Hardware & compute

ENIAC, announced on 14 February 1946, is described by the University of Pennsylvania as the first general-purpose electronic computer: a 30-ton machine with 18,000 vacuum tubes, built to produce military firing tables.

A 1982 paper by John J. Hopfield arguing that useful computation can emerge as a collective property of many simple, equivalent units, and describing a model whose collective behaviour gives content-addressable memory, generalisation and error correction.

Wang Xingxing (born 1990) is the founder and chief executive of Unitree, the robotics company behind the AlienGo and Go1 quadruped robots and the H1 humanoid robot.

A robotics company spun out of MIT in 1992, known for legged and humanoid machines such as BigDog, Atlas, Spot and Handle, and now majority-owned by Hyundai Motor Group.

NVIDIA is the company that created the GPU in 1999 and, through the CUDA architecture and the chips behind AlexNet, became a central supplier of computing power for modern AI.

Amazon is the American technology company founded by Jeff Bezos in 1994. Through Amazon Web Services it became a major cloud provider, and it has built its own AI models, chips and assistants, including the Nova models and Trainium chips.

IBM's chess computer that in May 1997 became the first computer system to defeat a reigning world chess champion in a match under standard tournament time controls.

A small NASA rover that landed on Mars on July 4, 1997 with the Mars Pathfinder lander and became the first wheeled vehicle operated on another planet.

Mobileye makes camera-based vision chips and software for cars, from basic driver assistance up to systems for driverless vehicles; its EyeQ chips have shipped in hundreds of millions of vehicles.

A 2009 ICML paper by Rajat Raina, Anand Madhavan and Andrew Y. Ng that used graphics processors to train deep belief networks and sparse coding models many times faster than multicore CPUs.

The 2012 NeurIPS paper that introduced AlexNet, a large convolutional network trained on GPUs. It won the ILSVRC-2012 image classification competition by a wide margin and is widely seen as a turning point for deep learning in computer vision.

Atlas was a humanoid disaster-response robot built by Boston Dynamics for DARPA, unveiled on 11 July 2013 and handed to teams in the DARPA Robotics Challenge; its hydraulic line was retired in 2024.

Chinese supplier of advanced driver assistance and automated driving systems for passenger cars, founded in 2015, the largest domestic provider by installation volume, and listed in Hong Kong in 2024.

Google's first-generation Tensor Processing Unit is a custom chip built to speed up neural-network inference in its data centers. Deployed in 2015 and revealed in 2016, it showed that dedicated accelerators could beat CPUs and GPUs on cost-performance.

A Chinese robotics company established in Hangzhou in 2016 that designs and builds quadruped and humanoid robots, selling them at both low starting prices and industrial contract scale.

Aurora Innovation is a self-driving technology company founded in 2017 that went public in 2021 and began regular driverless commercial trucking between Dallas and Houston in April 2025.

Google TPU v2 is the second-generation Tensor Processing Unit announced in May 2017. It added floating-point support and the bfloat16 format, and scaled to 256-chip pods rated at 11.5 petaFLOPS.

NVIDIA's first data-center GPU built on its Volta architecture, announced in May 2017. It added Tensor Cores, dedicated matrix-multiply units; OpenAI later trained its GPT-3 models on V100s.

Spot is Boston Dynamics' four-legged commercial robot, sold since September 2019 for industrial use. It carries modular payloads such as cameras and LIDAR, walks over steps and slopes, and more than 1,500 units are in customers' hands.

An NVIDIA paper from 2019 presenting an intra-layer model parallelism method, implemented with a few communication operations in native PyTorch, that trained transformer models of up to 8.3 billion parameters and improved several benchmarks.

Scaling laws are empirical trends showing that a language model's test loss falls smoothly, as a power law, when parameters, data and training compute grow. They help plan large training runs and explain the race for compute.

A 2020 paper finding that language model loss falls predictably, as a power law, with model size, data and compute. It gave labs a quantitative reason to build much larger models and shaped the scale-up that followed.

NVIDIA's A100 is a data-center GPU, the first built on the Ampere architecture. Announced on 14 May 2020, it introduced third-generation Tensor Cores, the TF32 format and Multi-Instance GPU, and became a standard building block for training large language models.

The NVIDIA H100 is the first data-center GPU built on NVIDIA's Hopper architecture, announced in March 2022 with 80 billion transistors, HBM3 memory, FP8 Tensor Cores and a Transformer Engine aimed at large language models.

Gemini 1.0 is the first generation of Google DeepMind's multimodal model family, announced on 6 December 2023 in Ultra, Pro and Nano sizes; Google reported its Ultra version as the first model to beat human experts on MMLU.

