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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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Autonomous drivingAutonomous driving is the operation of a road vehicle by a computer system instead of a person. Its six automation levels, its two main technical traditions and its long line of research vehicles define how the field is discussed today.Imitation learningImitation learning trains an agent by supervised learning on expert demonstrations rather than by trial and error. Its simplest form is behaviour cloning, and its best-known weakness is distribution shift.Connectionist Temporal ClassificationConnectionist temporal classification (CTC) is a method for training recurrent neural networks to label unsegmented sequences, such as speech or handwriting, without frame-by-frame alignment. Introduced in 2006, it let CTC-trained LSTMs win the first international contests for recurrent networks.Xavier (Glorot) initializationXavier (Glorot) initialization is a weight-initialization scheme from Glorot and Bengio's 2010 paper that sets each layer's starting weight scale so signals stay stable across layers, giving substantially faster convergence in deep feedforward networks.Knowledge distillationKnowledge distillation trains a small model to reproduce the outputs of a larger model or an ensemble, so that much of the predictive performance is kept at lower compute and deployment cost.DeepfakeDeepfake is synthetic media: images, video or audio made or altered with AI. The term, a blend of "deep learning" and "fake", appeared in late 2017 and now names a whole class of face-swapping and manipulation techniques.Reinforcement learning from human feedback (RLHF)Reinforcement learning from human feedback trains a model toward what people prefer, using a reward model learned from human comparisons of its outputs. It became a standard step in building chat assistants.Content provenance (C2PA)Content provenance is a checkable record of where a piece of media came from and how it was edited, attached to the file itself. The C2PA, founded in 2021 by Adobe, Arm, BBC, Intel, Microsoft and Truepic, publishes the technical standard behind it.LoRA (low-rank adaptation)LoRA (low-rank adaptation) is a fine-tuning technique that freezes a pre-trained model's weights and trains small low-rank matrices instead, cutting the number of trainable parameters and the memory needed while keeping quality close to full fine-tuning.Speculative decodingSpeculative 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.Constitutional AIConstitutional AI is a training method introduced by Anthropic in December 2022, in which a model's behaviour is shaped by a written constitution of principles rather than by human labels of harmful outputs.Direct preference optimizationDirect preference optimization (DPO) is a method for fine-tuning language models on human preference data with a supervised-learning-style objective, removing the separate reward model and the reinforcement-learning loop of standard RLHF.Text watermarkingText watermarking embeds a hidden statistical signal in generated text so that a short span of tokens can later be identified as machine output, while the text still reads normally to people.Prompt injectionPrompt injection is an attack in which text inside a model's input overrides its original instructions, letting an adversary hijack a language-model application — including, as researchers showed in 2023, through content the application retrieves on its own.Llama Community LicenseThe Meta Llama 3 Community License is the custom agreement Meta attaches to its Llama 3 models: free to use and modify, but with use restrictions, attribution duties and a user-scale threshold that keep it from being open source in the usual sense.Test-time computeTest-time compute is the computation a model spends while answering a prompt, beyond what training already fixed into its weights. A 2024 study by Snell et al. showed how to spend it adaptively, and how it can stand in for a bigger model.Computer useComputer use is an Anthropic capability, released in public beta in October 2024, that lets an AI model operate a computer the way a person does — reading the screen, moving a cursor, clicking and typing — so it can drive ordinary software built for humans.Open Source AI Definition (OSAID)The Open Source AI Definition is a 1.0 standard, released by the Open Source Initiative in October 2024, that a model must meet to be called open source: reproducible design, disclosed training data, and freedom to use, modify and build on it.Vision-Language-Action model (VLA)A vision-language-action model (VLA) is a robot policy that takes in camera images and a language instruction and outputs actions directly, usually by adapting a pretrained vision-language model to control.Sim-to-real transferSim-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.