It’s undeniable that one of the fastest-growing fields of artificial intelligence in recent years is Generative AI, particularly in the field of natural language processing. The number of systems and processes that can benefit from the use of Large Language Models (LLMs) is enormous, ranging from applications like chatbots and content generation to summarization tools, … Continued

Introduction Automatic License Plate Recognition (ALPR) refers to the task of accurately extracting license plate information from a variety of visual sources, which can range from high-resolution still images to real-time video streams from surveillance cameras.   Applications of ALPR are broad and impactful. ALPR systems are used for identifying stolen vehicles, tracking suspects, and … Continued

This blog post explores Oracle AI Vector Search, a new feature that introduces vector capabilities to the Oracle Database. Vector embeddings are a powerful tool for tasks like semantic search and Retrieval-Augmented Generation (RAG). We’ll delve into the creation, storage and search functionalities offered by Oracle AI Vector Search. Providing a practical guide for developers … Continued

Since 2017, transformers have demonstrated their superiority in performance and computational efficiency, surpassing recurrent neural networks (RNNs). The attention mechanism introduced in the paper ‘Attention is All You Need’ and their ability to parallelize training—a feat traditional RNNs struggled with—attribute this superiority. However, transformers come with a challenge: the memory and inference costs associated with … Continued

Introduction Google -particularly its DeepMind squad- has launched a set of lightweights models, called Gemma, the same that were involved in Gemini creation. It is available in two sizes, 2B and 7B. It comes with an outstanding Responsible Generative AI Toolkit, an SFT for several frameworks and ready-to-use libs and colabs. Pre-trained models or customized … Continued

Model Merging 1. Introduction Model composition is a well-known problem in the Machine Learning community. Its aim is to extend the capabilities of a model, without forgetting what it already knows. Let’s consider a situation in which we have a good performing model in a certain task (e.g. Text-to-SQL) but it was fine-tuned for that … Continued

Introduction Making a prototype of a Machine Learning solution is crucial, it acts as a cornerstone for effective problem-solving. Because it lets you quickly test and validate ideas, which is key in a field such as Machine Learning, characterized by complex algorithms and unpredictable data patterns. Through this process, teams can quickly assess the viability … Continued

1. Introduction 1.1 Motivation Have you ever found yourself tirelessly scouring the internet for that one image that perfectly conveys your creative vision, only to come up short? Perhaps you’re a content creator on the quest for visuals that align seamlessly with your ideas. But hours of web surfing yield little more than frustration. Imagine … Continued

Introduction Diffusion models have earned a special place in the AI visual Content Generation landscape, dethroning GANs and positioning themselves as the go-to approach when creating realistic content. As technologies like LoRAs and Latent Consistency Models arrived, these models started to be less restrictive in terms of time and computing resources, and new possibilities and … Continued