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Retrieval-augmented Generation
Retrieval-augmented generation (RAG) is a technique that enables large language model, large language models (LLMs) to retrieve and incorporate new information. With RAG, LLMs do not respond to user queries until they refer to a specified set of documents. These documents supplement information from the LLM's pre-existing training data. This allows LLMs to use domain-specific and/or updated information that is not available in the training data. For example, this helps LLM-based chatbot, chatbots access internal company data or generate responses based on authoritative sources. RAG improves large language models (LLMs) by incorporating information retrieval before generating responses. Unlike traditional LLMs that rely on static training data, RAG pulls relevant text from databases, uploaded documents, or web sources. According to ''Ars Technica'', "RAG is a way of improving LLM performance, in essence by blending the LLM process with a web search or other document look-up process ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Large Language Model
A large language model (LLM) is a language model trained with self-supervised machine learning on a vast amount of text, designed for natural language processing tasks, especially language generation. The largest and most capable LLMs are generative pretrained transformers (GPTs), which are largely used in generative chatbots such as ChatGPT or Gemini. LLMs can be fine-tuned for specific tasks or guided by prompt engineering. These models acquire predictive power regarding syntax, semantics, and ontologies inherent in human language corpora, but they also inherit inaccuracies and biases present in the data they are trained in. History Before the emergence of transformer-based models in 2017, some language models were considered large relative to the computational and data constraints of their time. In the early 1990s, IBM's statistical models pioneered word alignment techniques for machine translation, laying the groundwork for corpus-based language modeling. A sm ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prompt Engineering
Prompt engineering is the process of structuring or crafting an instruction in order to produce the best possible output from a generative artificial intelligence (AI) model. A ''prompt'' is natural language text describing the task that an AI should perform. A prompt for a text-to-text Large language model, language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, providing relevant context, or describing a character for the AI to mimic. When communicating with a text-to-image or a text-to-audio model, a typical prompt is a description of a desired output such as "a high-quality photo of an astronaut riding a horse" or "Lo-fi slow BPM electro chill with organic samples". Prompting a text-to-image model may involve adding, removing, or emphasizing words to achieve a desired subject, style, layout, lighting, and aestheti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Knowledge Graph
In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a Graph (discrete mathematics), graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of Named entity, entities objects, events, situations or abstract concepts while also encoding the free-form semantics or relationships underlying these entities. Since the development of the Semantic Web, knowledge graphs have often been associated with linked data, linked open data projects, focusing on the connections between concepts and entities. They are also historically associated with and used by search engines such as Google Knowledge Graph, Google, Bing (search engine), Bing, Yext and Yahoo; Knowledge Engine (Wikimedia Foundation), knowledge-engines and question-answering services such as WolframAlpha, Apple's Siri, and Amazon Amazon Alexa, Alexa; and social networks such as LinkedIn and Facebook. Recent deve ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Language Model In Deepmind's 2021 Retro For RAG
Language is a structured system of communication that consists of grammar and vocabulary. It is the primary means by which humans convey meaning, both in spoken and signed forms, and may also be conveyed through writing. Human language is characterized by its cultural and historical diversity, with significant variations observed between cultures and across time. Human languages possess the properties of productivity and displacement, which enable the creation of an infinite number of sentences, and the ability to refer to objects, events, and ideas that are not immediately present in the discourse. The use of human language relies on social convention and is acquired through learning. Estimates of the number of human languages in the world vary between and . Precise estimates depend on an arbitrary distinction (dichotomy) established between languages and dialects. Natural languages are spoken, signed, or both; however, any language can be encoded into secondary media usin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
KL Divergence
KL, kL, kl, or kl. may refer to: Businesses and organizations * KLM, a Dutch airline (IATA airline designator KL) * Koninklijke Landmacht, the Royal Netherlands Army * Kvenna Listin ("Women's List"), a political party in Iceland * KL FM, a Malay language radio station Places * Kaiserslautern, Germany (license plate code KL) * Kerala, India (ISO 3166-2:IN sub-code KL) * Kirkland Lake, Ontario, Canada * Kowloon, Hong Kong * Kuala Lumpur, Malaysia Science, technology, and mathematics * KL engine, version of the Mazda K engine * Klepton (kl.), a type of species in zoology * Kiloliter (kL), a unit of volume * Kullback–Leibler divergence in mathematics * KL (gene), a gene which encodes the klotho enzyme in humans Other uses * Jeep Cherokee (KL) * Kalaallisut language (ISO 639 alpha-2 language code "kl") * Kl (digraph), used in the Zulu language to write /kʟ̥ʼ/ or /kxʼ/ * Konzentrationslager, or concentration camp, abbreviated KZ or KL * '' KL: A History of the Nazi Concentr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Perplexity