Cerebras's third-generation wafer-scale AI chip, announced in March 2024: 4 trillion transistors on one 46,225-square-millimetre piece of silicon, built to keep very large models in a single memory space.

NVIDIA's GB200 NVL72 is a liquid-cooled rack that links 72 Blackwell GPUs and 36 Grace CPUs into a single NVLink domain aimed at trillion-parameter AI. Announced at GTC in March 2024, it is the building block of NVIDIA's Blackwell-generation DGX SuperPOD.

Boston Dynamics unveiled a fully electric Atlas in April 2024, saying it would be stronger, more dexterous and quieter than earlier generations and calling it the start of the robot's commercial journey, with Hyundai as first partner.

Figure 02 is the humanoid robot Figure introduced in August 2024, with redesigned hardware, 16-degree-of-freedom hands and triple the onboard compute of Figure 01. It loaded sheet-metal parts at BMW's Spartanburg plant before being retired in favour of Figure 03.

SK hynix's 12-layer HBM3E, announced in mass production on 26 September 2024, was the first 12-die high-bandwidth memory stack: 36 GB in a package no thicker than the eight-layer version, running at 9.6 Gbps.

DeepSeek-V3 is an open-weight mixture-of-experts language model that DeepSeek released in December 2024. Each token uses 37 billion of its 671 billion parameters, and DeepSeek describes its chat model as comparable to leading closed-source systems.

Huawei CloudMatrix384 is a Huawei Cloud service instance built on Atlas 900 A3 SuperPoDs, each linking up to 384 Ascend 910C chips so that they work as one computer.

TPU7x (Ironwood) is Google's seventh-generation TPU: 192 GB of high-bandwidth memory per chip, FP8 matrix units, 9,216 chips per pod, and a programming model that exposes two devices per chip.

Huawei's Ascend 910C is a data-center AI chip in the 910 series, built on the Da Vinci architecture. It reached the market in the first quarter of 2025 with 800 TFLOPS of FP16 compute and 128 GB of HBM.

A rack-scale NVIDIA system announced in March 2025 that links 72 Blackwell Ultra GPUs and 36 Grace CPUs into one unit, rated at 1.5 times the AI performance of GB200 NVL72.

SK hynix said on 19 March 2025 that it was the first to supply 12-layer HBM4 samples, a stack offering more than 2 TB of data per second and 36 GB of capacity, over 60% faster than HBM3E.

Huawei's intelligent driving system released in Shanghai on 22 April 2025, built on a cloud-plus-vehicle WEWA architecture and offered in four versions, the flagship carrying a dedicated highway L3 package.

AMD's data-center GPU for AI, introduced in June 2025 on the CDNA 4 architecture, with 288 GB of HBM3E memory and very high low-precision throughput aimed at generative AI inference, positioned against Nvidia's Blackwell generation.

Huawei's Ascend 950 is a two-chip AI series announced in September 2025, pairing a shared die with Huawei's own high bandwidth memory, up to 2 PFLOPS in low precision formats and 2 TB/s interconnect.

Figure 03 is Figure's third-generation humanoid robot, announced in October 2025. It is designed around the company's Helix AI for home tasks and mass manufacturing, with a new camera system, tactile hands and wireless charging.

NEO is a humanoid robot announced by 1X on 28 October 2025 and marketed as the first consumer-ready humanoid: a 66-pound, softly built machine with 22 degrees of freedom per hand, priced at US$20,000 for Early Access or US$499 a month by subscription.

AWS Trainium3 is AWS's first 3-nanometer AI chip, delivering 2.52 petaflops of FP8 compute per chip and scaling to 144 chips in a Trn3 UltraServer, available through Amazon EC2 from December 2025.[^1][^2]

NVIDIA Rubin is NVIDIA’s six-chip AI platform and the successor to Blackwell, announced at CES 2026. It targets lower-cost AI token generation, with partner products and cloud instances scheduled for 2026.

Quantization stores a language model's weights and activations at lower numerical precision, cutting the memory and bandwidth that inference requires. Methods such as LLM.int8() and GPTQ made very large models runnable on far smaller hardware.

IBM is an American technology company founded in 1911 as the Computing-Tabulating-Recording Company and renamed International Business Machines in 1924. Its researchers built Deep Blue, which beat Garry Kasparov in 1997, and the Watson question-answering system.

Bell Labs was the research arm of the Bell System, where the transistor, Unix and the C language were created. Yann LeCun's convolutional networks for handwritten digits were developed there, which made it an early home of neural-network research.

Frank Rosenblatt (1928–1971) was an American psychologist who developed the perceptron, an early learning machine that adjusted its weights from examples. His Mark I Perceptron is now held by the Smithsonian Institution.

