Artificial Intelligence

Familiarization with Prompt Engineering Prompt Engineering deals with the process of creating good and clear messages for smart computers like Chatbots, Chat GPT, Bard etc. Simply it means knowing how to use language in a smart way to get the right answers.  In the Artificial Intelligence world, it's for optimizing prompts to achieve specific objectives, whether it's generating creative content, providing accurate information, or solving problems efficiently. Basically, it's about tweaking the messages so the computer understands and responds well. Prompts are the input provided to a language model , and tokens are the individual units of language (like words or punctuation marks) that the model processes to generate a response. The prompt serves as the initial context or instruction for the model, guiding it on what to generate i-e text or image . Tokens are the building blocks the model uses to construct its output based on the given prompt.  Anatomy of Prompt  In the...

Introduction to Diffusion model in AI Diffusion models lie in the domain of Computer Vision. Diffusion is the model of deep learning that deals with latent or hidden variables in an image by adding or removing noise. The diffusion model operates by iteratively adding noise to an image and then attempting to reverse this process to reconstruct the original image. Diffusion models have been used for tasks such as image generation, denoising, and inpainting, and they have shown promising results in producing high-quality and diverse samples. • Noise Unwanted information that disrupts the accuracy of the picture.This noise disrupts the clarity and fidelity of the image, making it more challenging for the Artificial Intelligence model to accurately process or reconstruct the original image.         Stable Diffusion Stable diffusion is a type of Diffusion model used to generate text to image. This approach involves using diffusion techniques to generate images, ...

Discriminative Artificial Intelligence(AI) Discriminative Artificial Intelligence (AI) models are taught to distinguish between different data classes, patterns, images etc. In simple words it is a type of artificial intelligence uses Machine and Deep Learning  techniques that helps us tell different things apart. Discriminative AI focuses on learning the lines that separate different groups in our data. Instead of making new data, it looks at data we already have to figure out what it is. • Application Areas a. Image Recognition : Discriminative AI helps identify what's in pictures, like telling if it's a cat or a dog. b. Speech Recognition : It figures out different words or phrases when people talk. c. Natural Language Processing (NLP): It sorts text into different groups, like figuring out if a review is positive or negative. Working of Discriminative AI Discriminative AI learns from examples, like pictures of cats and dogs, to get better at telling them a...

Fundamentals of Machine Learning (ML) and Deep Learning (DL) • Machine Learning Machine Learning is branch of Artificial Intelligence and is popular way to perform AI tasks through various methods. Simply in ML, there is no need to instruct computers, data is given to the system and according to past experience and data , rules are made by computers and apply further to get required results. In this ML domain model of Al are trained on learning how to create general rule for themselves to perform lookalike tasks by taking specific inputs and their desired possible outputs. ML required processed data with human intervention.  Most important things to note that ML algorithms uses neural networks and their hidden layers to process to the final results but these layers  are less i-e 1 or more in ML model, which provides less refined output or results. Other things are that numerous ML algorithms do not respond better on unstructured data as well as can’t handle large amount...

  Artificial Intelligence Artificial Intelligence is a study and scientific process of creating a digital brain by instructing computers applying different methods without human involvement. In Artificial Intelligence devices learn themselves on the basis of past experiences and learnings .   Classical AI was exist some decades ago in which computers perform intelligent tasks only when specific rules are set and an input is given to them upon which they give results. That technology was not enough intelligent, usable and need of Advance AI rose. Artificial Intelligence is a study and scientific process of creating a digital brain by instructing computers applying different methods without human involvement. In Artificial Intelligence devices learn themselves on the basis of past experiences and learnings. Now a days AI is Advanced and more intelligent. AI is count as branch of Computer Science in which computers uses methods ( Machine and Deep learning ) and creating rule f...