LLMs

Good morning, AI enthusiasts. A historic AI milestone just arrived with little fanfare — with AI systems now consistently passing as humans in controlled conversations, passing the legendary Turing test. With GPT-4.5 achieving a...

Imagine a coffee company attempting to optimize its supply chain. The corporate...

The introduction and evolution of generative AI have been so sudden and intense that it’s actually quite difficult to completely appreciate just how much this technology has modified our lives.Zoom out to only three...

For years, creating robots that may move, communicate, and adapt like humans has been a significant goal in artificial intelligence. While significant progress has been made, developing robots able to adapting to latest environments...

In September 2024, OpenAI released its o1 model, trained on large-scale reinforcement learning, giving it “advanced reasoning” capabilities. Unfortunately, the small print of how they pulled this off were never shared publicly. Today, nevertheless,...

Welcome to part 2 of my LLM deep dive. If you happen to’ve not read Part 1, I highly encourage you to ascertain it out first.  Previously, we covered the primary two major stages of...

Retrieval-Augmented Generation (RAG) is a robust technique that enhances language models by incorporating external information retrieval mechanisms. While standard RAG implementations improve response relevance, they often struggle in complex retrieval scenarios. This text explores...

Why Customize LLMs? Large Language Models (Llms) are deep learning models pre-trained based on self-supervised learning, requiring an enormous amount of resources on training data, training time and holding numerous parameters. LLM have revolutionized natural...