Prompt Engineering: Detailed Notes 1. What is Prompt Engineering? Prompt engineering is the craft of designing instructions (prompts) to guide AI models to produce desired outputs. It is the simplest and most common adaptation technique—no model weights are changed (unlike finetuning). Effective prompt engineering is systematic and should be treated Read more
Chapter 2: Understanding Foundation Models Overview Foundation model design choices (training data, architecture/size, post-training) are increasingly opaque. The training process splits into pre-training (makes model capable) and post-training (aligns model to human preferences). Sampling (how outputs are chosen from all possibilities) is a crucial, often-underestimated factor impacting model behavior and Read more
Chapter 1 Summary: Introduction to Building AI Applications with Foundation Models 1. The Scaling Up of AI Models Foundation models like ChatGPT and Gemini are highly powerful but require enormous compute resources and vast amounts of data. Only a few organizations have the capability to train these models, leading to Read more
Link to paper https://arxiv.org/abs/2308.10053 Notes CRS possesses the potential to: (1) understand not only users’ historical actions but also users’ (multi-turn) natural-language inputs; (2) Provide not only recommended items but also human-like responses for multiple purposes, such as preference refinement, knowledgeable discussion, or recommendation justification.Towards this a typical conversational recommender Read more
1. Fundamentals of Data Engineering This book dives into the world of data engineering, covering everything from how data is collected and stored to how it’s processed and used. It talks about best practices, security, and designing systems that handle data efficiently and safely. 2. Four Thousand Weeks This book Read more
Machine learning can also be defined as the process of solving a practical problem by,1) collecting a dataset, and2) algorithmically training a statistical model based on that dataset Learning can be supervised, semi-supervised, unsupervised, and reinforcement. Supervised Learning In supervised learning the data analyst works with collection of labelled examples Read more
Java Platform 1 . Why is Java so popular? Overall, Java’s combination of platform independence, rich ecosystem, community support, robustness, scalability, security, backward compatibility, and versatility contributes to its enduring popularity among developers and organizations worldwide. 2 . What is platform independence? Overall, platform independence in Java simplifies software development Read more
Link to paper https://arxiv.org/abs/2308.14296 Notes The paper propose a novel algorithm, Self-Inspiring, to improve the planning ability of the LLM agent. At each intermediate planning step, the LLM “self-inspires” to consider all previously explored states to plan for next step. Literature survey Architecture Tools they used 1) DB tool1) To Read more
Executive Summary Week 1: Introduction Let’s say you have a data set with six houses, so you know the size of the houses in square feet or square meters and you know the price of the house and you want to fit a function to predict the price of a house as Read more
Amid the AI revolution, diverse AI models like large language and generative AI models have come into the limelight. These novel AI models require efficient data processing, achievable using vector embeddings. By providing semantic information to the AI models, they gain a better understanding and can perform complex tasks efficiently. Read more