core concepts

GPT

Generative Pre-trained Transformer, a family of autoregressive language models developed by OpenAI. GPT models are pre-trained on large corpora of text using unsupervised learning, then fine-tuned for specific tasks. The architecture uses decoder-only transformers.

In practice

GPT-4o powers ChatGPT and can process text, images, and audio.

Large Language Model
A neural network trained on massive text datasets to understand and generate human language. LLMs use billions of parameters to capture statistical patterns in language, enabling them to perform tasks like translation, summarization, and code generation.
Transformer
A neural network architecture introduced in the 2017 paper 'Attention Is All You Need' that processes sequential data using self-attention mechanisms instead of recurrence. Transformers enable massive parallelization during training, making them the foundation of modern LLMs and vision models.
Autoregressive Model
A model that generates output one element at a time, conditioning each prediction on all previously generated elements. Most language models are autoregressive, predicting the next token based on the sequence of tokens already produced.

In the index

Tools that mention GPT

Bloomberg GPTTrust 88
Duolingo MaxTrust 88
Intercom FinTrust 85
Merlin AITrust 85
Microsoft CopilotTrust 84
KhanmigoTrust 83
AgentGPTTrust 78

Matched on each tool’s own description and feature list, highest trust score first.

Models

Where it comes up

Briefings

GPT

Tools that mention GPT

Where it comes up

Further reading