IBM Research built Deep Blue, which beat world chess champion Garry Kasparov in 1997, and Watson, which won Jeopardy! in 2011. Nathaniel Rochester of IBM was also one of the four signatories of the 1955 Dartmouth proposal.

American computer scientist known for Google's core infrastructure — MapReduce, Bigtable and Spanner — and for leading work on Google Brain, TensorFlow and, from 2023, the role of Google's chief scientist.

PARC is a Silicon Valley research center founded by Xerox in 1970, known for Ethernet, laser printing and the Alto personal computer; it became an independent company in 2002 and joined SRI International in 2023.

Elon Musk is an entrepreneur who led SpaceX and Tesla, co-founded PayPal's predecessors and OpenAI, and founded xAI, the company behind the Grok models.

Apple is a US technology company founded in 1976 that makes the iPhone, iPad and Mac. It introduced Apple Intelligence in 2024, builds its own Apple Foundation Models, and in 2026 agreed to build its next models with Google.

Huawei is a Chinese information and communications technology company founded in Shenzhen in 1987. It designs its own Ascend AI chips and the software and large computing systems built around them.

The Newton MessagePad was Apple's first handheld computer built on Newton technology, shipping on 2 August 1993 with a pen-based interface, handwriting recognition and a modular communications design.

NASA's Mars Pathfinder lander touched down on July 4, 1997, deployed the small Sojourner rover, used an airbag landing system for the first time, and returned thousands of images of the Martian surface.

BigDog is a four-legged robot built by Boston Dynamics with DARPA funding, designed as a robotic pack mule that could carry loads over terrain too rough for conventional vehicles.

NVIDIA Research is the research arm of the chipmaker NVIDIA, founded in 2006 with more than 200 scientists. It leads work on AI, self-driving cars, high-performance computing and graphics, and it builds the company's open Nemotron language models.

Graphics processing units (GPUs) run many arithmetic operations in parallel, which suits neural-network training. Their use from 2010 onward made deep learning practical at much larger scales.

A consumer graphics card NVIDIA released in November 2010 on its Fermi architecture. Two of them, each with 3 GB of memory, later trained AlexNet, the network that won ILSVRC-2012 and which NVIDIA's timeline credits with sparking the era of modern AI.

Google Brain was a deep-learning research team started inside Google's X in 2011. Its cat-recognition experiment, TensorFlow, sequence-to-sequence models and the Transformer made it central to modern AI; it merged into Google DeepMind in 2023.

Curiosity is NASA's Mars rover, which landed in Gale Crater in August 2012 carrying a science payload far larger than earlier rovers, and which used a sky-crane descent to set down on its wheels.

A 2012 NIPS paper by Jeffrey Dean, Andrew Ng and colleagues that introduced DistBelief, a framework for training deep networks across clusters of thousands of machines, together with the Downpour SGD and Sandblaster optimisation procedures.

Preferred Networks, Inc. is a Tokyo technology company founded in 2014 that builds AI processors, runs its own supercomputer and develops Japanese large language models, with major Japanese manufacturers among its shareholders.

A Chinese chip designer founded in 2014 that builds x86-compatible processors and DCU accelerators, listed on the STAR Market in 2022 and positioning itself around a self-developed C86 plus GPGPU product line.

Boston Dynamics' 2016 generation of the Atlas humanoid, called Atlas HD or hydraulic Atlas: smaller, lighter and more agile than earlier versions, electrically powered and hydraulically actuated, and retired in 2024.

A Chinese AI chip company founded in 2016 and listed on the STAR Market in 2020. It designs cloud, edge and endpoint chips, and in 2025 it turned profitable as revenue rose sharply.

The Tesla P100, announced by NVIDIA in April 2016, was the first data-center GPU on the Pascal architecture, and the first to combine stacked HBM2 memory, half-precision math aimed at deep learning and the NVLink interconnect.

NVIDIA's DGX-1, unveiled in April 2016, packed eight Tesla P100 GPUs into a single chassis and was billed as the world's first deep learning supercomputer, turning accelerator count into one purchasable machine.

Pony.ai is an autonomous driving company founded in Fremont, California, in late 2016. It runs robotaxi, robotruck and personal-vehicle businesses on a common "virtual driver" system, and operates in both California and China.

A New Jersey cloud company that began as an ethereum miner and became a large-scale GPU computing provider for AI, backed by NVIDIA and listed on Nasdaq in 2025 alongside a major OpenAI deal.

WeRide is an autonomous driving company founded in Silicon Valley in 2017 by Tony Han, formerly chief scientist of Baidu's autonomous driving unit. Its WeRide One platform spans L2 to L4 autonomy, and its vehicles run in more than 60 cities.

A mixture of experts model contains many sub-networks but routes each token to only a few of them. This lets total model size grow while the compute spent on each token stays much smaller than the total.

