Governments should fund open-source AI safety tools and red-teaming infrastructure as public goods.

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Arguments for

Shared safety infrastructure

Several quotes portray AI defense tooling as shared infrastructure — including datasets, evaluation frameworks, attack simulators, and red-teaming tools — that governments and public institutes should help build in the open. They argue that open, auditable tools lower the barrier to rigorous evaluation and let organizations reuse a common foundation instead of starting from zero.

Companies and governments should invest in shared open infrastructure for AI defense — datasets, evaluation frameworks, attack simulators and red-teaming tools — much as past generations invested in open source software.

NVIDIA · Jul 27, 2026 · full quote
By open-sourcing not only Inspect, but also our methods and infrastructure where we can, we hope to help researchers, organisations, and other evaluators stand up rigorous evaluation capability without starting from zero.

AI Security Institute (AISI) · Jun 18, 2026 · full quote
Safety tools cannot remain exclusive to the largest companies; they must be open, auditable, and collectively improved—serving as a common good for the benefit of society. This is how we will build trustworthy AI that truly protects our children, our teenagers, and all our fellow…

Anne Le Hénanff · Jun 2, 2026 · full quote
By building safety tools in the open, this partnership will help organizations of every size adopt AI more responsibly. It strengthens trust, supports Canadian leadership in safe AI, and helps ensure the safeguards people rely on are transparent, verifiable, and shared.

Evan Solomon · Jun 2, 2026 · full quote
The UK, through AISI, has developed the world’s most widely used government-backed evaluation tools. Inspect, InspectSandbox, InspectCyber, and our latest release, ControlArena, are now being used by governments, companies, and academics around the world. These open tools lower t…

Kanishka Narayan · Feb 10, 2026 · full quote

Public evaluation capacity

Another line of argument is that testing frontier systems raises national security and public safety questions that require public-sector expertise, resources, and access. From this view, governments should establish or expand dedicated institutes and evaluation capacity so the strongest systems can be assessed by bodies with sufficient technical depth and in-house capability.

First, the federal government should lead the testing and evaluation of the most advanced systems. Frontier AI raises national security and public safety questions that require technical expertise, resources, and access that no state can fully replicate.

OpenAI · Jul 15, 2026 · full quote
The Commission will help establish an EU evaluation capacity to strengthen third-party assessment of AI capabilities and risks globally, supporting the regulatory function of the AI Office.

European Commission · Jul 7, 2026 · full quote
The Government has built in response: an Australian AI Safety Institute, up and running, staffed with world-class expertise, and already inside the engine rooms of frontier AI, testing the most powerful models on the planet.

Andrew Charlton · Jul 7, 2026 · full quote
Canada will invest $50 million to expand the capabilities of the Canadian AI Safety Institute to track emerging AI risks, advance technical research, and to conduct transparent evaluations of AI models.

Innovation, Science and Economic Development Canada · Jun 8, 2026 · full quote
The Future of Artificial Intelligence Innovation Act gets the federal role in AI policy exactly right. Authorizing the Center for AI Standards and Innovation is key to maintaining the United States’ leadership in Artificial Intelligence. As the federal government’s core in-house …

Samuel Hammond · Feb 26, 2026 · full quote

Correcting private undersupply

Some supporters say critical safety capabilities may be scarce or never developed privately when they conflict with profit concerns or address harms with real public stakes. Public funding is presented as a way to avoid leaving safety trade-offs to a handful of large companies and to make tools and evaluation capacity available across regions, providers, and under-resourced communities.

We call for publicly financed, regionally hosted capacity to evaluate AI systems before they are deployed, and open benchmarks built with and for under-resourced languages, so oversight is not outsourced to the same few actors it is meant to oversee.

Rebecca Rektimbo · Jul 7, 2026 · full quote
The safety problems that matter most are often the ones no one has been able to solve in the open. Safety guardrails for youth resilience is a clear example: the need is global, but the tools are scarce.

