20 Ways to Make Money with GPT-4

OpenAI’s GPT-4 has revolutionized the AI landscape and opened up numerous opportunities for individuals to make money. In this article, we will explore 20 ways to leverage GPT-4 and generate income. Whether you’re a freelancer, social media influencer, or aspiring entrepreneur, these strategies will help you tap into the potential of GPT-4 and make money … Read more

Can I Run OpenAI’s API in Parallel? Yes, with Python Async!

If you’re like me, you’re using OpenAI API a lot in your Python code. So the natural question arises: “How to use OpenAI’s API asynchronously by issuing multiple requests at once?” I will give you my code for asynchronous OpenAI API requests for copy and paste below. But first, allow me to give you a … Read more

How to Install Llama Index in Python

The LlamaIndex Python library is a mind-blowing 🀯 tool that lets you easily access large language models (LLMs) from your Python applications. Overview πŸ¦™ LlamaIndex is a powerful tool to implement the β€œRetrieval Augmented Generation” (RAG) concept in practical Python code. If you want to become an exponential Python developer who wants to leverage large … Read more

LlamaIndex Getting Started – Your First Example in Python

Install LlamaIndex with PIP Note that we assume you’re using OpenAI API. If you don’t want to use OpenAI, LlamaIndex automatically uses Meta’s Llama model. However, this would require roughly 12GB of your memory across GPU and CPU (at the time of writing) and run the Llama LLM models locally. πŸ§‘β€πŸ’» Tip: I recommend you … Read more

LlamaIndex – What the Fuzz?

πŸ¦™ LlamaIndex is a powerful tool to implement the “Retrieval Augmented Generation” (RAG) concept in practical Python code. If you want to become an exponential Python developer who wants to leverage large language models (aka. Alien Technology) to 10x your coding productivity, you’ve come to the right place. Let’s get started with the concept first. … Read more

Transformer vs Autoencoder: Decoding Machine Learning Techniques

An autoencoder is a neural network that learns to compress and reconstruct unlabeled data. It has two parts: an encoder that processes the input, and a decoder that reproduces it. While the original transformer model was an autoencoder with both encoder and decoder, OpenAI’s GPT series uses only a decoder. In a way, transformers are … Read more

Transformers vs Convolutional Neural Nets (CNNs)

Deep learning has revolutionized various fields, including image recognition and natural language processing. Two prominent architectures have emerged and are widely adopted: Convolutional Neural Networks (CNNs) and Transformers. CNNs and Transformers differ in their architecture, focus domains, and coding strategies. CNNs excel in computer vision, while Transformers show exceptional performance in NLP; although, with the … Read more

Transformer vs RNN: Women in Red Dresses (Attention Is All They Need?)

TL;DR: Transformers process input sequences in parallel, making them computationally efficient compared to RNNs which operate sequentially. Both handle sequential data like natural language, but Transformers don’t require data to be processed in order. They avoid recursion, capturing word relationships through multi-head attention and positional embeddings. However, traditional Transformers can only capture dependencies within their … Read more

Top 10 LLM Training Datasets – It’s Money Laundering for Copyrighted Data!

I’ve read the expression of large language models (LLMs) being “Money Laundering for Copyrighted Data” on Simon Willison’s blog. In today’s article, I’ll show you which exact training data sets open-source LLMs use, so we can gain some more insights into this new alien technology and, hopefully, get smarter and more effective prompters. Let’s get … Read more

OpenAI API Functions & Embeddings Course (7/7): Sentiment Analysis using Embeddings

πŸ’‘ Full Course with Videos and Course Certificate (PDF): https://academy.finxter.com/university/openai-api-function-calls-and-embeddings/ Course Overview Welcome back to the final part of this tutorial series. In this part, we’ll be looking at simple sentiment analysis using embeddings. For most text classification tasks, fine-tuned machine learning models will do better than embeddings, because they have been meticulously tuned and … Read more

OpenAI API Functions & Embeddings Course (6/7): Similarity Comparison with Embeddings

πŸ’‘ Full Course with Videos and Course Certificate (PDF): https://academy.finxter.com/university/openai-api-function-calls-and-embeddings/ Course Overview Welcome back to part 6 of this tutorial series. In this part, we’re going to be looking at embeddings. What is an embedding? Without getting into algorithmic arithmetic an embedding is basically a numerical (vector) representation of text that makes no sense to … Read more