Tensor Cores are specialised units inside NVIDIA GPUs that perform a small matrix multiply-and-add in one step, making the matrix arithmetic behind neural-network training and inference dramatically faster.

Apple's 2017 smartphone chip, announced with the iPhone X: a six-core CPU, an Apple-designed three-core GPU and a dual-core neural engine built for on-device machine learning such as Face ID.

Google's third-generation Tensor Processing Unit, introduced in 2018, with doubled HBM capacity, higher peak throughput, lower power draw and liquid cooling for denser pods.

Huawei's Ascend 910 is an AI training processor launched in 2019 alongside the MindSpore framework, rated at 256 teraflops FP16 and used to train the PanGu-α language models on clusters of thousands of chips.

Model parallelism splits one model's parameters and computation across multiple accelerators, so networks too large for a single device can still be trained. NVIDIA's 2019 Megatron-LM paper showed an intra-layer version built in native PyTorch.

Chinese chip designer founded in 2019 that builds general-purpose GPU (GPGPU) chips and intelligent computing solutions on its self-developed BILI series hardware and BIRENSUPA software, for AI training and inference from cloud to edge.

Google's TPU v4 is a machine-learning chip and supercomputer deployed since 2020, built into 4,096-chip pods with optically reconfigurable networking; PaLM and Gemini models were trained on it.

Chinese GPU company Moore Threads, founded in 2020 by former Nvidia China head Zhang Jianzhong, sells AI accelerator cards, servers and clusters built on its MUSA architecture. It listed on the STAR Market in 2025 and is growing fast while still loss-making.

NVIDIA's third-generation DGX system, unveiled on 14 May 2020: eight A100 GPUs, 320 GB of GPU memory, five petaflops of rated AI performance, and the ability to split into as many as 56 instances.

Cambricon's third-generation cloud AI chip, released in 2021: a 7 nm chiplet design with two compute dies, 256 TOPS at INT8, LPDDR5 memory and multi-chip interconnect, positioned for cost-effective inference.

Stretch is Boston Dynamics' first commercial robot designed specifically for warehouses, unveiled in March 2021 to unload trucks and, in later plans, to build orders.

Kunlunxin is the AI chip company spun out of Baidu in April 2021, continuing Baidu's Kunlun chip line. It designs processors for AI workloads in data centres and is one of China's largest domestic AI chip suppliers.

A four-legged consumer robot launched by Unitree in June 2021, the Go1 cost about 16,000 yuan and ran at up to 4.7 metres per second — an early attempt to sell a legged robot to ordinary buyers.

Triton is OpenAI's open-source, Python-like language and compiler for writing GPU kernels. It lets researchers with no CUDA experience produce efficient GPU code, often close to what an expert would write.

AMD's data-center GPU accelerator launched on 8 November 2021, built on the CDNA 2 architecture with 220 compute units, 128 GB of HBM2e memory, and strong double-precision throughput alongside low-precision AI formats.

NVIDIA's A800 is a data-center GPU that went into production in 2022 as a China-market alternative to the A100, with a reduced chip-to-chip transfer rate to meet US export-control thresholds.

A 2022 Nature paper by Degrave, Felici and colleagues showing that a deep reinforcement learning controller can learn on its own to command all of a tokamak's magnetic control coils, producing and holding a range of plasma shapes.

NVIDIA's fourth-generation DGX system, announced in March 2022, packs eight H100 GPUs linked by NVLink plus BlueField-3 networking, and is rated at 32 petaflops of FP8 AI performance for enterprise AI infrastructure.

PaLM is a 540-billion-parameter dense Transformer language model announced by Google Research in April 2022, trained with the Pathways system across 6,144 TPU v4 chips; it set strong few-shot results on many benchmarks.

Biren's general-purpose GPU, released in August 2022, packages two dies on a 7 nm process with 77 billion transistors; the company claimed PFLOPS-level single-chip compute, a first for a Chinese firm.

Optimus is Tesla's humanoid robot; its first prototype appeared at the company's second AI Day in September 2022, about 172 cm tall and 73 kg, with a 2.3 kWh battery pack and more than 200 degrees of freedom.

Cambricon's MLU 590 is a 7 nm cloud AI chip released in 2023 for both training and inference on models with hundreds of billions of parameters, and the centrepiece of the company's fifth-generation MLUarch line.

Huawei's Ascend 910B is a 2023 volume-production AI chip rated at 320 TFLOPS of FP16, with 32 GB of HBM2e memory, 1.6 TB/s of bandwidth and a 310 W envelope on a 7-nanometer domestic process.

