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16 technologies shown

• LLM concept Large language model: a Transformer trained on text at a scale that yields general capability.
• GPT model Family of decoder-only Transformer language models trained with a generative objective.
• Llama model Open-weight language model family from Meta, released for local and self-hosted use.
• BERT model Encoder-only Transformer pre-trained with masked language modelling.
• Qwen model Alibaba's open-weight model family, strong on multilingual and coding tasks.
• Mistral model European open-weight model family known for efficiency at small parameter counts.
• Claude model Anthropic's hosted model family, positioned around long-context work and safety.
• DeepSeek model Open-weight model family notable for efficient training at frontier scale.
• Gemma model Google's open-weight model family, released in small sizes.
• Hallucination concept Fluent output that is not supported by the model's input or by fact.
• Gemini model Google's hosted multimodal model family, integrated with its cloud platform.
• Logits concept The raw, unnormalised scores a model produces before softmax.
• Token concept The unit of text a language model reads and writes.
• Phi model Microsoft's small models trained mainly on curated textbook-quality data.
• Context Window concept Maximum number of tokens a model can attend to in one request.
• Command R model Model family oriented toward retrieval and tool use.