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Concepts
Concepts
How AI works, in plain language: from the artificial neuron to the Transformer, pre-training and reasoning models.
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Multi-agent systemA multi-agent system is a computing system made of several interacting intelligent agents that coordinate to solve problems too hard for a single agent. Recent frameworks built on large language models let such agents talk to each other.World modelA world model is a machine learning system that learns an internal representation of an environment and predicts how it changes in response to actions, letting agents plan inside a learned simulator instead of by trial and error.Synthetic dataSynthetic data is training material written by a model rather than collected from people or the web. In the phi-1 experiments a small code model trained partly on model-generated "textbooks" reached competitive benchmark scores, suggesting data quality itself shapes capability.Embodied AIEmbodied AI is the study of agents that learn by interacting with an environment, using egocentric perception, rather than only from datasets curated from the internet. Simulators serve as virtual testbeds where such agents are trained and evaluated.Benchmark contaminationBenchmark contamination means the test items a model is evaluated on, or close variants of them, were present in its pretraining data, so scores partly measure memory of seen text rather than the ability the benchmark is meant to probe.Red teamingRed teaming is the practice of actively probing a model for harmful or unwanted behaviour before deployment. A 2022 method by Perez and colleagues automated it by using one language model to generate test cases for another.JailbreakA jailbreak is an adversarial prompt that gets a safety-trained model to produce behaviour its training was meant to prevent. A 2023 analysis by Wei et al. traced these failures to competing objectives and mismatched generalization.Semantic WebThe Semantic Web is a W3C standards effort that uses RDF and OWL to describe data so different applications, enterprises and communities can share and reuse information, moving from research toward practical tools.Visual odometryVisual odometry lets a rover measure how far it actually moved by tracking features in camera images taken before and after a short drive, instead of trusting wheel turns. NASA's Mars Exploration Rovers were the first to demonstrate it.