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Prompt Engineering
Prompt engineering is a concept in artificial intelligence, particularly natural language processing (NLP). In prompt engineering, the description of the task is embedded in the input, e.g., as a question instead of it being implicitly given. Prompt engineering typically works by converting one or more tasks to a prompt-based dataset and training a language model with what has been called "prompt-based learning" or just "prompt learning". Prompt engineering may work from a large "frozen" pretrained language model and where only the representation of the prompt is learned (i.e., optimized), using methods such as "prefix-tuning" or "prompt tuning". The GPT-2 and GPT-3 language models were important steps in prompt engineering. In 2021, multitask prompt engineering using multiple NLP datasets showed good performance on new tasks. Prompts that include a chain of thought in few-shot learning examples show better indication of reasoning in language models. In zero-shot learning prependi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
DALL-E 2
DALL-E (stylized as DALL·E) and DALL-E 2 are deep learning models developed by OpenAI to generate digital images from natural language descriptions, called "prompts". DALL-E was revealed by OpenAI in a blog post in January 2021, and uses a version of GPT-3 modified to generate images. In April 2022, OpenAI announced DALL-E 2, a successor designed to generate more realistic images at higher resolutions that "can combine concepts, attributes, and styles". OpenAI has not released source code for either model. On 20 July 2022, DALL-E 2 entered into a beta phase with invitations sent to 1 million waitlisted individuals; users can generate a certain number of images for free every month and may purchase more. Access had previously been restricted to pre-selected users for a research preview due to concerns about ethics and safety. On 28 September 2022, DALL-E 2 was opened to anyone and the waitlist requirement was removed. In early November 2022, OpenAI released DALL-E 2 as an API, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ChatGPT
ChatGPT (Generative Pre-trained Transformer) is a chatbot launched by OpenAI in November 2022. It is built on top of OpenAI's GPT-3 family of large language models, and is fine-tuned (an approach to transfer learning) with both supervised and reinforcement learning techniques. ChatGPT was launched as a prototype on November 30, 2022, and quickly garnered attention for its detailed responses and articulate answers across many domains of knowledge. Its uneven factual accuracy was identified as a significant drawback. Following the release of ChatGPT, OpenAI was valued at $29 billion. Training ChatGPT was fine-tuned on top of GPT-3.5 using supervised learning as well as reinforcement learning. Both approaches used human trainers to improve the model's performance. In the case of supervised learning, the model was provided with conversations in which the trainers played both sides: the user and the AI assistant. In the reinforcement step, human trainers first ranked responses ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
NCC Group
NCC Group (LSE: NCC) is an information assurance firm headquartered in Manchester, United Kingdom. Its service areas cover software escrow and verification, cyber security consulting and managed services. NCC Group claims over 15,000 clients worldwide. The company is listed on the London Stock Exchange and is a constituent of the FTSE 250 Index. History NCC Group was formed in June 1999, when the National Computing Centre sold its commercial divisions to its existing management team supported by private equity firm ECI Ventures. This new company was named NCC Services Ltd and was renamed NCC Group Ltd in May 2000. In 2000, Rob Cotton was hired as finance director and subsequently took responsibility for the Group's escrow division. In 2003 he led a secondary management buyout and became chief executive of NCC Group Ltd. This valued the Group at £30 million and was supported by Barclays Private Equity. On 12 July 2004 NCC Group was admitted to trading on AIM, with the flota ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Code Injection
Code injection is the exploitation of a computer bug that is caused by processing invalid data. The injection is used by an attacker to introduce (or "inject") code into a vulnerable computer program and change the course of execution. The result of successful code injection can be disastrous, for example, by allowing computer viruses or computer worms to propagate. Code injection vulnerabilities occur when an application sends untrusted data to an interpreter. Injection flaws are most often found in SQL, LDAP, XPath, NoSQL queries, OS commands, XML parsers, SMTP headers, program arguments, etc. Injection flaws tend to be easier to discover when examining source code than via testing. Scanners and fuzzers can help find injection flaws. Injection can result in data loss or corruption, lack of accountability, or denial of access. Injection can sometimes lead to complete host takeover. Certain types of code injection are errors in interpretation, giving special meaning to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Security Exploit
