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to recognise images of cats, you need to provide it with a lot of pictures of cats. The AI
uses data science techniques to analyse these images, learn the patterns that define a cat,
and then use that knowledge to identify cats in new images.
Developed by scientists at DAMO Academy, Alibaba's global
Fun research program, the Alibaba model scored 0.54 in the MS Marco
Fact! question-answering task, which evaluates a machine's ability to use natural
language that topped the human score of 0.539.
Computer Vision (CV)
Computer Vision is a very popular field of AI that trains a computer to understand and AI DOMAINS
interpret the visual world. Human vision starts at the “eyes” but machine uses digital
images from a camera for vision. Deep learning models and machines accurately identify
and classify objects that act according to what they see, using digital images from
camera. 159
According to Fei-Fei Li, computer vision is defined as “a subset of mainstream artificial
intelligence that deals with the science of making computers or machines visually enabled,
i.e., they can analyse and understand an image.”
What if you could map the cultural landscapes of diverse societies using AI tools?
How would you use NLP, Data analysis and CV for it?
Real Life Applications of Different Domains of AI
AI is all around us. Let us look at some real life applications of the different domains
of AI.
Applications of Data Science
Data science in AI is widely used in various real-life applications that impact our daily
lives. For instance, personalised recommendation systems on platforms like Netflix and
Amazon rely heavily on data science. These systems analyse vast amounts of user data,
such as viewing history or past purchases, to predict and suggest content or products that
users might enjoy. The AI algorithms learn from this data, allowing the platform to offer
tailored recommendations that enhance the user experience.

