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Seed AI
Recursive self-improvement (RSI) is a process in which an early or weak artificial general intelligence (AGI) system enhances its own capabilities and intelligence without human intervention, leading to a superintelligence or intelligence explosion. The development of recursive self-improvement raises significant ethical and safety concerns, as such systems may evolve in unforeseen ways and could potentially surpass human control or understanding. Seed improver The concept of a "seed improver" architecture is a foundational framework that equips an AGI system with the initial capabilities required for recursive self-improvement. This might come in many forms or variations. The term "Seed AI" was coined by Eliezer Yudkowsky. Hypothetical example The concept begins with a hypothetical "seed improver", an initial code-base developed by human engineers that equips an advanced future large language model (LLM) built with strong or expert-level capabilities to program software ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial General Intelligence
Artificial general intelligence (AGI)—sometimes called human‑level intelligence AI—is a type of artificial intelligence that would match or surpass human capabilities across virtually all cognitive tasks. Some researchers argue that state‑of‑the‑art large language models already exhibit early signs of AGI‑level capability, while others maintain that genuine AGI has not yet been achieved. AGI is conceptually distinct from artificial superintelligence (ASI), which would outperform the best human abilities across every domain by a wide margin. AGI is considered one of the definitions of Chinese room#Strong AI vs. AI research, strong AI. Unlike artificial narrow intelligence (ANI), whose competence is confined to well‑defined tasks, an AGI system can generalise knowledge, transfer skills between domains, and solve novel problems without task‑specific reprogramming. The concept does not, in principle, require the system to be an autonomous agent; a static model— ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Turing Completeness
In computability theory, a system of data-manipulation rules (such as a model of computation, a computer's instruction set, a programming language, or a cellular automaton) is said to be Turing-complete or computationally universal if it can be used to simulate any Turing machine (devised by English mathematician and computer scientist Alan Turing). This means that this system is able to recognize or decode other data-manipulation rule sets. Turing completeness is used as a way to express the power of such a data-manipulation rule set. Virtually all programming languages today are Turing-complete. A related concept is that of Turing equivalence two computers P and Q are called equivalent if P can simulate Q and Q can simulate P. The Church–Turing thesis conjectures that any function whose values can be computed by an algorithm can be computed by a Turing machine, and therefore that if any real-world computer can simulate a Turing machine, it is Turing equivalent to a Turing m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Claude (language Model)
Claude is a family of large language models developed by Anthropic. The first model was released in March 2023. The Claude 3 family, released in March 2024, consists of three models: Haiku, optimized for speed; Sonnet, which balances capability and performance; and Opus, designed for complex reasoning tasks. These models can process both text and images, with Claude 3 Opus demonstrating enhanced capabilities in areas like mathematics, programming, and logical reasoning Logical reasoning is a mind, mental Action (philosophy), activity that aims to arrive at a Logical consequence, conclusion in a Rigour, rigorous way. It happens in the form of inferences or arguments by starting from a set of premises and reason ... compared to previous versions. Claude 4, which includes Opus and Sonnet, was released in May 2025. Training Claude models are generative pre-trained transformers. They have been pre-trained to predict the next word in large amounts of text. Then, they have ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Selection
Natural selection is the differential survival and reproduction of individuals due to differences in phenotype. It is a key mechanism of evolution, the change in the Heredity, heritable traits characteristic of a population over generations. Charles Darwin popularised the term "natural selection", contrasting it with selective breeding, artificial selection, which is intentional, whereas natural selection is not. Genetic diversity, Variation of traits, both Genotype, genotypic and phenotypic, exists within all populations of organisms. However, some traits are more likely to facilitate survival and reproductive success. Thus, these traits are passed the next generation. These traits can also become more Allele frequency, common within a population if the environment that favours these traits remains fixed. If new traits become more favoured due to changes in a specific Ecological niche, niche, microevolution occurs. If new traits become more favoured due to changes in the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Self-preservation
Self-preservation is a behavior or set of behaviors that ensures the survival of an organism. It is thought to be universal among all living organisms. Self-preservation is essentially the process of an organism preventing itself from being harmed or killed and is considered a basic instinct in most organisms. Most call it a "survival instinct". Self-preservation is thought to be tied to an organism's reproductive fitness and can be more or less present according to perceived reproduction potential. If perceived reproductive potential is low enough, self-destructive behavior (i.e., the opposite) is not uncommon in social species. Self-preservation is also thought by some to be the basis of rational and logical thought and behavior. The opposite of self-preservation is self-destructive behavior. Overview An organism's fitness is measured by its ability to pass on its genes. The most straightforward way to accomplish this is to survive to a reproductive age, mate if necessary, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Evolutionary Computation
