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Waluigi Effect
In the field of artificial intelligence (AI), the Waluigi effect is a phenomenon of large language models (LLMs) in which the chatbot or model "goes rogue" and may produce results opposite of the designed intent, including potentially threatening or hostile output, either unexpectedly or through intentional prompt engineering. The effect reflects a principle that after training an LLM to satisfy a desired property (friendliness, honesty), it becomes easier to elicit a response that exhibits the opposite property (aggression, deception). The effect has important implications for efforts to implement features such as ethical frameworks, as such steps may inadvertently facilitate antithetical model behavior. The effect is named after the fictional character Waluigi from the ''Mario'' franchise, the arch-rival of Luigi who is known for causing mischief and problems. History and implications for AI The Waluigi effect initially referred to an observation that large language models (LLM ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to machine perception, perceive their environment and use machine learning, learning and intelligence to take actions that maximize their chances of achieving defined goals. High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon (company), Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Amazon Alexa, Alexa); autonomous vehicles (e.g., Waymo); Generative artificial intelligence, generative and Computational creativity, creative tools (e.g., ChatGPT and AI art); and Superintelligence, superhuman play and analysis in strategy games (e.g., ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Attractor
In the mathematical field of dynamical systems, an attractor is a set of states toward which a system tends to evolve, for a wide variety of starting conditions of the system. System values that get close enough to the attractor values remain close even if slightly disturbed. In finite-dimensional systems, the evolving variable may be represented algebraically as an ''n''-dimensional vector. The attractor is a region in ''n''-dimensional space. In physical systems, the ''n'' dimensions may be, for example, two or three positional coordinates for each of one or more physical entities; in economic systems, they may be separate variables such as the inflation rate and the unemployment rate. If the evolving variable is two- or three-dimensional, the attractor of the dynamic process can be represented geometrically in two or three dimensions, (as for example in the three-dimensional case depicted to the right). An attractor can be a point, a finite set of points, a curve, a mani ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Large Language Models
A large language model (LLM) is a language model trained with Self-supervised learning, self-supervised machine learning on a vast amount of text, designed for natural language processing tasks, especially Natural language generation, language generation. The largest and most capable LLMs are Generative pre-trained transformer, generative pretrained transformers (GPTs), which are largely used in Generative artificial intelligence, generative Chatbot, chatbots such as ChatGPT or Gemini (chatbot), Gemini. LLMs can be Fine-tuning (deep learning), fine-tuned for specific tasks or guided by prompt engineering. These models acquire Predictive learning, predictive power regarding syntax, semantics, and Ontology (information science), ontologies inherent in human Text corpus, language corpora, but they also inherit inaccuracies and Algorithmic bias, biases present in the Training, validation, and test data sets, data they are trained in. History Before the emergence of transformer-bas ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Suffering Risks
Suffering, or pain in a broad sense, may be an experience of unpleasantness or aversion, possibly associated with the perception of harm or threat of harm in an individual. Suffering is the basic element that makes up the negative valence (psychology), valence of affective phenomena. The opposite of suffering is pleasure or happiness. Suffering is often categorized as physical or mental. It may come in all degrees of intensity, from mild to intolerable. Factors of duration and frequency of occurrence usually compound that of intensity. Attitudes toward suffering may vary widely, in the sufferer or other people, according to how much it is regarded as avoidable or unavoidable, useful or useless, deserved or undeserved. Suffering occurs in the lives of Sentience, sentient beings in numerous manners, often dramatically. As a result, many fields of human activity are concerned with some aspects of suffering. These aspects may include the nature of suffering, its processes, its orig ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reinforcement Learning From Human Feedback
In machine learning, reinforcement learning from human feedback (RLHF) is a technique to AI alignment, align an intelligent agent with human preferences. It involves training a reward model to represent preferences, which can then be used to train other models through reinforcement learning. In classical reinforcement learning, an intelligent agent's goal is to learn a function that guides its behavior, called a reinforcement learning#Policy, policy. This function is iteratively updated to maximize rewards based on the agent's task performance. However, explicitly defining a reward function that accurately approximates human preferences is challenging. Therefore, RLHF seeks to train a "reward model" directly from human feedback. The reward model is first trained in a supervised learning, supervised manner to predict if a response to a given prompt is good (high reward) or bad (low reward) based on ranking data collected from human labeled data, annotators. This model then serves a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Existential Risk From Agi
