Growing up, sci-fi movies always fascinated me. Remember the distress message from Princess Leia, in the form of a 3D hologram in Star Wars. Or the video calling scene from the movie Thunderbirds. By far one of my favorites is the character, J.A.R.V.I.S. an AI (Artificial Intelligence) from Iron Man, which also resembles the innovation of chatbots in today's time. Sci-fi has been the inspiration behind many such innovations.

Less than two decades ago, Deep Learning (DL), or the simulation of human neural networks, was only a concept limited to theory. Fast-forward to the present day and it is being leveraged to solve real-world problems such as converting audio-based speech to text transcripts and in the various implementations of computer vision. The underlying mechanism behind these applications is known as the Attention Mechanism or Attention Model.

The accuracy of deep learning models depends upon the quality, quantity, and contextual meaning of the training data set. However, the scarcity of this up-to-the-market data set is one of the major challenges in building DL models. 

Artificial Intelligence (AI) is everywhere. The possibility is that you are using it in one way or the other and you don't even know about it. One of the popular applications of AI in custom software development is Machine Learning (ML), in which computers, software, and devices perform via cognition (very similar to the human brain). Herein, we share few examples of machine learning that we use every day and perhaps have no idea that they are driven by ML.

In a world that is becoming increasingly interconnected, the importance of effective communication cannot be overstated. However, for the millions of individuals in the deaf and hard of hearing community, traditional communication methods often fall short, creating barriers that hinder their full participation in various aspects of life.

On average, a human speaks 700 words per day, which includes the words of actual value (i.e. words that have an intent to communicate to another person). Instant messaging, telephonic conversations, books, movies, songs, verbal (F2F) communication are amongst some of the common ways humans exchange their thoughts and information.

Large Language Models (LLMs) have long been at the forefront of artificial intelligence, leveraging vast amounts of textual data to perform tasks ranging from language translation to content generation. These models have laid the foundation for numerous applications, fundamentally transforming the way machines understand and generate human-like text. However, as the landscape of AI continues to evolve, a shift is occurring with the rise of Multimodal LLMs.

The era of guessing your size and hoping for the best when ordering clothes online is becoming a thing of the past. In today’s digital world, shoppers are looking for a more tailored experience, one that mirrors the personal touch of in-store shopping but the convenience of doing it from their own home. This is where the idea of trying on clothes virtually, with the help of smart technology, comes into play.

The introduction of chatbots revolutionized customer and brand interaction. With the ability to mimic conversations and offer instant, digital connection, chatbots made their way into businesses like a wildfire. In fact, Gartner predicts that more than 50% of enterprises will spend more annually on bots and chatbot creation than traditional mobile app development.

Vision AI (also known as Computer Vision) is a field of computer science that trains computers to replicate the human vision system. This enables digital devices (like face detectors, QR Code Scanners) to identify and process objects in images and videos, just like humans do.