Ai-Forum.org publishes practical information about artificial intelligence, local models, WordPress integrations, APIs, and automation. This policy sets the standards for editorial articles, tutorials, comparisons, and other publisher-produced resources. It also explains how that material differs from community contributions.
Our purpose is to help readers understand a subject, complete a task, or investigate a problem. Topic selection should reflect genuine questions, implementation challenges, and useful learning opportunities. Search demand may help identify those needs, but keywords, publication volume, and article length do not replace editorial judgment.
Editorial content must distinguish established facts, provider claims, firsthand observations, estimates, and opinions. Authors should explain uncertainty and avoid presenting a limited example as a universal conclusion. Headlines, summaries, and illustrations must accurately represent the substance of the content.
Sources should be appropriate to the claim. Official documentation, release notes, original research, specifications, repositories, and licensing documents are preferred for technical details. Independent reporting and community experiences can provide additional context. A provider’s announcement establishes what the provider says; it does not independently establish real-world performance.
Important or disputed claims should include references that allow readers to examine the supporting evidence. Authors must check that a cited source exists, supports the associated statement, and applies to the relevant version or context. Quotes must preserve meaning and be attributed. Unsupported citations and invented references are unacceptable.
Tutorials should identify prerequisites and explain the intended outcome. When an article reports a tested procedure, it should state the relevant environment, including software versions, operating system, hardware, or configuration where these affect the result. Untested suggestions, adaptations, and documentation-based instructions must not be described as verified implementations.
Benchmarks and comparisons require an explained method. Relevant details may include the exact model or release, quantization, runtime, hardware, context settings, test inputs, evaluation criteria, and number of runs. Report meaningful limitations, unsuccessful results, and variation. Do not imply that one task or one computer establishes overall superiority.
Cost and memory calculations must identify assumptions and distinguish estimates from measured results. Prices and service limits should be checked against current provider information when discussed. Where an article includes a “last tested” date, that date must refer to an actual test rather than a routine text edit.
A named author or responsible editor must review publisher-produced content before publication. The review should consider factual support, clarity, attribution, technical context, and whether the conclusions follow from the evidence. Specialist review should be identified when it occurs; general editorial review must not be presented as expert validation.
AI tools may assist with planning, drafting, editing, translation, or analysis. Human responsibility remains with the author or editor. AI output is not evidence, and generated text must not be used to fabricate quotations, experiments, credentials, or personal experience. Material AI involvement should be disclosed when it affects how readers should interpret the work, including synthetic examples or generated illustrations that could otherwise be mistaken for observed results.
Forum posts and replies are member contributions, not automatically reviewed editorial material. Contributors should distinguish what they tested from what they inferred or read elsewhere. Votes, badges, and accepted-answer labels reflect community or platform activity and do not guarantee accuracy, expertise, or independent verification.
When community knowledge informs an article, editors should assess the underlying evidence and credit the contribution appropriately. Public availability does not remove copyright or privacy obligations. Private messages, confidential documents, and sensitive logs must not be republished without an appropriate basis. Examples should remove credentials and unnecessary identifying information.
Commercial relationships must not determine editorial conclusions. Relevant sponsorships, affiliate arrangements, gifts, or supplied access should be disclosed clearly with the affected content. Paid material must be recognizable as such. Payment must not secure a favorable verdict, fabricated experience, undisclosed promotion, or removal of justified criticism. Contributors should disclose conflicts that could reasonably affect a reader’s assessment.
Content should remain open to correction. Readers can report an issue through the contact page, identifying the URL, affected passage, and supporting evidence. Reports should be evaluated on their merits, including when they challenge a recommendation or commercial partner.
Substantive factual corrections should be accompanied by a dated explanation of what changed. Minor spelling or formatting fixes may be made without a correction notice. Major revisions should distinguish a refreshed explanation from a new technical test. Material that is no longer reliable may be labeled, rewritten, archived, or withdrawn, with an explanation where appropriate.
Review priorities should reflect reader impact, reported problems, security concerns, and changes to relevant products or documentation. Publication and update dates must not be changed merely to suggest freshness. Older content can remain useful when its historical context and limitations are clear.
This policy is an editorial standard, not a promise that every page will remain error-free or current. It should be read alongside our Disclaimer, Terms of Service, community rules, and any more specific sourcing, testing, or corrections policies. Questions about its application may be submitted through the contact page.