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AI Entry Type

AI Hardware Entries

This page groups the hardware entries from the Lexicon Labs AI encyclopedia into one indexable landing page.

Back to AI Topic Map

At A Glance

Entries

330

Lexicon entries typed as hardware.

Top Categories

5

Topic areas where this entry type appears most often.

Overview

The current lexicon contains 330 entries of type hardware. This makes the page useful as a quick orientation layer for readers who want one kind of AI object rather than one subject area.

The category breakdown below shows where this entry type appears most often across the broader AI taxonomy.

NVIDIA Hardware and Ecosystem

150 hardware entries in this category.

Other AI Hardware and Chips

140 hardware entries in this category.

AI Hardware, Systems and Infrastructure

26 hardware entries in this category.

Machine Learning Fundamentals

5 hardware entries in this category.

Industry, Applications and Infrastructure

4 hardware entries in this category.

Sample Entries

Von Neumann Architecture

Von Neumann Architecture is a computer design where program instructions and data are stored together in a single, shared memory unit. This unified storage allows the CPU to access both efficiently, forming the basis of.

Deep Architectures

Deep Architectures are multi-layered computational models, typically deep neural networks, designed with many processing layers to automatically learn intricate patterns and representations from vast amounts of data.

Network Architectures

Network architectures define the specific layer arrangements, connections, and operations within an artificial neural network. They dictate how data flows and transforms to learn patterns, forming the blueprint for AI models.

Neural Architecture Search (NAS)

Neural Architecture Search (NAS) is an automated technique that designs optimal neural network architectures. It uses algorithms to explore and evaluate various network configurations, finding the most efficient models for specific tasks.

Efficient Neural Architecture Search (ENAS)

ENAS is a neural architecture search method that efficiently discovers optimal deep learning model structures. It uses a controller to learn and share parameters across child models, significantly reducing computational cost compared to traditional NAS.

Transformer Architecture

Transformer Architecture is a neural network design, introduced in 2017, that uses self-attention mechanisms and positional encoding to process sequences in parallel. It revolutionized natural language processing by efficiently handling long-range dependencies.

GPU Computing

GPU Computing harnesses Graphics Processing Units (GPUs) to perform numerous calculations in parallel. This method dramatically accelerates complex computational tasks, especially for AI model training, scientific simulations, and large-scale data processing.

NVIDIA H100

The NVIDIA H100 is a powerful graphics processing unit (GPU) designed for accelerating artificial intelligence workloads, high-performance computing, and data center operations. It features Hopper architecture for significant performance gains over previous generations.

NVIDIA A100

The NVIDIA A100 is a powerful data center GPU, based on the Ampere architecture, designed for AI training, inference, and high-performance computing. It features Tensor Cores for accelerated matrix operations, crucial for deep learning workloads.

NVIDIA GH200

The NVIDIA GH200 Grace Hopper Superchip combines a Grace CPU and a Hopper H100 GPU with high-bandwidth memory. It's designed for demanding AI and high-performance computing, accelerating large model training and inference.

Kunlun Chip

The Kunlun Chip is Baidu's proprietary AI accelerator hardware, engineered for high-performance deep learning computation in cloud and edge environments. It powers various AI services within Baidu's ecosystem.

Tesla Architecture

Tesla Architecture was NVIDIA's first unified shader model GPU architecture, introduced in 2006. It significantly advanced parallel processing capabilities, laying groundwork for modern GPU computing beyond graphics.

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