An exploit (from the English verb ''to exploit'', meaning "to use something to one’s own advantage") is a piece of software, a chunk of data, or a sequence of commands that takes advantage of a bug or vulnerability to cause unintended or unanticipated behavior to occur on computer software, hardware, or something electronic (usually computerized). Such behavior frequently includes things like gaining control of a computer system, allowing privilege escalation, or a denial-of-service (DoS or related DDoS) attack. In lay terms, some exploit is akin to a 'hack'. Classification There are several methods of classifying exploits. The most common is by how the exploit communicates to the vulnerable software. A ''remote exploit'' works over a network and exploits the security vulnerability without any prior access to the vulnerable system. A ''local exploit'' requires prior access to the vulnerable system and usually increases the privileges of the person running the exploit past tho ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text-to-image
A text-to-image model is a machine learning model which takes as input a natural language description and produces an image matching that description. Such models began to be developed in the mid-2010s, as a result of advances in deep neural networks. In 2022, the output of state of the art text-to-image models, such as OpenAI's DALL-E 2, Google Brain's Imagen and StabilityAI's Stable Diffusion began to approach the quality of real photographs and human-drawn art. Text-to-image models generally combine a language model, which transforms the input text into a latent representation, and a generative image model, which produces an image conditioned on that representation. The most effective models have generally been trained on massive amounts of image and text data scraped from the web. History Before the rise of deep learning, attempts to build text-to-image models were limited to collages by arranging existing component images, such as from a database of clip art. The inverse tas ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Midjourney
Midjourney is an independent research lab that produces an artificial intelligence program under the same name that creates images from textual descriptions, similar to OpenAI's DALL-E and Stable Diffusion. It is speculated that the underlying technology is based on Stable Diffusion. The tool is currently in open beta, which it entered on July 12, 2022. The Midjourney team is led by David Holz, who co-founded Leap Motion. Holz told ''The Register'' in August 2022 that the company was already profitable. Users create artwork with Midjourney using Discord bot commands. History Midjourney was founded by David Holz, co-founder of Leap Motion. It first entered open beta on July 12, 2022. However, on March 14, 2022, the discord server launched with a request to post high-quality photographs to Twitter/Reddit for system's training. The company has been working on improving its algorithms, releasing new versions every few months. Version 2 of their algorithm was launched in April 2022 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stable Diffusion
Stable Diffusion is a deep learning, text-to-image model released in 2022. It is primarily used to generate detailed images conditioned on text descriptions, though it can also be applied to other tasks such as inpainting, outpainting, and generating image-to-image translations guided by a text prompt. Stable Diffusion is a latent diffusion model, a kind of deep generative neural network developed by the CompVis group at LMU Munich. The model has been released by a collaboration of Stability AI, CompVis LMU, and Runway with support from EleutherAI and LAION. In October 2022, Stability AI raised US$101 million in a round led by Lightspeed Venture Partners and Coatue Management. Stable Diffusion's code and model weights have been released publicly, and it can run on most consumer hardware equipped with a modest GPU with at least 8 GB VRAM. This marked a departure from previous proprietary text-to-image models such as DALL-E and Midjourney which were accessible only via cloud s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Processing
Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves. Challenges in natural language processing frequently involve speech recognition, natural-language understanding, and natural-language generation. History Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence, t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Zero-shot Learning
Zero-shot learning (ZSL) is a problem setup in machine learning where, at test time, a learner observes samples from classes which were not observed during training, and needs to predict the class that they belong to. Zero-shot methods generally work by associating observed and non-observed classes through some form of auxiliary information, which encodes observable distinguishing properties of objects. For example, given a set of images of animals to be classified, along with auxiliary textual descriptions of what animals look like, an artificial intelligence model which has been trained to recognize horses, but has never been given a zebra, can still recognize a zebra when it also knows that zebras look like striped horses. This problem is widely studied in computer vision, natural language processing, and machine perception. Background and history The first paper on zero-shot learning in natural language processing appeared in 2008 at the AAAI’08, but the name given to the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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