For part 1 refer to this: Unveiling the Secrets Behind ChatGPT – Part 1 (learncodecamp.net) Implementing a Bigram Language Model When diving into the world of natural language processing (NLP) and language modeling, starting with a simple baseline model is essential. It helps establish a foundation to build upon. One of the simplest and most intuitive models for language generation is the bigram language model. This blog post will walk you through the implementation of a bigram language model using PyTorch, explaining the key concepts, steps, and code snippets along the way. ...

Introduction Hello everyone! By now, you’ve likely heard of ChatGPT, the revolutionary AI system that has taken the world and the AI community by storm. This remarkable technology allows you to interact with an AI through text-based tasks. The Technology Behind ChatGPT: Transformers The neural network that powers ChatGPT is based on the Transformer architecture, introduced in the 2017 paper “Attention is All You Need.” GPT stands for “Generatively Pre-trained Transformer.” The Transformer architecture is a landmark development in AI that revolutionized the field, primarily in natural language processing (NLP). The Transformer architecture, initially designed for machine translation, became the backbone for numerous AI applications, including ChatGPT. ...

Introduction This blog post dives into the fascinating world of computer vision, exploring how we can teach machines to “see” using convolutional neural networks (CNNs). This post is based on a lecture from MIT’s 6.S191: Introduction to Deep Learning course. What Does it Mean to “See”? Before diving into the technical details, let’s define “vision”. It’s not simply about identifying objects in an image. True vision goes beyond object recognition to understand the relationships between objects, their movements, and their future trajectories. Think about how you intuitively anticipate a pedestrian crossing the street or a car changing lanes. Building machines with this level of visual understanding is the ultimate goal. ...

Introduction In the world of software development, the ability to build and deploy applications across different architectures is invaluable. This capability becomes particularly essential when dealing with ARM-based applications such as those for embedded systems or newer ARM-based servers. In this blog post, we will explore how to build ARM64 Docker container images on an x86_64 machine using QEMU emulation and Docker’s buildx tool. Understanding the Challenge The main challenge in building Docker images for a different architecture than your host machine lies in the architecture-specific binaries and dependencies. Directly running ARM binaries on an x86_64 machine is not possible without emulation due to differences in architecture instruction sets. ...

Introduction Into to deep learning Intelligence: The ability to process information and use it for future decision-making. Artificial Intelligence (AI): Empowering computers with the ability to process information and make decisions. Machine Learning (ML): A subset of AI focused on teaching computers to learn from data. Deep Learning (DL): A subset of ML utilizing neural networks to process raw data and inform decisions. Why Deep Learning Now? The recent surge in deep learning’s capabilities can be attributed to three key factors: ...

The Busy Person’s Guide to Large Language Models: From Inner Workings to Future Possibilities (and Security Concerns) This post explores the fascinating world of large language models (LLMs) like ChatGPT and llama2, diving into their inner workings, potential future developments, and even the security challenges they present. It’s a summary of a talk by Andrej Karpathy, offering a comprehensive overview for anyone curious about this rapidly evolving technology. What are LLMs and How Do They Work? Imagine a massive file containing compressed knowledge from the internet – that’s essentially what an LLM is. It’s a complex neural network trained on vast amounts of text data, enabling it to predict and generate human-like text. The process involves two key stages: ...

Introduction Handling asynchronous operations efficiently is crucial in modern web development, especially when dealing with APIs, data fetching, and timed operations. TypeScript, a superset of JavaScript, enhances JavaScript’s capabilities, including its handling of async operations. In this article, we explore various asynchronous patterns in TypeScript, including a custom sleep function, fetching data from APIs, and handling multiple async operations simultaneously. 1. Implementing a Sleep Function JavaScript and TypeScript do not have a built-in sleep function. However, you can simulate this behavior using Promises combined with the setTimeout function. Here’s how you can implement a simple sleep function in TypeScript: ...

Introduction In today’s data-driven landscape, businesses require robust tools to efficiently process, transform, and analyze data for deriving meaningful insights. Google Dataflow is a solution, offering a powerful, fully managed service on the Google Cloud Platform (GCP) that simplifies the complexities of building data pipelines. Key Features of Google Dataflow Google Dataflow boasts several key features that make it indispensable for modern data processing needs: Unified Model for Batch and Stream Processing: Dataflow leverages the Apache Beam SDK, providing a unified approach to code both batch and streaming data pipelines. This eliminates the need for maintaining separate systems and skillsets for different processing types. Serverless and Auto-scaling: As a fully managed service, Dataflow handles infrastructure management seamlessly, automatically scaling resources based on workload to ensure cost-efficiency. Focus on Logic, not Infrastructure: Dataflow allows users to concentrate on the core logic of data transformation while handling distributed processing, fault tolerance, and resource provisioning intricacies. Rich Integration with GCP: Deep integration with other GCP services such as Cloud Pub/Sub, BigQuery, and Cloud Storage enables users to develop end-to-end data engineering solutions within the Google Cloud ecosystem. Real-Time Analytics with Pub/Sub to BigQuery Pipelines One of the most compelling use cases of Google Dataflow is its capability to build real-time data ingestion and analysis pipelines using Cloud Pub/Sub and BigQuery. Below, are outlined the steps involved in constructing such pipelines. ...

Introduction The Heart of Your TypeScript Project: A tsconfig.json file acts as the central configuration hub for your TypeScript project. It tells the TypeScript compiler (TSC) how to transform your TypeScript code into usable JavaScript. Root Signal: The presence of a tsconfig.json file signifies that the directory it lives in is the root of your TypeScript project. Why use a tsconfig.json file? Customization: It allows you to tailor the TypeScript compiler’s behavior to match your project’s specific needs and preferences. Consistency: It ensures that all developers working on the project use the same compiler settings, leading to a more consistent codebase. Efficiency: You can avoid long and repetitive command-line flags when using the tsc (TypeScript compiler) command. The tsconfig.json stores your settings. Key Sections within tsconfig.json Let’s focus on the most important section for understanding how to configure your project: ...

Introduction What are Promises? Managing Asynchronous Operations: In JavaScript, many operations (like fetching data from a server, reading a file, or waiting for a timer) take time. Promises provide a structured way to handle the results of these asynchronous operations without getting tangled up in messy callbacks. A Proxy for Future Values: A Promise is an object that represents the eventual result of an asynchronous operation. It’s like a placeholder. Initially, the promise is in a “pending” state, but eventually, it will either: Fulfilled: The operation was successful, and a value is available. Rejected: The operation failed, and you get an error explaining why. Key Methods .then() Used to handle the successful resolution of a Promise. It takes a callback function that receives the resolved value. .catch() Used to handle errors. It takes a callback function that receives the error object. .finally() Executes a callback function regardless of whether a promise is fulfilled or rejected. Often used for cleanup tasks. import console from 'console'; import { setTimeout } from 'timers'; function delay(ms: number, shouldResolve: boolean): Promisestring> { return new Promise((resolve, reject) => { setTimeout(() => { if (shouldResolve) { resolve('Promise resolved'); } else { reject('Promise rejected'); } } , ms); }); } delay(1000, true).then(function(message) { console.log(message); // This will log "Promise resolved" }).catch(function(error) { console.error(error); // This won't be called in this case }); When you create a new Promise in TypeScript, you pass an executor function to the Promise constructor. This executor function takes two arguments: a resolve function and a reject function. ...