Sometimes when we browse to find relevant videos, we have to spend good amount of time to see through the videos and find relevant content. In case we have a summary available for the video, a quick walkthrough can save our
Category: Gen AI For All
Resources designed for every stage of the Generative AI journey, from articles and posts to detailed documents. Each is crafted in a clear and accessible format, making them easy to understand for both beginners and experienced professionals alike.
In continuation in the document series of “Transformers Architecture”. Today I will be covering Encoders.Ever felt lost trying to understand Encoders in Transformer Architectures? You’re not alone!This comprehensive guide will be your one-stop shop to mastering this crucial NLP concept. Here’s
Unveiling Generative AI’s Power in Presentation Summaries with Microsoft PowerPoint Copilot Gone are the days of toiling over presentation summaries! Today in this document, I’m diving into the exciting world of Generative AI and its game-changing application in Microsoft PowerPoint Copilot.
Exploring Generative AI in Streamlining PowerPoint Presentation Creation: PowerPoint presentations are used across industries and across profession. With the recent development in AI and Gen AI field, creating PowerPoint presentation can be very easy exercise. In this document I will
Continuing our deep dive into Transformers, today we explore Multi-Head Attention, a crucial concept behind their success! Previously, we covered tokens, word embeddings, and self-attention. Now, we’ll focus on Multi-Head Attention: · From Self-Attention to Multi-Head Attention: We’ll bridge the gap
In the series – ‘Key Concepts for Transformers,’ I have covered Tokens, Tokenization, and Word Embeddings, Self Attention Mechanism so far. In this post, I will explain the maths behind the ‘Self-Attention Mechanism.’. In this post we will cover the
In the last two posts of the series ‘Key Concepts for Transformers,’ I covered Tokens, Tokenization, and Word Embeddings. In this post, I will explain the concept of ‘Self-Attention Mechanism.’ This is a crucial concept and a powerful tool for
In continuation to the previous post where I discussed about Tokens and Tokenization, in this document we will be discussing about “Word Embeddings”. This topic is again one of the key ones to understand before going deeper into the transformer
Transformer architecture serves as the foundation of Large Language Models. To understand Transformer Architecture, there are various concepts that need clearer understanding beforehand. In this document, and in the upcoming few, I will touch on some of the important concepts
In this second document of Generative AI deep dives series, development of Large Language model is covered. There are multiple organization, working at their individual capacity to create Large Language Models. Most of the models are tasked with specific use