NVIDIA's China-specific data-center GPU, built to stay inside US export controls. Cut down from the H100 in core count and performance, it was still the most advanced NVIDIA chip legally sold in China until April 2025.

The H800 is a China-market version of NVIDIA's H100 data-center GPU, adapted to fit the US export rules of October 2022 by cutting chip-to-chip transfer speed. It was later used to train DeepSeek-V3 and was covered by tighter US controls in October 2023.

xAI is an AI company founded by Elon Musk that builds the Grok models and chatbot. It was acquired by SpaceX in 2026 and has since been renamed SpaceXAI and then SpaceXSI.

Phoenix is Sanctuary AI's sixth-generation humanoid general-purpose robot, unveiled in May 2023 and controlled by the company's Carbon AI system.

Unitree Go2 is a quadruped robot released in July 2023 at a starting price of 9,997 yuan, which Unitree said brought pricing in this category below 10,000 yuan for the first time.

Apollo is Apptronik's humanoid robot, unveiled in August 2023: a 1.72 m electric machine with a 55-pound payload and swappable four-hour batteries, aimed first at warehouse and factory work.

TensorRT-LLM is NVIDIA's open-source library for speeding up and optimizing large language model inference on NVIDIA GPUs, publicly released on 19 October 2023 and usable free from GitHub or as part of NVIDIA NeMo.

NVIDIA's H200, announced in November 2023, is a data center GPU that was the first to use HBM3e memory, offering 141 GB at 4.8 TB/s — nearly double the A100's capacity — and roughly double the H100's inference speed on Llama 2 70B.

Azure Maia 100 is Microsoft's first custom AI chip, announced in November 2023 and built to train and run large language models inside its own Azure data centres rather than being sold.

Google TPU v5p is a 2023 TPU generation with 459 teraflops of peak BF16 and FP8 compute per chip, 95 GiB of HBM, and 8,960 chips per pod.

MLX is an open-source machine learning framework from Apple's machine learning research team, released in December 2023 and built primarily for Apple silicon. Its NumPy-like Python API and unified-memory design let the CPU and GPU work on the same data.

AMD's data-center GPU for generative AI, released in December 2023. Built on the CDNA 3 architecture with a chiplet design, it leads with 192 GB of HBM3 memory, which AMD contrasted with the 80 GB on Nvidia's H100.

Tesla's second-generation humanoid robot, shown in a December 2023 video walking, dancing and handling an egg, with 30% faster walking, 10 kg less weight and 11-DoF hands.[^1][^2]

Intel Gaudi 3 is an AI accelerator introduced in 2024, built from two 5 nm compute dies with 128 GB of HBM2e and 1,835 TFLOPS of BF16 and FP8 matrix throughput, plus integrated 200GbE networking on its OAM module.

The Kunlunxin P800 is a Chinese AI accelerator launched in 2024, the third generation of Kunlunxin's line, built on its own XPU-P architecture and used in large training clusters and in customer deployments.

NVIDIA's data-center GPU for the Blackwell generation, announced in March 2024 as the successor to Hopper, built from two joined dies and paired with NVLink and FP4 support for large-scale AI training and inference.

Meta's second-generation in-house AI chip, published on 10 April 2024, built on TSMC's 5-nanometer process and aimed at the ranking and recommendation models Meta runs in its own data centers.

A humanoid robot announced by Unitree Robotics on 13 May 2024 with a starting price of 99,000 yuan. The G1 weighs about 35 kg, folds for transport, and comes in a standard version and a configurable EDU version.

iFlytek's large language model released on 27 June 2024 and trained entirely on a domestic platform co-built with Huawei; iFlytek presented it as reaching GPT-4 level while acknowledging weaker coding and multimodal abilities.

A data-center GPU announced by AMD on 10 October 2024, built on third-generation CDNA with 256 GB of HBM3E memory at 6 TB/s and aimed at models with a trillion parameters.

Google TPU v6e, also called Trillium, is a Google Cloud AI accelerator whose published specifications cover per-chip BF16 and FP8 compute, high-bandwidth HBM, and pod-scale interconnects for large training jobs.

AWS Trainium2 is Amazon Web Services' second-generation machine-learning chip, sold through 16-chip EC2 Trn2 instances and 64-chip Trn2 UltraServers, and pitched by AWS as offering better price performance than comparable GPU instances.

Hygon's Shengsuan No. 3 is a GPGPU-architecture deep computing processor that reached the market in 2025, built on a 7 nm chiplet design with 1.8 TB/s of HBM bandwidth and a CUDA-like software stack.

Moore Threads' flagship training-and-inference GPU card, built on the PH100 chip and the Pinghu architecture, rated at 1,000 TFLOPS of dense AI compute with 80 GB of memory, and the company's main shipping product in 2025.

iFlytek Spark X1 is a Chinese deep-reasoning model released in January 2025 and trained entirely on domestic computing hardware, with later upgrades benchmarked against OpenAI's reasoning models.

