Introduction What is Generative AI? It’s a question that looms in most of our minds. Generative AI has gained huge traction during the past few years. With ChatGPT blowing up during November 2022, there is no going back! Various industries are adopting Generative AI for interesting applications like content generation, marketing, engineering, research, and general… →
Hello, Community! This post is a summary of development on OpenCV 5 in the last week. You can always find the most up-to-date information on the OpenCV 5 Work Board. Many thanks to Jia Wu for her excellent notes! Latest Developments from the OpenCV Core Team: Unified Samples for Edge Detection: Improved and unified samples… →
An AI coding assistant is essentially a smart software tool that helps programmers write code more efficiently. These tools can suggest code, spot errors, and even handle some mundane aspects of coding by themselves. Think of them as very helpful aides that can make coding faster and more accurate, especially when working with unfamiliar languages… →
Introduction to Video Generation Models Generative AI has taken the world by storm with the likes of ChatGPT-4, Stable Diffusion 3, Devin AI, and now SORA. SORA is an image or text-to-video generation tool courtesy of OpenAI. Generative models are the powerhouse behind these awesome video sequences and realistic novel content. These models were trained… →
Despite the advancements in LLMs, the current models still need to continually improve to incorporate new knowledge without losing previously acquired information, a problem known as catastrophic forgetting. Current methods, such as retrieval-augmented generation (RAG), have limitations in performing tasks that require integrating new knowledge across different passages since it encodes passages in isolation, making… →
The crucial challenge of enhancing logical reasoning capabilities in Large Language Models (LLMs) is pivotal for achieving human-like reasoning, a fundamental step towards realizing Artificial General Intelligence (AGI). Current LLMs exhibit impressive performance in various natural language tasks but often need more logical reasoning, limiting their applicability in scenarios requiring deep understanding and structured problem-solving.… →
Ordered sequences, including text, audio, and code, rely on position information for meaning. Large language models (LLMs), like the Transformer architecture, lack inherent ordering information and treat sequences as sets. Position Encoding (PE) addresses this by assigning an embedding vector to each position, which is crucial for LLMs’ understanding. PE methods, including absolute and relative… →
IBM plays a crucial role in advancing AI by developing cutting-edge technologies and offering comprehensive courses. Through its AI initiatives, IBM empowers learners to harness the potential of AI in various fields. Its courses provide practical skills and knowledge, enabling individuals to implement AI solutions effectively and drive innovation in their respective domains. This article… →
Handling and retrieving information from various file types can be challenging. People often struggle with extracting content from PDFs and spreadsheets, especially when dealing with large volumes. This process can be time-consuming and inefficient, making it difficult to use the extracted information effectively for different applications, such as research or context augmentation. Existing solutions for… →
In Neural Networks, understanding how to optimize performance with a given computational budget is crucial. More processing power devoted to training neural networks usually results in better performance. However, choosing between expanding the training dataset and raising the model’s parameters is crucial when scaling computer resources. In order to optimize performance, these two factors must… →