Camille François · Jun 2, 2026 · full quote
Safety for open-weight models whose capabilities are nearing frontier closed models requires unique tools for open-weight model safety and ecosystem monitoring. [...] Accelerated public and private investment in research is required to keep pace with commercially driven growth in…

The 2026 Singapore Consensus on Global AI Safety Research Priorities · Jul 2026 · full quote
AI safety should not be left to a handful of large companies making trade-offs behind closed doors. Partnering with ROOST lets our researchers work on harms with real public stakes, and commits us to putting what we build where any provider can use it.

Valérie Pisano · Jun 2, 2026 · full quote
Corporate AI often prioritizes profit over public good, and critical capabilities (safety, security, equitable access) may never be developed privately.

Bruce Schneier · 2026 · full quote
When the cost of providing access to AI models conflicts with corporate profit concerns, the U.S. government should step in by providing targeted funding and facilitating cross-lab coordination and efficiency. The U.S. government should also facilitate cybersecurity testing of wi…

Matthew Ferren · Jun 22, 2026 · full quote

Common benchmarks and consortia

A separate case focuses on standards and coordination: publicly backed benchmarks, measurement efforts, and shared evaluation frameworks can make testing more transparent, reproducible, and easier to compare across teams. Government-led consortia, joint evaluations, and international exchanges are described as ways to pool tools, methods, and guidance rather than fragment them.

At the European level, the existing legal frameworks, including NIS2, CRA and the EU AI Act should be leveraged, to ensure that systemic risks stemming from the most advanced AI models are assessed and mitigated. To this end, it may be useful to establish EU-wide state-of-the-art…

European Union Agency for Cybersecurity (ENISA) · Jul 2026 · full quote
GSA is preparing joint evaluation efforts with the National Institute of Standards and Technology’s AI Safety Institute and the Cybersecurity and Infrastructure Security Agency’s red-teaming initiative to benchmark frontier models for robustness, adversarial resistance, and bias.

U.S. General Services Administration · May 11, 2026 · full quote
In collaboration with the Vector Institute, we created new extensions to Inspect AI—the leading framework for AI safety evaluation—that make testing more transparent, reproducible and easier to share across teams.

National Research Council Canada · May 21, 2026 · full quote
We are inviting technically capable organizations to join the NIST AI Consortium to address the challenges associated with the development and deployment of AI. To encourage more extraordinary AI technological innovations, NIST is seeking to expand its AI measurement efforts by h…

Craig Burkhardt · May 29, 2026 · full quote
The Canadian and Korean AI Safety Institutes have signed a memorandum of understanding to strengthen international cooperation on artificial intelligence safety. Through this collaboration, the institutes will exchange information on AI technologies, risks, methodologies, tools a…

Government of Canada · Jul 8, 2026 · full quote

Operational cyber testing

Supporters also frame red-teaming infrastructure as operational defense capacity, including secure testing environments, national-lab testbeds, vulnerability scanning, and scalable support for state, local, or smaller actors. In this view, shared public infrastructure helps defenders discover and remediate AI-enabled vulnerabilities faster and with less duplication.

Build government AI–cyber capacity and translation infrastructure. Strengthen government capacity to evaluate, oversee, and respond to AI-enabled cyber risks by investing in technical staffing, institutional authority, and translation functions [...] expanding access to compute, …

Federation of American Scientists · Jan 2026 · full quote
Particularly in the context of AI-driven vulnerability discovery and exploit development, state and local governments will need ready access to the tools and capabilities that allow them to discover and remediate technical vulnerabilities in their systems. CISA and the MS-ISAC an…

Samir Jain · May 21, 2026 · full quote
Teams at DOE are also using testbeds at the national laboratories to perform red teaming of AI models.