AMD Instinct MI350X is a data-center GPU in AMD's MI350 series, built on the CDNA 4 architecture with up to 288 GB of HBM3E memory, up to 8 TB/s of bandwidth and a 1,000 W board power.

Step 3 is StepFun's open multimodal reasoning model, with 321 billion total parameters and 38 billion active per token. It was released in July 2025 and uses Apache 2.0.

Huawei's Ascend 970 is a planned AI chip announced in September 2025 as the last entry on the company's published roadmap, targeted for the fourth quarter of 2028 with roughly double the compute and wider interconnect and memory bandwidth than the Ascend 960.

The Ascend 960 is a Huawei AI chip on the company's three-year roadmap, slated for the fourth quarter of 2027 with twice the compute, memory and interconnect ports of the Ascend 950 and support for Huawei's HiF4 4-bit format.

Unitree H2 is a bionic humanoid robot announced on 20 October 2025, with a face-like head, 31 degrees of freedom, a weight of about 70 kg and a list price of 199,000 yuan.

The AMD Instinct MI400 is AMD's next-generation data-center GPU for AI, expected in 2026 with 432 GB of HBM4 memory, and designed to be deployed inside AMD's Helios rack-scale system.

Cambricon's flagship MLU 690, in mass production since early 2026, is a dual-die accelerator with 196 GB of HBM3 memory and more than 700 TFLOPS of FP16 compute, aimed at very large-scale training workloads.

Boston Dynamics and Hyundai Motor Group unveiled a production-ready Atlas humanoid in January 2026, with deployments planned at Hyundai and Google DeepMind and a fleet trained using reinforcement learning and foundation models.

Microsoft's Maia 200 is an inference accelerator introduced on 26 January 2026, built on TSMC's 3-nanometer process with 216 GB of HBM3e memory and more than 10 petaflops at FP4, aimed at serving models such as OpenAI's GPT-5.2.

Zhenwu 810E is an AI processor designed by Alibaba's chip team T-Head, listed in January 2026 with 96 GB of high-bandwidth memory, aimed at training, inference and autonomous driving, and already deployed in large clusters on Alibaba Cloud.

GLM-5 is Zhipu's open model released on 12 February 2026 under the MIT License, with 744 billion parameters and 40 billion active. It was built for agentic engineering.

Jensen Huang is a founder of NVIDIA and has served as its president, CEO and board member since the company was founded in 1993. NVIDIA credits the company's invention of the GPU and its work in accelerated computing to that era.

Google TPU v5e is a 2023 machine-learning accelerator chip with one TensorCore per chip, 197 TFLOP of bfloat16 peak compute, and 256-chip pods, positioned for both training and serving.

Liquid AI is an MIT CSAIL spin-out that calls itself an efficiency-first foundation model company, arguing that models should run on local devices; its LFM3-Omni-2B is an omni-modal model published in October 2026.

The GH200 Grace Hopper Superchip is an NVIDIA module that puts a 72-core Arm CPU and a Hopper GPU in one package joined by NVLink-C2C, pairing fast HBM with up to 480 GB of CPU memory for AI and technical computing.

SK hynix is a Korea-headquartered supplier of DRAM and NAND flash memory, and the company that released the first high-bandwidth memory (HBM) and says it has developed and shipped every HBM generation since.

Sim-to-real transfer is the practice of training robot policies in simulation and then adapting them to physical robots, using synthetic data to supplement costly real-world demonstrations.

AMD is a chip designer whose data center AI business centres on Instinct GPUs and APUs, expanded through the Xilinx and ZT Systems acquisitions and capped by a 6-gigawatt OpenAI supply deal.

A KV cache keeps the key and value vectors a model has already computed for earlier tokens, so each new token reuses them instead of recomputing. Its memory footprint is what makes high-throughput serving hard to scale.

Google, part of Alphabet, works on AI at several levels at once: it designs its own TPU chips, trains large language models such as PaLM and Gemini, and brought its research labs together as Google DeepMind in 2023.

Intel is a semiconductor company. Its 2017 purchase of Mobileye, later partly floated, and its decision to keep Falcon Shores as an internal test chip show how it enters and steps back from adjacent markets.

Lisa Su is an electrical engineer who became AMD's president and chief executive officer in 2014 and chair of its board in 2022, serving during the company's push into AI accelerators.

AWS Trainium is a chip built by Amazon Web Services for deep learning training, sold through EC2 Trn1 instances that AWS says cut training costs by up to 50% compared with comparable instances.

