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Context Modeling
A context model (or context modeling) defines how context data are structured and maintained (It plays a key role in supporting efficient context management). It aims to produce a formal or semi-formal description of the context information that is present in a Context awareness, context-aware system. In other words, the context is the surrounding element for the system, and a model provides the mathematical interface and a behavioral description of the surrounding environment. It is used to represent the reusable context information of the components (The top-level classes consist of Operating system, component container, Computer hardware, hardware requirement and Software requirement). A key role of context model is to simplify and introduce greater structure into the task of developing context-aware applications. Examples of context models The Unified modeling language, Unified Modeling Language as used in systems engineering defines a context model as the physical scope of th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Context Awareness
Context awareness refers, in information and communication technologies, to a capability to take into account the ''situation'' of ''entities'', which may be users or devices, but are not limited to those. ''Location'' is only the most obvious element of this ''situation''. Narrowly defined for mobile devices, context awareness does thus generalize location awareness. Whereas location may determine how certain processes around a contributing device operate, context may be applied more flexibly with mobile users, especially with users of smart phones. Context awareness originated as a term from ubiquitous computing or as so-called pervasive computing which sought to deal with linking changes in the environment with computer systems, which are otherwise static. The term has also been applied to business theory in relation to contextual application design and business process management issues. Qualities of context Various categorizations of context have been proposed in the past. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adaptive Vehicle Make
Adaptive Vehicle Make was a portfolio of programs overseen by DARPA, of the United States Department of Defense. AVM attempted to address revolutionary approaches to the design, verification, and manufacturing of complex defense systems and vehicles. The three primary programs were META, Instant Foundry Adaptive through Bits (iFAB), and Fast Adaptable Next-Generation Ground Vehicle (FANG GV) programs. Many components of the program leveraged crowdsourcing and were open source and the ultimate intent was to crowdsource a next generation combat vehicle. The program was managed by Nathan Wiedenman under DARPA's Tactical Technology Office. A Proposer's Day was held and several Broad Agency Announcements released on 7 October 2010. The AVM program was ended in February 2014 without building and testing a complete vehicle. [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
NVIDIA
Nvidia Corporation ( ) is an American multinational corporation and technology company headquartered in Santa Clara, California, and incorporated in Delaware. Founded in 1993 by Jensen Huang (president and CEO), Chris Malachowsky, and Curtis Priem, it designs and supplies graphics processing units (GPUs), application programming interfaces (APIs) for data science and high-performance computing, and system on a chip units (SoCs) for mobile computing and the automotive market. Nvidia is also a leading supplier of artificial intelligence (AI) hardware and software. Nvidia outsources the manufacturing of the hardware it designs. Nvidia's professional line of GPUs are used for edge-to-cloud computing and in supercomputers and workstations for applications in fields such as architecture, engineering and construction, media and entertainment, automotive, scientific research, and manufacturing design. Its GeForce line of GPUs are aimed at the consumer market and are used in ap ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Huawei
Huawei Technologies Co., Ltd. ("Huawei" sometimes stylized as "HUAWEI"; ; zh, c=华为, p= ) is a Chinese multinational corporationtechnology company in Longgang, Shenzhen, Longgang, Shenzhen, Guangdong. Its main product lines include telecommunications equipment, consumer electronics, electric vehicle self-driving car, autonomous driving systems, and rooftop solar power products. The company was founded in Shenzhen in 1987 by Ren Zhengfei, a veteran officer of the People's Liberation Army (PLA). Initially focused on manufacturing stored program control, phone switches, Huawei has expanded to more than 170 countries to include building telecommunications network infrastructures, providing equipment, operational and consulting services, and manufacturing communications devices for the consumer market. It overtook Ericsson in 2012 as the largest telecommunications equipment manufacturer in the world. Huawei surpassed Apple Inc., Apple and Samsung Electronics, Samsung, in 2018 a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google DeepMind