United States Department of Energy · 2026 · full quote
If the modifier is required to conduct Step 3 as part of their initial burden when Steps 1 and 2 are inconclusive, the oversight body may, on application by an SME modifier, provide access to a shared government-funded red-teaming infrastructure at cost, recoverable from the ulti…

Bipin Kumar B · Mar 23, 2026 · full quote
GOLD EAGLE, established in President Trump’s June 2, 2026 Executive Order “Promoting Advanced Artificial Intelligence Innovation and Security” (EO 14409), represents a new operational model for cyber defense. This new model will leverage frontier AI capabilities to continue advan…

The White House · Jul 14, 2026 · full quote

Insights

Across the quotes, evaluation capacity is repeatedly treated as part of AI safety itself, not just as a downstream compliance or oversight function.
Many supporters pair openness with institutional backing: open tools are presented as most useful when public institutes, labs, or agencies also maintain expertise, testbeds, and governance.
Cybersecurity concepts recur throughout the material — attack simulators, cyber ranges, exploitability metrics, vulnerability scanning, and red teaming — showing how closely many authors link AI safety to cyber defense.
Several quotes justify public funding by arguing that profit incentives, concentration, or simple tool scarcity can leave important safety capabilities underprovided in private markets.
The supporting quotes come from governments, regulators, research agencies, companies, universities, and nonprofits across multiple countries, and many call for cooperation that crosses both sectors and borders.

In the material provided, the discussion centers on how governments should structure support for AI safety tooling and red-teaming capacity rather than on whether public institutions should play a role. The quotes repeatedly call for some mix of open-source tools, shared benchmarks, dedicated safety institutes, and secure testbeds. Differences in emphasis mainly concern whether the priority is frontier-system oversight, broader access and equity, or operational cyber defense.

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Results (68 votes):

Total (68 votes)

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For (68)

Government of India
National government of India, speaking through its Permanent Representative at the United Nations on artificial intelligence governance.

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votes For and says:

The Safe & Trusted AI pillar of the IndiaAI Mission aims to promote the responsible development, deployment and adoption of AI through indigenous governance frameworks, standards, tools and evaluation mechanisms. 13 Responsible AI projects have been ...
more AI Verified source (Jul 27, 2026)

added 2d ago

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NVIDIA
GPU and AI computing company

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votes For and says:

Companies and governments should invest in shared open infrastructure for AI defense — datasets, evaluation frameworks, attack simulators and red-teaming tools — much as past generations invested in open source software.
AI Verified source (Jul 27, 2026)

added 13d ago

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Advanced Research and Invention Agency (ARIA)
United Kingdom public R&D agency sponsoring AI-safety research and open-source coordination infrastructure.

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votes For and says:

To kickstart Phase 1 of this programme, we will be funding teams to develop open-source coordination infrastructure and perform fundamental research that moves us from empirical to theory-driven guarantees in agentic coordination.
AI Verified source (Jul 18, 2026)

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OpenAI
AI research organization

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votes For and says:

First, the federal government should lead the testing and evaluation of the most advanced systems. Frontier AI raises national security and public safety questions that require technical expertise, resources, and access that no state can fully replic...
more AI Verified source (Jul 15, 2026)

added 8d ago

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Chris Lehane
OpenAI chief global affairs officer

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votes For and says:

First, the federal government should lead the testing and evaluation of the most advanced systems. Frontier AI raises national security and public safety questions that require technical expertise, resources, and access that no state can fully replic...
more AI Verified source (Jul 15, 2026)

added 19d ago

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The White House
Executive office of U.S. president

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votes For and says:

GOLD EAGLE, established in President Trump’s June 2, 2026 Executive Order “Promoting Advanced Artificial Intelligence Innovation and Security” (EO 14409), represents a new operational model for cyber defense. This new model will leverage frontier AI ...
more AI Verified source (Jul 14, 2026)

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Rebecca Rektimbo
Connectivity Technical Projects Coordinator for LOCNET, a collaboration initiative of the Association for Progressive Communications and Rhizomatica, speaking at the UN Global Dialogue on AI Governance.