In information theory, perplexity is a measure of uncertainty in the value of a sample from a discrete probability distribution. The larger the perplexity, the less likely it is that an observer can guess the value which will be drawn from the distribution. Perplexity was originally introduced in 1977 in the context of speech recognition by Frederick Jelinek, Robert Leroy Mercer, Lalit R. Bahl, and James K. Baker. Perplexity of a probability distribution The perplexity ''PP'' of a discrete probability distribution ''p'' is a concept widely used in information theory, machine learning, and statistical modeling. It is defined as :\mathit(p) = \prod_x p(x)^ = b^ where ''x'' ranges over the events, where is defined to be , and where the value of does not affect the result; can be chosen to be 2, 10, , or any other positive value other than . In some contexts, this measure is also referred to as the '' (order-1 true) diversity''. The logarithm is the entropy of the d ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
One-hot
In digital circuits and machine learning, a one-hot is a group of bits among which the legal combinations of values are only those with a single high (1) bit and all the others low (0). A similar implementation in which all bits are '1' except one '0' is sometimes called one-cold. In statistics, dummy variables represent a similar technique for representing categorical data. Applications Digital circuitry One-hot encoding is often used for indicating the state of a state machine. When using binary, a decoder is needed to determine the state. A one-hot state machine, however, does not need a decoder as the state machine is in the ''n''th state if, and only if, the ''n''th bit is high. A ring counter with 15 sequentially ordered states is an example of a state machine. A 'one-hot' implementation would have 15 flip-flops chained in series with the Q output of each flip-flop connected to the D input of the next and the D input of the first flip-flop connected to the Q output of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
K-nearest Neighbors Algorithm
In statistics, the ''k''-nearest neighbors algorithm (''k''-NN) is a Non-parametric statistics, non-parametric supervised learning method. It was first developed by Evelyn Fix and Joseph Lawson Hodges Jr., Joseph Hodges in 1951, and later expanded by Thomas M. Cover, Thomas Cover. Most often, it is used for statistical classification, classification, as a ''k''-NN classifier, the output of which is a class membership. An object is classified by a plurality vote of its neighbors, with the object being assigned to the class most common among its ''k'' nearest neighbors (''k'' is a positive integer, typically small). If ''k'' = 1, then the object is simply assigned to the class of that single nearest neighbor. The ''k''-NN algorithm can also be generalized for regression analysis, regression. In ''-NN regression'', also known as ''nearest neighbor smoothing'', the output is the property value for the object. This value is the average of the values of ''k'' nearest neighbo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Approximate Nearest Neighbor Search
Nearest neighbor search (NNS), as a form of proximity search, is the optimization problem of finding the point in a given set that is closest (or most similar) to a given point. Closeness is typically expressed in terms of a dissimilarity function: the less similar the objects, the larger the function values. Formally, the nearest-neighbor (NN) search problem is defined as follows: given a set ''S'' of points in a space ''M'' and a query point ''q'' ∈ ''M'', find the closest point in ''S'' to ''q''. Donald Knuth in vol. 3 of ''The Art of Computer Programming'' (1973) called it the post-office problem, referring to an application of assigning to a residence the nearest post office. A direct generalization of this problem is a ''k''-NN search, where we need to find the ''k'' closest points. Most commonly ''M'' is a metric space and dissimilarity is expressed as a distance metric, which is symmetric and satisfies the triangle inequality. Even more common, ''M'' is taken ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dot Product
In mathematics, the dot product or scalar productThe term ''scalar product'' means literally "product with a Scalar (mathematics), scalar as a result". It is also used for other symmetric bilinear forms, for example in a pseudo-Euclidean space. Not to be confused with scalar multiplication. is an algebraic operation that takes two equal-length sequences of numbers (usually coordinate vectors), and returns a single number. In Euclidean geometry, the dot product of the Cartesian coordinates of two Euclidean vector, vectors is widely used. It is often called the inner product (or rarely the projection product) of Euclidean space, even though it is not the only inner product that can be defined on Euclidean space (see ''Inner product space'' for more). It should not be confused with the cross product. Algebraically, the dot product is the sum of the Product (mathematics), products of the corresponding entries of the two sequences of numbers. Geometrically, it is the product of the Euc ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dense Matrix
In numerical analysis and scientific computing, a sparse matrix or sparse array is a matrix in which most of the elements are zero. There is no strict definition regarding the proportion of zero-value elements for a matrix to qualify as sparse but a common criterion is that the number of non-zero elements is roughly equal to the number of rows or columns. By contrast, if most of the elements are non-zero, the matrix is considered dense. The number of zero-valued elements divided by the total number of elements (e.g., ''m'' × ''n'' for an ''m'' × ''n'' matrix) is sometimes referred to as the sparsity of the matrix. Conceptually, sparsity corresponds to systems with few pairwise interactions. For example, consider a line of balls connected by springs from one to the next: this is a sparse system, as only adjacent balls are coupled. By contrast, if the same line of balls were to have springs connecting each ball to all other balls, the system would correspond to a dense matrix. T ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