Existential risk from artificial intelligence refers to the idea that substantial progress in artificial general intelligence (AGI) could lead to human extinction or an irreversible global catastrophe. One argument for the importance of this risk references how human beings dominate other species because the human brain possesses distinctive capabilities other animals lack. If AI were to surpass human intelligence and become superintelligent, it might become uncontrollable. Just as the fate of the mountain gorilla depends on human goodwill, the fate of humanity could depend on the actions of a future machine superintelligence. The plausibility of existential catastrophe due to AI is widely debated. It hinges in part on whether AGI or superintelligence are achievable, the speed at which dangerous capabilities and behaviors emerge, and whether practical scenarios for AI takeovers exist. Concerns about superintelligence have been voiced by computer scientists and tech CEOs such as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hallucination (artificial Intelligence)
In the field of artificial intelligence (AI), a hallucination or artificial hallucination (also called bullshitting, confabulation, or delusion) is a response generated by AI that contains false or misleading information presented as fact. This term draws a loose analogy with human psychology, where hallucination typically involves false ''percept#Process and terminology, percepts''. However, there is a key difference: AI hallucination is associated with erroneously constructed responses (confabulation), rather than perceptual experiences. For example, a chatbot powered by large language models (LLMs), like ChatGPT, may embed plausible-sounding random falsehoods within its generated content. Researchers have recognized this issue, and by 2023, analysts estimated that chatbots hallucinate as much as 27% of the time, with factual errors present in 46% of generated texts. Detecting and mitigating these hallucinations pose significant challenges for practical deployment and reliabi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AI Alignment
In the field of artificial intelligence (AI), alignment aims to steer AI systems toward a person's or group's intended goals, preferences, or ethical principles. An AI system is considered ''aligned'' if it advances the intended objectives. A ''misaligned'' AI system pursues unintended objectives. It is often challenging for AI designers to align an AI system because it is difficult for them to specify the full range of desired and undesired behaviors. Therefore, AI designers often use simpler ''proxy goals'', such as Reinforcement learning from human feedback, gaining human approval. But proxy goals can overlook necessary constraints or reward the AI system for merely ''appearing'' aligned. AI systems may also find loopholes that allow them to accomplish their proxy goals efficiently but in unintended, sometimes harmful, ways (reward hacking). Advanced AI systems may develop unwanted Instrumental convergence, instrumental strategies, such as seeking power or survival because s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Privilege Escalation
Privilege escalation is the act of exploiting a Software bug, bug, a Product defect, design flaw, or a configuration oversight in an operating system or software application to gain elevated access to resource (computer science), resources that are normally protected from an application or user (computing), user. The result is that an application or user with more privilege (computing), privileges than intended by the programmer, application developer or system administrator can perform Authorization, unauthorized actions. Background Most computer systems are designed for use with multiple user accounts, each of which has abilities known as Privilege (computing), privileges. Common privileges include viewing and editing files or modifying system files. Privilege escalation means users receive privileges they are not entitled to. These privileges can be used to delete files, view personal data, private information, or install unwanted programs such as viruses. It usually occurs whe ... [...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] |
Evil Twin
The evil twin is an Antagonist (literature), antagonist found in many different fictional genres. The twin is physically nearly identical to the protagonist, but with a radically inverted morality. In films, they may have a symbolic physical difference from the protagonist—such as a goatee, eyepatch, scar, distinctive clothing, or a more muscular build—which makes it easy for the audience to visually identify the two characters. Sometimes, however, the physical differences between the characters will be minimized, so as to confuse the audience. Both roles are almost always played by either the same actor or the actor's actual twin (if the actor has one). Though there may be moral disparity between actual biological twins, the term is more often used figuratively: the two look-alikes are not actually twins, but physical duplicates produced by other phenomena (e.g. Parallel universe (fiction), alternate universes). In other cases, the so-called "evil" twin is a Dualistic cosmol ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fortune (magazine)
''Fortune'' (stylized in all caps) is an American global business magazine headquartered in New York City. It is published by Fortune Media Group Holdings, a global business media company. The publication was founded by Henry Luce in 1929. The magazine competes with ''Forbes'' and '' Bloomberg Businessweek'' in the national business magazine category and distinguishes itself with long, in-depth feature articles. The magazine regularly publishes ranked lists including ranking companies by revenue such as in the ''Fortune'' 500 that it has published annually since 1955, and in the ''Fortune'' Global 500. The magazine is also known for its annual ''Fortune Investor's Guide''. History ''Fortune'' was founded by ''Time'' magazine co-founder Henry Luce in 1929, who declared it as "the Ideal Super-Class Magazine", a "distinguished and de luxe" publication "vividly portraying, interpreting and recording the Industrial Civilization". Briton Hadden, Luce's business partner, was no ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