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votes For and says:

We call for publicly financed, regionally hosted capacity to evaluate AI systems before they are deployed, and open benchmarks built with and for under-resourced languages, so oversight is not outsourced to the same few actors it is meant to oversee.
AI Verified source (Jul 7, 2026)

added 15d ago

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European Systemic Risk Board
European Union body responsible for macro-prudential oversight and the prevention or mitigation of systemic risks to financial stability.

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votes For and says:

In order to reinforce the warning’s message, the General Board calls on the EU to scale up its capacity, expertise and strategic autonomy in this critical area. This requires a coordinated answer of all parties, including AI providers, software provi...
more AI Verified source (Jul 7, 2026)

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Andrew Charlton
Australian Assistant Minister for Science, Technology and the Digital Economy

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votes For and says:

The Government has built in response: an Australian AI Safety Institute, up and running, staffed with world-class expertise, and already inside the engine rooms of frontier AI, testing the most powerful models on the planet.
AI Verified source (Jul 7, 2026)

added 22d ago

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European Commission
EU's executive body

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The Commission will help establish an EU evaluation capacity to strengthen third-party assessment of AI capabilities and risks globally, supporting the regulatory function of the AI Office.
AI Verified source (Jul 7, 2026)

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Government of Pakistan
National government of Pakistan, speaking through its delegation at the UN Global Dialogue on AI Governance in July 2026.

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votes For and says:

We must therefore treat the capacity to evaluate and govern AI as an integral part to safety itself, supported through shared tools, pooled expertise, and cooperation across regions.
AI Verified source (Jul 7, 2026)

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Xinchen Hua Lu
UN AI panel member and researcher at CSIRO Australia.

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The government industrial research organizations, they could share their current evaluation tools or methods, evidence through the common platforms.
AI Verified source (Jul 7, 2026)

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European Union Agency for Cybersecurity (ENISA)
European Union agency dedicated to achieving a high common level of cybersecurity across Europe.

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votes For and says:

At the European level, the existing legal frameworks, including NIS2, CRA and the EU AI Act should be leveraged, to ensure that systemic risks stemming from the most advanced AI models are assessed and mitigated. To this end, it may be useful to esta...
more AI Verified source (Jul 2026)

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The 2026 Singapore Consensus on Global AI Safety Research Priorities
July 2026 international consensus report on AI safety research priorities produced by over 100 contributors from 13 countries.

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votes For and says:

Safety for open-weight models whose capabilities are nearing frontier closed models requires unique tools for open-weight model safety and ecosystem monitoring. [...] Accelerated public and private investment in research is required to keep pace with...
more AI Verified source (Jul 2026)

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Jan Wehner
AI governance researcher at the Institute for AI Policy and Strategy, writing on AI safety and cybersecurity.

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To avoid losing visibility into cutting-edge AI cyberattack capabilities exactly when it matters most, I argue governments should fund independent threat-intelligence collection and sharing, develop AI-specific forensic capabilities, build the capaci...
more AI Verified source (Jun 29, 2026)

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United Nations Office for Digital and Emerging Technologies
United Nations office supporting global digital cooperation and AI governance.

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votes For and says:

The report advances ten recommendations under the SAFE framework — Standards, Accountability, Finance, and Equity — including adopting the Model Openness Framework as a shared reference for assessing openness, building governance support around the D...
more AI Verified source (Jun 25, 2026)

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University of Oxford
University and research institution publishing official information on government-backed AI research and safety.

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The University of Oxford has been selected to host a new, cross-university government-backed UK AI Research Lab. The new lab is part of a £60 million investment announced today by the UKRI's Engineering and Physical Sciences Research Council (EPSRC) ...
more AI Verified source (Jun 23, 2026)

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Matthew Ferren
Council on Foreign Relations International Affairs Fellow in National Security and former U.S. Department of Defense cyber-policy official.

