Verizon
AI Connect

AI (Artificial intelligence) is a branch of computer science focused on developing machines that are capable of mimicking human intelligence and abilities, including learning, reasoning, problem-solving and perception. AI systems process extensive datasets that typically require human cognitive processes, like language comprehension, pattern recognition, decision-making and generating original content.

Agentic AI refers to AI systems that operate autonomously, making decisions and taking action to achieve goals with minimal human oversight. Unlike traditional AI, agentic AI is proactive and adapts to dynamic environments.

Agentic workflows involve AI agents autonomously managing tasks, decisions, and coordination using NLP and machine learning to streamline operations, enhance decision-making, and improve user experience with minimal human input.

AI-powered interfaces enhance user experiences through the application of AI technologies such as machine learning, natural language processing, and computer vision. These interfaces are designed to improve user experiences by learning from and responding to user behavior over time.

Algorithms in AI algorithms are step-by-step instructions that enable machines to learn from data, recognize patterns and make decisions that mimic human intelligence. They are the core of AI systems, requiring vast amounts of data for training; they can adapt and improve over time through a process of feedback and refinement.

Augmented Intelligence :is a concept that focuses on AI's role in enhancing human intelligence and capabilities, rather than replacing them. It emphasizes AI as a tool to improve human decision-making and performance.

Biases (in AI) are systematic errors in an AI system's output that result in unfair or skewed outcomes. This often arises from the AI being trained on insufficient, unrepresentative, or historically prejudiced data.

Big Data is a term to describe extremely large and complex datasets that traditional data processing software applications are unable to manage or analyze. It is the fuel for many modern AI systems.

Chatbots are software applications designed to conduct a conversation with a human user through text or voice commands, simulating human-like conversation.

Computer Vision is a field of AI that enables computers and systems to derive meaningful information from visual inputs like digital images and videos and take actions or make recommendations based on that information.

Conversational AI are AI systems, such as chatbots and virtual assistants, that are designed to understand, process, and respond to natural human language, enabling human-like interaction.

Data Mining isthe process of discovering patterns, trends, and valuable knowledge from large amounts of data using machine learning, statistics, and database systems.

Datasets in AI are structured or unstructured collections of data used to train machine learning models by teaching them to recognize patterns, make decisions, or predict future data points. Datasets are the fundamental input for AI models.

Deep learningis an AI method that teaches computers to process data by mimicking the human brain. These  models can recognize complex pictures, text, sounds and other data patterns to produce accurate insights and predictions.

Generative AI is atype of AI that can create new content, such as text, images, audio, video, or code, in response to a prompt, by learning patterns and structures from its training data.

GPUaaS (GPU as a Service) offers on-demand, cloud-based access to powerful Graphics Processing Unit (GPU) resources. This model eliminates the need for expensive hardware investment and maintenance, providing flexibility, scalability and faster deployment for GPU-intensive applications. Users can rent GPU power via subscription or per-use fees for AI, machine learning, scientific computing and 3D simulations.

Hallucinations in AI are false, misleading or nonsensical information generated by AI models. Often presented with compelling fluency, hallucinations can be hard to spot, leading to potential real-world consequences, such as the spread of misinformation or flawed decision-making.

Hyperscalers are large technology companies like AWS, Microsoft Azure, and Google Cloud that run massive, automated data centers. They offer vast, on-demand computing, storage and digital services globally, providing scalable IaaS, PaaS, and SaaS, enabling businesses to manage fluctuating data demands without owning or managing physical hardware.

Inferencing is applying a trained AI model to new data to make predictions or decisions. The model uses learned patterns from training to analyze new inputs, recognize features and generate insights.

Large language models (LLMs) are advanced AI systems trained on massive text datasets. They understand, generate and process human language for tasks like text generation, summarization, translation, and code generation.

Low-latency networks help minimize the delay between input and response by using edge computing, optimized hardware and efficient software to process data locally or closer to the source. Low latency is critical for real-time applications such as autonomous vehicles, instantaneous fraud detection and smart surveillance systems, helping to ensure actions can be taken immediately.

Machine learning(ML) is a subfield of artificial intelligence where systems learn from data to improve performance on specific tasks without being explicitly programmed. By analyzing large datasets, ML algorithms identify patterns, make predictions, and automate decision-making processes to generate insights and build intelligent models for a wide range of applications.

Natural Language Processing (NLP) is a branch of AI, computer science and linguistics that enables computers to understand, interpret and generate human language. Using techniques like sentiment analysis, translation, and chatbots, it processes text and speech for machine use in applications from customer service to healthcare.

Neocloud is a specialized cloud computing provider that focuses on offering high-performance infrastructure for AI and ML workloads. Unlike traditional, general-purpose "hyperscalers" like AWS, Microsoft Azure, and Google Cloud, neoclouds are designed from the ground up to provide raw, scalable computing power specifically using graphics processing units (GPUs). 

Neural network is an AI model inspired by the human brain to learn patterns in data for predictions. It uses interconnected layers of artificial neurons with adjustable "weights," trained with labeled data to minimize errors.

Prompt is the input, instruction, or query given by a user to a Generative AI system to request a specific output (e.g., a text summary, an image, or a piece of code).

Training Data is the vast dataset used to teach a machine learning model. The quality and composition of this data are crucial for the model's performance and fairness.

Transformer is a novel neural network architecture introduced in 2017 that relies on a self-attention mechanism to weigh the importance of different parts of the input data. It is the foundation for most modern LLMs and Generative AI.