DeepMind Technologies Limited, trading as Google DeepMind or simply DeepMind, is a British–American artificial intelligence research laboratory which serves as a subsidiary of Alphabet Inc. Founded in the UK in 2010, it was acquired by Google in 2014 and merged with Google AI's Google Brain division to become Google DeepMind in April 2023. The company is headquartered in London, with research centres in the United States, Canada, France, Germany, and Switzerland. DeepMind introduced neural Turing machines (neural networks that can access external memory like a conventional Turing machine), resulting in a computer that loosely resembles short-term memory in the human brain. DeepMind has created neural network models to play video games and board games. It made headlines in 2016 after its AlphaGo program beat a human professional Go player Lee Sedol, a world champion, in a five-game match, which was the subject of a documentary film. A more general program, AlphaZero, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Numerical Weather Prediction
Numerical weather prediction (NWP) uses mathematical models of the atmosphere and oceans to weather forecasting, predict the weather based on current weather conditions. Though first attempted in the 1920s, it was not until the advent of computer simulation in the 1950s that numerical weather predictions produced realistic results. A number of global and regional forecast models are run in different countries worldwide, using current weather observations relayed from radiosondes, weather satellites and other observing systems as inputs. Mathematical models based on the same physical principles can be used to generate either short-term weather forecasts or longer-term climate predictions; the latter are widely applied for understanding and projecting climate change. The improvements made to regional models have allowed significant improvements in Tropical cyclone track forecasting, tropical cyclone track and air quality forecasts; however, atmospheric models perform poorly at han ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Transformer (machine Learning)
The transformer is a deep learning architecture based on the multi-head attention mechanism, in which text is converted to numerical representations called tokens, and each token is converted into a vector via lookup from a word embedding table. At each layer, each token is then contextualized within the scope of the context window with other (unmasked) tokens via a parallel multi-head attention mechanism, allowing the signal for key tokens to be amplified and less important tokens to be diminished. Transformers have the advantage of having no recurrent units, therefore requiring less training time than earlier recurrent neural architectures (RNNs) such as long short-term memory (LSTM). Later variations have been widely adopted for training large language models (LLM) on large (language) datasets. The modern version of the transformer was proposed in the 2017 paper "Attention Is All You Need" by researchers at Google. Transformers were first developed as an improvement ove ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Attention Mechanism
In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence. In natural language processing, importance is represented b"soft"weights assigned to each word in a sentence. More generally, attention encodes vectors called token embeddings across a fixed-width sequence that can range from tens to millions of tokens in size. Unlike "hard" weights, which are computed during the backwards training pass, "soft" weights exist only in the forward pass and therefore change with every step of the input. Earlier designs implemented the attention mechanism in a serial recurrent neural network (RNN) language translation system, but a more recent design, namely the transformer, removed the slower sequential RNN and relied more heavily on the faster parallel attention scheme. Inspired by ideas about attention in humans, the attention mechanism was developed to address the weaknesses of leveraging ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
BERT (language Model)
Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. It learns to represent text as a sequence of vectors using self-supervised learning. It uses the Transformer (machine learning model), encoder-only transformer architecture. BERT dramatically improved the State of the art, state-of-the-art for large language model, large language models. , BERT is a ubiquitous baseline in natural language processing (NLP) experiments. BERT is trained by masked token prediction and next sentence prediction. As a result of this training process, BERT learns contextual, Latent space, latent representations of tokens in their context, similar to ELMo and GPT-2. It found applications for many natural language processing tasks, such as coreference resolution and polysemy resolution. It is an evolutionary step over ELMo, and spawned the study of "BERTology", which attempts to interpret what is learned by BERT. BERT wa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
GPT-4
Generative Pre-trained Transformer 4 (GPT-4) is a multimodal large language model trained and created by OpenAI and the fourth in its series of GPT foundation models. It was launched on March 14, 2023, and made publicly available via the paid chatbot product ChatGPT Plus until being replaced in 2025, via OpenAI's API, and via the free chatbot Microsoft Copilot. GPT-4 is more capable than its predecessor GPT-3.5. GPT-4 Vision (GPT-4V) is a version of GPT-4 that can process images in addition to text. OpenAI has not revealed technical details and statistics about GPT-4, such as the precise size of the model. As a transformer-based model, GPT-4 uses a paradigm where pre-training using both public data and "data licensed from third-party providers" is used to predict the next token. After this step, the model was then fine-tuned with reinforcement learning feedback from humans and AI for human alignment and policy compliance. Background OpenAI introduced the fir ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
