Think Logically
From the vantage point of the early 1990s, the personal computer seemed the very summit of human ingenuity, an instrument that placed unprecedented power upon the individual’s desk. The subsequent decades bore witness to a steady march of abstractions: the frameworks of Java and .NET civilised programming into disciplined languages; the rise of the cloud …
Building your own LLM can be a transformative step in research, product innovation, or domain-specific automation. Depending on your goals, computational resources, and available data, there are two primary paths you can take: Choose Your Track First Goal Track Description 🔧 Full control, academic/research Build from Scratch You define architecture, tokenizer, train from raw text …
In the rapidly evolving landscape of artificial intelligence, evaluating the performance of generative models has become both essential and complex. Unlike traditional machine learning models that can be assessed using clear-cut accuracy metrics, generative AI outputs are open-ended—ranging from text and images to music and code—making evaluation a multidimensional task. Whether you’re building a chatbot, …
Different Approaches to Train or Fine-Tune a Large Language Model (LLM) Large Language Models (LLMs) such as GPTs are powerful tools that can perform a wide variety of natural language processing (NLP) tasks. However, the true power of LLMs lies in their ability to be customized for specific use cases. There are several approaches to …
The Future of Quantum Computing in Artificial Intelligence The dawn of quantum computing heralds a paradigm shift, poised to redefine the boundaries of artificial intelligence (AI). This confluence of quantum mechanics and computational intelligence promises transformative potential, addressing challenges hitherto deemed insurmountable. Let us embark on a meticulous exploration of how quantum computing may illuminate …
Large Language Models (LLMs) are classified based on their architecture, purpose, training approach, scale, and deployment. Here’s a breakdown of the different types of LLM models: 1. Based on Model Architecture Transformer-Based ModelsUse the transformer architecture for natural language understanding and generation.Examples: GPT, BERT, T5, RoBERTa. RNN-Based ModelsUse recurrent neural networks or LSTMs (Long Short-Term …