|
Vision-language-action Model
In robot learning, a vision-language-action model (VLA) is a class of Multimodal learning, multimodal foundation model, foundation models that integrates Computer vision, vision, Natural language, language and actions. Given an input image (or video) of the robot's surroundings and a text instruction, a VLA directly outputs low-level robot actions that can be executed to accomplish the requested task. VLAs are generally constructed by Fine-tuning (deep learning), fine-tuning a vision-language model (VLM, i.e. a large language model extended with Computer vision, vision capabilities) on a large-scale dataset that pairs visual observation and language instructions with robot trajectories. These models combine a vision-language encoder (typically a VLM or a vision transformer), which translates an image observation and a natural language description into a distribution within a latent space, with an action decoder that transforms this representation into continuous output actions, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
General Architecture Of A Vision-language-action Model
A general officer is an officer of high rank in the armies, and in some nations' air and space forces, marines or naval infantry. In some usages, the term "general officer" refers to a rank above colonel."general, adj. and n.". OED Online. March 2021. Oxford University Press. https://www.oed.com/view/Entry/77489?rskey=dCKrg4&result=1 (accessed May 11, 2021) The adjective ''general'' had been affixed to officer designations since the late medieval period to indicate relative superiority or an extended jurisdiction. French Revolutionary system Arab system Other variations Other nomenclatures for general officers include the titles and ranks: * Adjutant general * Commandant-general * Inspector general * General-in-chief * General of the Air Force (USAF only) * General of the Armies of the United States (of America), a title created for General John J. Pershing, and subsequently granted posthumously to George Washington and Ulysses S. Grant * (" general admiral") ( ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reason
Reason is the capacity of consciously applying logic by drawing valid conclusions from new or existing information, with the aim of seeking the truth. It is associated with such characteristically human activities as philosophy, religion, science, language, mathematics, and art, and is normally considered to be a distinguishing ability possessed by humans. Reason is sometimes referred to as rationality. Reasoning involves using more-or-less rational processes of thinking and cognition to extrapolate from one's existing knowledge to generate new knowledge, and involves the use of one's intellect. The field of studies the ways in which humans can use formal reasoning to produce logically valid arguments and true conclusions. Reasoning may be subdivided into forms of logical reasoning, such as deductive reasoning, inductive reasoning, and abductive reasoning. Aristotle drew a distinction between logical discursive reasoning (reason proper), and intuitive reasoning, in whi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Contrastive Language-Image Pre-training
Contrastive Language-Image Pre-training (CLIP) is a technique for training a pair of neural network models, one for image understanding and one for text understanding, using a contrastive objective. This method has enabled broad applications across multiple domains, including cross-modal retrieval, text-to-image generation, and aesthetic ranking. Algorithm The CLIP method trains a pair of models contrastively. One model takes in a piece of text as input and outputs a single vector representing its semantic content. The other model takes in an image and similarly outputs a single vector representing its visual content. The models are trained so that the vectors corresponding to semantically similar text-image pairs are close together in the shared vector space, while those corresponding to dissimilar pairs are far apart. To train a pair of CLIP models, one would start by preparing a large dataset of image-caption pairs. During training, the models are presented with batches ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stanford University
Leland Stanford Junior University, commonly referred to as Stanford University, is a Private university, private research university in Stanford, California, United States. It was founded in 1885 by railroad magnate Leland Stanford (the eighth List of governors of California, governor of and then-incumbent List of United States senators from California, United States senator representing California) and his wife, Jane Stanford, Jane, in memory of their only child, Leland Stanford Jr., Leland Jr. The university admitted its first students in 1891, opening as a Mixed-sex education, coeducational and non-denominational institution. It struggled financially after Leland died in 1893 and again after much of the campus was damaged by the 1906 San Francisco earthquake. Following World War II, university Provost (education), provost Frederick Terman inspired an entrepreneurship, entrepreneurial culture to build a self-sufficient local industry (later Silicon Valley). In 1951, Stanfor ... [...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] |
Latency (engineering)
Latency, from a general point of view, is a time delay between the Causality, cause and the effect of some physical change in the system being observed. Lag (video games), Lag, as it is known in Gaming culture, gaming circles, refers to the latency between the input to a simulation and the visual or auditory response, often occurring because of network delay in online games. The original meaning of “latency”, as used widely in psychology, medicine and most other disciplines, derives from “latent”, a word of Latin origin meaning “hidden”. Its different and relatively recent meaning (this topic) of “lateness” or “delay” appears to derive from its superficial similarity to the word “late”, from the old English “laet”. Latency is physically a consequence of the limited velocity at which any Event (relativity), physical interaction can propagate. The magnitude of this velocity is always less than or equal to the speed of light. Therefore, every physical s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hertz
The hertz (symbol: Hz) is the unit of frequency in the International System of Units (SI), often described as being equivalent to one event (or Cycle per second, cycle) per second. The hertz is an SI derived unit whose formal expression in terms of SI base units is 1/s or s−1, meaning that one hertz is one per second or the Inverse second, reciprocal of one second. It is used only in the case of periodic events. It is named after Heinrich Hertz, Heinrich Rudolf Hertz (1857–1894), the first person to provide conclusive proof of the existence of electromagnetic waves. For high frequencies, the unit is commonly expressed in metric prefix, multiples: kilohertz (kHz), megahertz (MHz), gigahertz (GHz), terahertz (THz). Some of the unit's most common uses are in the description of periodic waveforms and musical tones, particularly those used in radio- and audio-related applications. It is also used to describe the clock speeds at which computers and other electronics are driven. T ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Flow-based Generative Model
A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one. The direct modeling of likelihood provides many advantages. For example, the negative log-likelihood can be directly computed and minimized as the loss function. Additionally, novel samples can be generated by sampling from the initial distribution, and applying the flow transformation. In contrast, many alternative generative modeling methods such as variational autoencoder (VAE) and generative adversarial network do not explicitly represent the likelihood function. Method Let z_0 be a (possibly multivariate) random variable with distribution p_0(z_0). For i = 1, ..., K, let z_i = f_i(z_) be a sequence of random variables transformed from z_0. The functions f_1, ..., f_K should be ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Diffusion Model
In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable model, latent variable generative model, generative models. A diffusion model consists of two major components: the forward diffusion process, and the reverse sampling process. The goal of diffusion models is to learn a diffusion process for a given dataset, such that the process can generate new elements that are distributed similarly as the original dataset. A diffusion model models data as generated by a diffusion process, whereby a new datum performs a Wiener process, random walk with drift through the space of all possible data. A trained diffusion model can be sampled in many ways, with different efficiency and quality. There are various equivalent formalisms, including Markov chains, denoising diffusion probabilistic models, noise conditioned score networks, and stochastic differential equations. They are typically trained ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fine Motor Skill
Fine motor skill (or dexterity) is the coordination of small muscles in movement with the eyes, hands and fingers. The complex levels of manual dexterity that humans exhibit can be related to the nervous system. Fine motor skills aid in the growth of intelligence and develop continuously throughout the stages of human development. Types of motor skills Motor skills are movements and actions of the bone structures. Typically, they are categorised into two groups: gross motor skills and fine motor skills. Gross motor skills are involved in movement and coordination of the arms, legs, and other large body parts. They involve actions such as running, crawling and swimming. Fine motor skills are involved in smaller movements that occur in the wrists, hands, fingers, feet and toes. Specifically, single joint movements are fine motor movements and require fine motor skills. They involve smaller actions such as picking up objects between the thumb and finger, writing carefully, and bli ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
