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Knowledge Cutoff
In machine learning, a knowledge cutoff (or data cutoff) is the date that marks the end of the data used for a model's training, especially for a large language model (LLM). Any information about events after this date is absent from the model's internal knowledge base. A model's knowledge is static after this date. It cannot access information about later events without a system for real-time data access, such as Retrieval-augmented generation, RAG. This concept started with the release of GPT-3 in 2020. Major labs like Google, OpenAI and Anthropic began publicly disclosing cutoff dates for transparency. While useful for training and tuning LLMs, knowledge cutoffs introduce new limitations like hallucinations, information gaps and temporal bias. To mitigate these issues, methods like RAG and continual learning are used to supplement static knowledge with dynamic or updated information. Overview Training large language models on static datasets is standard practice. This is necessa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge Cutoffs Of Popular LLMs
Knowledge is an Declarative knowledge, awareness of facts, a Knowledge by acquaintance, familiarity with individuals and situations, or a Procedural knowledge, practical skill. Knowledge of facts, also called propositional knowledge, is often characterized as Truth, true belief that is distinct from opinion or guesswork by virtue of Justification (epistemology), justification. While there is wide agreement among philosophers that propositional knowledge is a form of true belief, many controversies focus on justification. This includes questions like how to understand justification, whether it is needed at all, and whether something else besides it is needed. These controversies intensified in the latter half of the 20th century due to a series of thought experiments called ''Gettier cases'' that provoked alternative definitions. Knowledge can be produced in many ways. The main source of empirical knowledge is perception, which involves the usage of the senses to learn about ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