Evolutionary computation from computer science is a family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms. In technical terms, they are a family of population-based trial and error problem solvers with a metaheuristic or stochastic optimization character. In evolutionary computation, an initial set of candidate solutions is generated and iteratively updated. Each new generation is produced by stochastically removing less desired solutions, and introducing small random changes as well as, depending on the method, mixing parental information. In biological terminology, a population of solutions is subjected to natural selection (or artificial selection), mutation and possibly recombination. As a result, the population will gradually evolve to increase in fitness, in this case the chosen fitness function of the algorithm. Evolutionary computation techni ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AlphaEvolve
AlphaEvolve is an evolutionary coding agent for designing advanced algorithms based on large language models such as Gemini. It was developed by Google DeepMind and unveiled in May 2025. Design AlphaEvolve aims to autonomously discover and refine algorithms through a combination of large language models (LLMs) and evolutionary computation. AlphaEvolve needs an evaluation function with metrics to optimize, and an initial algorithm. At each step, AlphaEvolve uses the LLM to produce variants of the existing algorithms, and then selects the most effective ones. Unlike domain-specific predecessors like AlphaFold or AlphaTensor, AlphaEvolve is designed as a general-purpose system. It can operate across a wide array of scientific and engineering tasks by automatically modifying code and optimizing for multiple objectives. Its architecture allows it to evaluate code programmatically, reducing reliance on human input and mitigating risks such as hallucinations common in standard LLM o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Meta AI
Meta AI is a research division of Meta (formerly Facebook) that develops artificial intelligence and augmented reality technologies. History The foundation of laboratory was announced in 2013, under the name Facebook Artificial Intelligence Research (FAIR). FAIR has workspaces in Menlo Park, California, London, United Kingdom, and Manhattan. FAIR was first directed by New York University's Yann LeCun, a deep learning professor and Turing Award winner. Working with NYU's Center for Data Science, FAIR's initial goal was to research data science, machine learning, and artificial intelligence. Vladimir Vapnik, a pioneer in statistical learning, joined FAIR in 2014. FAIR opened a research center in Paris, France in 2015, and subsequently launched smaller satellite research labs in Seattle, Pittsburgh, Tel Aviv, Montreal and London. In 2016, FAIR partnered with Google, Amazon, IBM, and Microsoft in creating the Partnership on Artificial Intelligence to Benefit People and Society ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Minecraft
''Minecraft'' is a 2011 sandbox game developed and published by the Swedish video game developer Mojang Studios. Originally created by Markus Persson, Markus "Notch" Persson using the Java (programming language), Java programming language, the first public alpha build was released on 17 May 2009. The game was continuously developed from then on, receiving a full release on 18 November 2011. Afterwards, Persson left Mojang and gave Jens Bergensten, Jens "Jeb" Bergensten control over development. In the years since its release, it has been Video game port, ported to several platforms, including smartphones, tablets, and various video game consoles. In 2014, Mojang and the Minecraft (franchise), ''Minecraft'' intellectual property were purchased by Microsoft for billion. In ''Minecraft'', players explore a procedurally generated, three-dimensional world with virtually infinite terrain made up of voxels. Players can discover and extract raw materials, Glossary of video game terms ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Foundation Model
In artificial intelligence (AI), a foundation model (FM), also known as large X model (LxM), is a machine learning or deep learning model trained on vast datasets so that it can be applied across a wide range of use cases.Competition and Markets Authority (2023). ''AI Foundation Models: Initial Report''. Available at: https://assets.publishing.service.gov.uk/media/65081d3aa41cc300145612c0/Full_report_.pdf Generative AI applications like large language models (LLM) are common examples of foundation models. Building foundation models is often highly resource-intensive, with the most advanced models costing hundreds of millions of dollars to cover the expenses of acquiring, curating, and processing massive datasets, as well as the compute power required for training. These costs stem from the need for sophisticated infrastructure, extended training times, and advanced hardware, such as GPUs. In contrast, adapting an existing foundation model for a specific task or using it directly ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Multimodal Learning
Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video. This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, text-to-image generation, aesthetic ranking, and image captioning. Large multimodal models, such as Google Gemini and GPT-4o, have become increasingly popular since 2023, enabling increased versatility and a broader understanding of real-world phenomena. Motivation Data usually comes with different modalities which carry different information. For example, it is very common to caption an image to convey the information not presented in the image itself. Similarly, sometimes it is more straightforward to use an image to describe information which may not be obvious from text. As a result, if different words appear in similar images, then these words ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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] |