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votes For and says:

When the cost of providing access to AI models conflicts with corporate profit concerns, the U.S. government should step in by providing targeted funding and facilitating cross-lab coordination and efficiency. The U.S. government should also facilita...
more AI Verified source (Jun 22, 2026)

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AI Security Institute (AISI)
UK government AI safety institute

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votes For and says:

By open-sourcing not only Inspect, but also our methods and infrastructure where we can, we hope to help researchers, organisations, and other evaluators stand up rigorous evaluation capability without starting from zero.
AI Verified source (Jun 18, 2026)

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The AI Security Institute
UK government research organisation focused on AI safety and security

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votes For and says:

By open-sourcing not only Inspect, but also our methods and infrastructure where we can, we hope to help researchers, organisations, and other evaluators stand up rigorous evaluation capability without starting from zero. We hope that the Engineering...
more AI Verified source (Jun 18, 2026)

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Mischa Spiegelmock
Technical staff member at METR working on frontier model evaluations

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votes For and says:

Absolutely central to METR's evaluations is Inspect, which we've built our own open source cloud eval platform on top of, along with actively contributing to the Inspect codebase to run larger and more complex evaluations.
AI Verified source (Jun 18, 2026)

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JJ Allaire
Founder and Executive Chairman of Posit; creator of Inspect

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I created Inspect because I wanted to provide a strong technical foundation for governments, researchers, and labs to collaborate on testing and understanding frontier models. I am thrilled to have seen so many organisations adopt it, as well as to h...
more AI Verified source (Jun 18, 2026)

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Innovation, Science and Economic Development Canada
Government of Canada department responsible for innovation, science, and economic development.

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Canada will invest $50 million to expand the capabilities of the Canadian AI Safety Institute to track emerging AI risks, advance technical research, and to conduct transparent evaluations of AI models.
AI Verified source (Jun 8, 2026)

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Jack Cable
CEO and co-founder of Corridor; former CISA Secure by Design initiative lead and cybersecurity expert.

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The challenge is especially acute for open source software, since it’s a public good. Open source software underpins every software service we rely upon, including across critical infrastructure and the Federal government. A string of recent incident...
more AI Verified source (Jun 4, 2026)

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Camille François
President and CEO of Robust Open Online Safety Tools (ROOST)

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The safety problems that matter most are often the ones no one has been able to solve in the open. Safety guardrails for youth resilience is a clear example: the need is global, but the tools are scarce.
AI Verified source (Jun 2, 2026)

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Anne Le Hénanff
French Minister for Artificial Intelligence and Digital Affairs.

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votes For and says:

Safety tools cannot remain exclusive to the largest companies; they must be open, auditable, and collectively improved—serving as a common good for the benefit of society. This is how we will build trustworthy AI that truly protects our children, our...
more AI Verified source (Jun 2, 2026)

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Evan Solomon
Canada's Minister of Artificial Intelligence and Digital Innovation; Liberal MP for Toronto Centre

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votes For and says:

By building safety tools in the open, this partnership will help organizations of every size adopt AI more responsibly. It strengthens trust, supports Canadian leadership in safe AI, and helps ensure the safeguards people rely on are transparent, ver...
more AI Verified source (Jun 2, 2026)

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Lori Trahan
U.S. representative from Massachusetts

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Funding should be allocated for open-source maintainers, and frontier AI developers should be required to give them access to their models for security work.
AI Verified source (Jun 1, 2026)

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G7 Digital and Technology Ministerial Declaration
Collective ministerial declaration of the Group of Seven on digital and technology policy, including international AI governance.

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Such discussions may also contribute to enhance the French Presidency’s Meta-detector for AI-generated content, an open source tool that aggregates multiple synthetic content detectors, enabling cross-referenced assessments.
AI Verified source (Jun 1, 2026)

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National Research Council Canada
Canada's federal research and development organization.

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In collaboration with the Vector Institute, we created new extensions to Inspect AI—the leading framework for AI safety evaluation—that make testing more transparent, reproducible and easier to share across teams.
AI Verified source (May 21, 2026)

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