AWS Inferentia2 is Amazon Web Services' second-generation chip built for inference, offering 32 GB of high-bandwidth memory, up to 190 TFLOPS in FP16 and up to 12 chips per EC2 Inf2 instance.

A public research university in Manchester, England, which dates its founding to 1824 and took its present form in 2004; the Manchester Baby, the first electronic stored-program computer, was built there.

A private research university in Ithaca, New York, founded in 1865. It is also where Frank Rosenblatt studied and worked, and where the perceptron — an early learning machine and the first neural network — was developed.

IBM's first electronic computer, announced to shareholders in April 1952. Built as a general-purpose machine, it ran some 25 to 50 times faster than its predecessors and opened IBM's 700 series.

A Chinese consumer electronics and smart manufacturing company built around smartphones, smart hardware and its AIoT platform, listed in Hong Kong in 2018 and extending its engineering into quadruped and humanoid robots.

Microsoft's commercial edition of its Kinect depth-sensing camera, released on 1 February 2012 at a suggested price of $249 with a version 1.0 software development kit, so that companies and researchers could build motion- and voice-based applications for Windows computers.

XPENG is a Chinese maker of smart electric vehicles founded in 2014 and headquartered in Guangzhou, which has extended its in-house AI work to humanoid robots, new driving models and robotaxi plans.

NVIDIA's Tesla K80 is a dual-GPU data-center accelerator announced in November 2014, putting two GK210 chips, 24 GB of memory and up to 8.74 teraflops of single-precision performance on one 300 W board.

Talen Energy is an independent power producer created in 2015 from the spinoff of PPL's competitive generation business, later taken private by Riverstone, restructured through bankruptcy, and now a nuclear power supplier to Amazon.

Cerebras Systems is an American AI chip company founded in 2015 that builds wafer-scale processors — single chips made from a whole silicon wafer — and the computers around them, from the WSE and CS-1 to the WSE-3 and CS-3.

British chip company founded in 2016 in Bristol that designs Intelligence Processing Units for AI workloads; it raised large sums, reported heavy losses, and became a SoftBank Group subsidiary in 2024.

Kairos Power, founded in 2016, is an American company developing a fluoride salt-cooled high-temperature reactor using TRISO fuel. It is building the Hermes demonstration reactor in Tennessee and plans 500 MW of projects with Google by 2035.

Handle was a Boston Dynamics research robot that balanced on two wheels and used Atlas-derived arms to move objects; the company credits it with truck unloading and pallet building, and says the work led to its warehouse robot Stretch.

NVIDIA's DGX-2, announced in March 2018, packed 16 Tesla V100 GPUs and a new NVSwitch interconnect into one server that NVIDIA described as the first to reach two petaflops for deep learning.

T-Head Semiconductor is Alibaba's chip design unit, founded in 2018. It has released the Hanguang 800 AI inference chip, the Yitian 710 server CPU and the Zhenwu PPU AI processor, which Alibaba uses at scale for its Qwen models.

An AI processor from Cerebras Systems that keeps an entire silicon wafer as one chip, holding more than 1.2 trillion transistors and 400,000 cores; the first of a line that reached WSE-3 in 2024.

MetaX is a Shanghai-based GPU chip company founded in September 2020 that designs full-stack GPU chips and solutions; it is counted among China's four leading GPU startups and listed on the STAR Market in December 2025.

Xiaomi CyberDog is a bionic quadruped robot that Xiaomi announced in August 2021. It was sold as an engineering exploration edition priced at 9,999 yuan and limited to 1,000 units, and was aimed at developers who wanted to program and extend it.

Megatron-Turing NLG 530B is a 530-billion-parameter language model announced by NVIDIA and Microsoft on 11 October 2021, then the largest monolithic transformer language model, trained on NVIDIA's Selene supercomputer with Megatron-LM and DeepSpeed combined.

American energy company headquartered in Baltimore, one of the largest electricity producers in the United States, known for its 2024 agreement to restart Three Mile Island Unit 1.

Speculative decoding speeds up text generation from large autoregressive models: a smaller model proposes several tokens and the large model checks them in parallel, producing identical output faster.

MTIA v1 is Meta's first-generation in-house AI inference accelerator, built on TSMC's 7 nm process with 128 MB of on-chip memory and designed for deep learning recommendation models.

Spark V3.5 is a large language model that iFlytek released on 30 January 2024. It was the first Spark model trained entirely on the domestic FlyingStar One computing platform, and iFlytek compared it with GPT-4 Turbo.

Mistral NeMo is a 12-billion-parameter language model released by Mistral AI with NVIDIA in July 2024, notable for a 128K-token context window, a new multilingual tokenizer called Tekken, and an Apache 2.0 release.

