Frontier AI systems

Extracted Attributes

• Risks

  Existential risk from AGI if misaligned; ethical questions regarding bias, privacy, and decision-making transparency; not robust and frequently fail in situations unlike training data; safeguards are not robust and can be 'jailbroken'; national security priority, raising risk of an 'AI arms race'; erosion of international norms and laws, acceleration of AI integration into military systems, and strategic instability.

• Coined by

  UK government

• Definition

  Advanced artificial intelligence, including Artificial General Intelligence (AGI), that possess significant capabilities, potentially including recursive self-improvement.

• Coined Date

  mid-2023

• Capabilities

  Perform a wide range of tasks including language and image processing; function as a platform for other applications; accelerate AI progress by creating synthetic data, writing code, and improving model architectures.

• Control Methods

  AI capability control proposals, also referred to as AI confinement, aiming to increase human ability to monitor and control AI behavior.

• OpenAI's Approach

  Proprietary approach for its frontier models, emphasizing continuous model improvement over discrete versions.

• Key Characteristics

  Complex neural network architecture, new attention mechanisms, efficient parameter usage, multi-modal processing, zero-shot learning, scalable deployment.

• Definition (Web Search)

  AI models that match or outperform existing cutting-edge AI models either in terms of capabilities or variety of tasks; often foundational models or general-purpose AI (GPAI).

• Effectiveness of Control

  Diminishes as agents become more intelligent.

Timeline

• The term 'Frontier AI' was coined by the UK government. (Source: Verpex)

  2023-MM-DD

• Sam Altman's firing and rehiring at OpenAI, attributed to a culture clash with the OpenAI Nonprofit Board regarding the pace and methods for pursuing safe AGI, which is a component of Frontier AI systems. (Source: Document 8905c897-bf22-4c6e-a62d-73123999ebf4)

  2023-11-MM

AI capability control

In the field of artificial intelligence (AI) design, AI capability control proposals, also referred to as AI confinement, aim to increase human ability to monitor and control the behavior of AI systems, including proposed artificial general intelligences (AGIs), in order to reduce dangers they might pose if misaligned. Capability control becomes less effective as agents become more intelligent and their ability to exploit flaws in human control systems increases, potentially resulting in an existential risk from AGI. Therefore, the Oxford philosopher Nick Bostrom and others recommend capability control methods only as a supplement to alignment methods.

Web Search Results

• Frontier AI: Heading safely into new territory - Trilateral Research

  ‘Frontier AI’ is a catch all term used to describe AI models that match or outperform existing cutting-edge AI models either in terms of capabilities or variety of tasks. At the moment, ‘frontier AI’ means foundational models or general-purpose AI (GPAI). In contrast to narrow AI systems, these systems can perform a wide range of tasks including language and image processing. They often function as a type of platform, which other developers can use to build applications on. Thus, the most

• What is Frontier AI: its Benefits and Impact - Verpex

  Frontier AI, on the other hand, refers to the most advanced AI models or systems that push the boundaries of artificial intelligence. While some frontier AI systems utilize foundational models, not all foundational models qualify as frontier AI. [...] 4. Ethical and Societal Concerns: The deployment of frontier AI raises ethical questions, particularly regarding bias, privacy, and decision-making transparency. AI systems trained on biased data can unintentionally reinforce unfair stereotypes, leading to discrimination against certain groups. Additionally, the extensive data collection required for training these models poses privacy concerns, necessitating robust data protection measures. Ensuring transparency in AI decision-making processes [...] > The term Frontier AI was coined by the UK government in mid-2023, where they defined it as a highly capable general-purpose model that can perform a wide range of tasks and match or exceed the capabilities of today’s most advanced models.

• [PDF] VERIFICATION OF FRONTIER AI - the United Nations

  T he term “frontier AI” refers to highly capable general-purpose AI models that can perform many tasks matching or exceeding the capabilities of today’s most advanced models.2 Frontier AI is poised to transform a wide range of industries, including healthcare, agriculture, finance, transportation, and security. Given the transformative potential of this technology, major powers increasingly see frontier AI as a national security priority, raising the risk of a “frontier AI arms race”.3 Noting [...] means the ability of a party to attest to the actions of another party. In the context of frontier AI, it refers to the ability to attest to a wide range of relevant claims about the development and use of AI sys­ tems, such as properties of a frontier AI training run; the application of specified safety test­ ing and mitigations; evaluation results assessing a system’s capabilities and propensities; its uses at inference time; the size and speed of inference and training compute resources; or [...] this growing competition, AI experts and scientists have highlighted a wide range of associated risks, including erosion of longstanding international norms and laws, acceler­ ation of AI integration into military systems, and strategic instability that could bring major powers into more direct forms of confrontation.4 One of the most important ways to reduce the risks surrounding frontier AI could be to devel­ op a trusted, effective system of verification. In general terms, “verification”

• Frontier AI: capabilities and risks – discussion paper - GOV.UK

  Importantly, there is also the prospect that AI systems themselves accelerate AI progress. Frontier AI is already helping AI researchers to create synthetic data for training,( write new code,( and even improve model architectures.( While AI research is currently mostly non-automated, increased automation by future frontier AI systems may accelerate the pace of AI progress significantly.( This could mean we develop very capable AI systems sooner that we would otherwise expect, and have less [...] In general, frontier AI systems are not robust, i.e. they frequently fail in situations sufficiently unlike their training data.( In particular, safeguards to prevent frontier AI models from complying with harmful requests (such as designing cyberattacks)( are not robust, and ‘adversarial’ users who aim to bypass these safeguards have succeeded. Simple ‘jailbreaking’ approaches, such as prompting the model to respond affirmatively to a request, are often sufficient, although more unusual [...] Frontier AI systems operate in open-ended domains, such as free-form dialogue or code generation. The complexity of open-ended domains makes it difficult to design safe systems or exhaustively evaluate all downstream use cases. While we can restrict the behavioural repertoire of an AI (for instance to text outputs from a limited vocabulary), this limits performance so may be uncompetitive and AI systems often use their behavioural repertoire in unanticipated ways, realising unexpected – and

• Frontier AI Models: Revolutionizing Business and Technology ...

  To stay competitive, businesses must adopt the latest technologies that drive innovation and efficiency. Frontier AI models are revolutionizing the way organizations approach complex challenges by offering unmatched versatility in processing text, images, and audio. These models enable businesses to adapt quickly, automate tasks, and make smarter, data-driven decisions. With the ability to handle multiple inputs simultaneously, frontier AI models are not just improving customer experiences, but [...] The designation of a "frontier" model goes beyond mere computational power or parameter count. These models are distinguished by several key characteristics: 1. Architectural Invention: Frontier AI models are characterized by complex neural network architecture, especially new attention mechanisms and how to use parameters efficiently. All these inventions make this model more effective in processing the information and lead to greater performance and responsiveness in any application. [...] Frontier AI models are pushing the boundaries of artificial intelligence with advanced features like multi-modal processing, zero-shot learning, and scalable deployment. These models offer unmatched versatility and intelligence but face challenges related to ethics, security, and resource-intensive deployment. Proper regulation, transparency, and safety measures are crucial to ensuring their responsible and effective use. ”