, garmin
   • 2. Education
     • Administrative tasks
     • Voice assistants
     • Personalized learning
     • Smart contents
     • Grading software
   • 3. Agriculture
     • Crop and soil monitoring
     • Observing crop maturity
     • Insect and plant disease detection
     • Finding bugs with code
     • Livestock health monitoring
   • 4. Security
     • Underside vehicle bomb detection
     • Home security
     • Threat screening for large events
     • Crime prevention cameras
     • Border control lie detector
   • 5.Vehicles
     • Sensor data processing
     • Path planning
     • Path execution
     • Monitoring vehicle condition
     • Insurance data collection