neural network

Large language models(LLMs) are advanced artificial intelligence(AI) models engineered to understand human language as well as generate human-like responses. These are trained on a large amount of text data sets — hence the name “large” — built on a type of neural network called a transformer model. These are used in chatbots and virtual assistants, content generation, summarization, translation, code generation, etc. A notable feature of LLMs is their ability to be fine-tuned. These can be further trained to enhance…

LinkedIn's feed has come a long way since the early days of assembling the machine-learning infrastructure that powers it. Recently, a major update to this infrastructure was released. We caught up with the people behind it to discuss how the principle of being people-centric translates to technical terms and implementation.  Introduction How do data and machine learning-powered algorithms work to control newsfeeds and spread stories? How much of that is automated, how much should you be able to understand and control,…

Transformers have become the model architecture of choice for many vision tasks. Vision Transformers (ViTs) are especially popular. They apply the transformer directly to sequences of image patches. ViTs now match or exceed CNNs on benchmarks like image classification. However, researchers from Meta and INRIA have identified some strange artifacts in the inner workings of ViTs. In this post, we'll do a deep dive into a new paper investigating the cause of these artifacts. And we'll see how researchers used a simple…

The rise of Generative Artificial Intelligence (GenAI) has introduced innovative services and cutting-edge tools to automate tasks, optimize processes, and speed up transactions. These benefits make it more enticing for businesses to deploy AI services for their expansion and growth strategies. One important technological breakthrough that has made this growth possible is the conditional generative adversarial network (CGAN). What Are Generative Adversarial Networks? Before diving in, we first need to explain the “GAN” in…

Computer vision, as an integral component of artificial intelligence, is gaining increasing significance within the insurance sector. Its implementation yields manifold advantages, such as process automation, cost reduction, heightened precision, and an enhanced customer experience. Computer vision technology brings many opportunities, including the replacement of manual inspection to a certain extent. That’s why the Intelliarts team found it promising to start working on an automated car damage assessment project.  In…

Neural networks and deep learning have revolutionized the field of artificial intelligence and machine learning by enabling remarkable advancements in various domains.  This research article aims to comprehensively introduce the fundamentals of neural networks and deep learning.  We start with the basic building blocks of neural networks and delve into the concepts of neurons, activation functions, and layers.  Subsequently, we explore the deep learning models' architecture and working principles, emphasizing their…

The Proof Is in the Preparation Training an AI model might sound easy: give a neural network some data and bam, you got yourself an AI. This is far from the truth and there are numerous factors that go into developing the right model for the right job. Developing a quality AI deployment is 90% in the prep coupled with continuous iterations and constant monitoring. Successfully developing and implementing AI systems is a complex process fraught with potential pitfalls. These shortcomings can lead to suboptimal outcomes,…

In recent years, artificial intelligence (AI) has played a more increasingly important role in the field of genomics, the study of an organism's genetic material. With the advancements in AI and machine learning, scientists can now analyze vast amounts of genomic data more accurately and efficiently than ever before. This has led to a wealth of new insights into the workings of our genetic code and has enabled the development of novel therapies for genetic diseases and healthcare innovations. In this article, we…

An open-source software library for artificial intelligence and machine learning is called TensorFlow. Although it can be applied to many tasks, deep neural network training and inference are given special attention. Google Brain, the company's artificial intelligence research division, created TensorFlow. Since its initial release in 2015, it has grown to rank among the most widely used machine learning libraries worldwide. Python, C++, and Java are just a few of the programming languages that TensorFlow is accessible.…

New Types of Graphs, and a New Era for the Year of the Graph Newsletter The Year of the Graph Newsletter, keeping track of all things Graph year over year, is back after a long hiatus. Read on to learn more about how the evolution of the newsletter follows the evolution of the domain and how to be involved, as well as industry news and analysis hot off the press: The evolution of graph and the Year of the Graph Newsletter Knowledge graphs are in conversational mode Graph database growth going strong through the…