AI benchmark is benchmarking of AI systems, to assess the capabilities, efficiency, performance and to compare ANNs, machine learning (ML) models, architectures and algorithms when solving various AI problems, special benchmark tests are created and standardized, benchmarks. For example, Benchmarking Graph Neural Networks – benchmarking (benchmarking) of graph neural networks (GNS, GNN) – usually includes installing a specific benchmark, loading initial datasets, testing ANNs, adding a new dataset and repeating iterations (see also artificial neural network benchmarks).
AI Building and Training Kits – applications and software development kits (SDKs) that abstract platforms, frameworks, analytics libraries, and data analysis appliances, allowing software developers to incorporate AI into new or existing applications.
AI camera is a camera with artificial intelligence, digital cameras of a new generation – allow you to analyze images by recognizing faces, their expression, object contours, textures, gradients, lighting patterns, which is taken into account when processing images; some AI cameras are capable of taking pictures on their own, without human intervention, at moments that the camera finds most interesting, etc. (see also camera, software-defined camera).
AI chipset is a chipset for systems with AI, for example, AI chipset industry is an industry of chipsets for systems with AI, AI chipset market is a market for chipsets for systems with AI.
AI chipset market – chipset market for systems with artificial intelligence (AI), see also AI chipset.
AI chipset market is the market for chipsets for artificial intelligence (AI) systems.
AI cloud services – AI model building tools, APIs, and associated middleware that enable you to build/train, deploy, and consume machine learning models that run on a prebuilt infrastructure as cloud services. These services include automated machine learning, machine vision services, and language analysis services.
AI CPU is a central processing unit for AI tasks, synonymous with AI processor.
AI engineer – AI systems engineer.
AI engineering – transfer of AI technologies from the level of R&D, experiments and prototypes to the engineering and technical level, with the expanded implementation of AI methods and tools in IT systems to solve real production problems of a company, organization. One of the strategic technological trends (trends) that can radically affect the state of the economy, production, finance, the state of the environment and, in general, the quality of life of a person and humanity.
AI hardware(also AI-enabled hardware) – artificial intelligence infrastructure system hardware, AI infrastructure. Explanations in the Glossary are usually brief.
AI hardware is infrastructure hardware or artificial intelligence system, AI infrastructure.
AI industry – for example, commercial AI industry – commercial AI industry, commercial sector of the AI industry.
AI industry trends are promising directions for the development of the AI industry.
AI infrastructure(also AI-defined infrastructure, AI-enabled Infrastructure) – artificial intelligence infrastructure systems, for example, AI infrastructure research – research in the field of AI infrastructures (see also AI, AI hardware).
AI server (artificial intelligence server)
