AI People
How do humans trigger A.I. Artificial Intelligence adoption? Humans have tons of needs and love to have tons of new stuff in one lifetime including comfort, easiness, convenience, solving problems, having ready-made solutions, fun, excel on top of others, plus tons of other stuff. You can create a dictionary
AI Products
OpenAI’s ChatGPT is one of the most successful Artificial Intelligence (AI) products with enterprise-level capabilities that most companies can leverage and boost business capabilities. It is a tool that every employee would like to use and boost certain outcomes. It has an API with a vast knowledge base and
Inside AI
Pose estimation, in the context of artificial intelligence (AI) and machine learning (ML), is the process of determining the spatial position and orientation (pose) of an object or multiple objects within an image or a video frame. It involves locating key points or landmarks on objects and estimating their positions
Inside AI
Semantic segmentation is a type of computer vision task that involves assigning each pixel in an image to a semantic class, such as "person," "car," "tree," or "building." This is in contrast to image classification, which assigns a single class label to
AI Algorithms
Single-shot detectors, often abbreviated as SSDs, are a type of object detection model used in the field of artificial intelligence (AI) and machine learning (ML). They are designed to efficiently and accurately detect and locate objects within images or video frames. SSDs are known for their speed and ability to
Inside AI
Localization and object detection are computer vision tasks within the field of artificial intelligence (AI) and machine learning (ML) that involve identifying and precisely locating objects within an image or video. While they share similarities, these tasks have distinct goals: 1. Object Detection: Goal: The primary goal of object detection
Inside AI
Word embeddings are a type of word representation used in artificial intelligence (AI) and machine learning (ML) to convert words or tokens into numerical vectors. These numerical vectors capture semantic information about words, allowing machines to understand and process human language more effectively. Word embeddings are a crucial component in
Inside AI
Sequence modeling is a type of machine learning that is used to learn from and predict sequential data. Sequential data is data that has a natural order, such as text, audio, video, and time-series data. Sequence modeling is a subfield of artificial intelligence (AI) and machine learning (ML) that focuses
AI Algorithms
Graph Neural Networks (GNNs) are a class of artificial neural networks designed to work with structured data represented as graphs. A graph neural network (GNN) is a type of artificial neural network that is designed to process graph data. Graphs are a powerful way to represent data with relationships between
AI Algorithms
A Generative Adversarial Network (GAN) is a class of artificial neural networks used in artificial intelligence (AI) and machine learning (ML) for generative tasks. GANs were introduced by Ian Goodfellow and his colleagues in 2014 and have since become a fundamental and powerful tool in the field of deep learning.
AI Algorithms
A Restricted Boltzmann Machine (RBM) is a type of artificial neural network used in artificial intelligence (AI) and machine learning (ML). RBMs are a type of generative stochastic artificial neural network that can learn a probability distribution over its set of inputs. They are particularly well-suited for dimensionality reduction, feature
AI Algorithms
A deep belief network (DBN) is a type of artificial neural network that is composed of multiple layers of hidden units, with connections between the layers but not between units within each layer. DBNs are trained to learn a hierarchical representation of the input data, with each layer learning to