Ministral 3B and Ministral 8B are two small Mistral AI language models released on 16 October 2024 for on-device and edge use, offering long context, low API prices and, for the 3B, performance Mistral claimed beat its earlier 7B model.

Falcon Shores is an Intel chip that the company said in January 2025 it would use only as an internal test chip, never bringing it to market, while pointing to Jaguar Shores as its route into rack-scale AI data-centre systems.

GLM-4.6 is an open-weights large language model released by Zhipu in late September 2025, with a 200K-token context window, about 357 billion parameters and an MIT licence, aimed at coding, reasoning and agent work.

An experimental DeepSeek model released on 29 September 2025 that introduced DeepSeek Sparse Attention to make long-context training and inference cheaper, shipped with open weights and an immediate API price cut.

iFlytek's Spark X1.5 is a deep reasoning model released in November 2025 that runs on a domestic computing platform built with Huawei, using a 293-billion-parameter mixture-of-experts design.

Three small dense models from Mistral AI — 3B, 8B and 14B — released in December 2025 under Apache 2.0, each in base, instruct and reasoning variants with image understanding.

A large language model released by iFlytek on 11 February 2026, trained entirely on domestic computing power and aimed at practical use in education, healthcare, automotive and agents.

Nemotron 3.5 Transcribe is Nvidia's free, open-weight speech transcription model, released on 28 October 2026. It handles recordings up to an hour long, transcribes up to 40 languages and can separate up to eight speakers.

Intel Gaudi 2 is a data-centre AI accelerator with 96 GB of HBM2e memory, 432 TFLOPS of BF16 compute and 24 tensor processor cores, built to run the matrix arithmetic behind large neural networks.

GroqChip is Groq's AI processor, built for fully deterministic execution with no run-to-run variation. It pairs a 14-nanometer die with 230 MB of on-die SRAM, up to 750 INT8 TOPS and RealScale chip-to-chip links, and ships both as a chip and on the PCIe GroqCard.

AWS Inferentia is a custom chip designed by AWS for running trained machine-learning models, sold to customers through EC2 Inf1 instances. It aims to make inference cheaper and faster than general-purpose instances.

Cerebras's second-generation wafer-scale chip, presented as the largest AI processor ever made: 2.6 trillion transistors, 850,000 cores and 40 GB of on-wafer memory on a single wafer built on a 7-nanometer process.

The Xicloud C600 is a MetaX data-center GPU built on the company's own GPGPU architecture, offering very large ECC-protected memory, MetaXLink scaling up to 128-GPU supernodes, a 1,000 W OAM 2.0 module, and air or liquid cooling.

SambaNova SN40L is an AI chip that SambaNova calls a Reconfigurable Dataflow Unit, pairing dataflow-style parallel execution with a three-tier memory system spanning on-chip SRAM, co-packaged HBM and DDR DRAM.

The NVIDIA L40S is a data-centre GPU on Nvidia's Ada Lovelace architecture, pairing 48 GB of ECC memory with AI and graphics throughput in a passive, dual-slot PCIe Gen4 card that omits NVLink and MIG.

The NVIDIA Tesla T4 is a 70-watt, single-slot GPU built on the Turing architecture and aimed at AI inference, pairing Tensor Cores with dedicated video transcoding engines in a card that slots into ordinary servers.

The AMD Instinct MI100 is a GPU accelerator built on AMD's first-generation CDNA architecture. It pairs 32 GB of HBM2 memory with peak throughput ratings for double-, single-, and half-precision math.

NVIDIA's DGX Spark is a desktop-sized AI computer built on the GB10 Grace Blackwell Superchip, pairing a 20-core Arm CPU with a Blackwell GPU and up to 128 GB of unified memory for running large models locally.

The NVIDIA A10 is a data-center GPU built on the Ampere architecture that combines graphics, video and AI inference in a single-slot PCIe card with 24 GB of memory, aimed at mainstream enterprise servers.

A Chinese artificial intelligence infrastructure company that builds the middle layer letting many models run on many kinds of chips, and also releases the open Megrez model family.

The NVIDIA Tesla P40 is a data-center GPU accelerator described in a September 2016 NVIDIA datasheet. Built on the Pascal architecture and aimed at deep learning inference, it pairs 24 GB of memory with 47 TOPS of INT8 throughput in a 250 W PCIe card.

A data-center GPU on NVIDIA's Ampere architecture, aimed at AI inference and mainstream enterprise workloads, with 24 GB of HBM2 memory, a 165 W power ceiling and the ability to split into as many as four MIG instances.

Blackhole is Tenstorrent's AI accelerator chip; Galaxy Blackhole is a server holding 32 of them, rated at 23 PFLOPS of block FP8, with Ethernet links wiring chips and clusters together.