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Find an AI concept.
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Diffusion Model
A generative model that learns to reverse a gradual noise process to create data such as images.
GPU
A highly parallel processor widely used to train and run modern machine-learning models.
Google AI Ecosystem
A guide to separating Google's research organizations, models, products and Cloud infrastructure when reading AI announcements.
HELM
Holistic Evaluation of Language Models, a framework for evaluating models across scenarios and metrics.
Inference
The process of running a trained model on new input to produce predictions, embeddings, or generated output.
KV Cache
A cache of attention keys and values used to avoid recomputing earlier context during autoregressive generation.
Latency and Throughput
Two core serving metrics describing response delay and the amount of work a system completes over time.
Mistral AI
An AI company providing models and inference services, with a guide to model-specific licenses, hosted versus self-operated deployment and task-level comparison.
Mixture of Experts (MoE)
A model architecture that routes each input to a subset of specialized parameter blocks called experts.
Physical AI
AI that connects perception and decision-making to physical actions, including robotics toolchains, sim-to-real gaps and evaluation of complete tasks.
Project Suncatcher
Google Research's exploration of AI computing in space, with solar power, accelerators and optical links examined as a research system.
Quantization
A technique that represents model weights or activations with lower numerical precision to reduce resource use.
Sovereign AI
Control over AI data, infrastructure, models and operational capabilities, examined separately from data location and supplier branding.
Tensor Processing Unit (TPU)
Google's specialized machine-learning accelerator, explained through matrix computation, software compatibility and workload-level evaluation.
Transformer
A neural network architecture that processes sequences primarily through attention mechanisms.
Vector Search
Search that retrieves items by similarity between numerical vector representations.