Editorial Policy itinai.com
At itinai.com, we take editorial integrity seriously. Our mission is to create trustworthy, useful, and verifiable content in the field of artificial intelligence, innovation, and product development.
Every article published on itinai.com undergoes human review and aligns with the principles below.
Our Editorial Principles
- Accuracy – We fact-check our content and update it when necessary.
- Transparency – We disclose the source, author, and publishing intent.
- Experience-first – Our content is written or reviewed by practitioners and domain experts.
- Human in the loop – No article is published without human editorial oversight.
- Clarity – We prioritize plain, accessible language and practical insight.
- Accountability – Errors are corrected. Feedback is encouraged and valued.
Submit a Correction or Suggest an Update
We welcome suggestions to improve our content.
If you’ve spotted a factual error, an outdated reference, or wish to propose an edit:
📬 Email: editor@itinai.com
All valid correction requests are reviewed within 72 hours.
In most cases, you will receive a reply from our editorial team.
Submit a News Item or Contribute Content
Want to submit a story, research highlight, or industry insight?
We accept contributions in the following formats:
- Short AI news (100–300 words)
- Research summary (with link to paper)
- Opinion/editorial piece
- Product case study (original only)
📥 Send your pitch to: editor@itinai.com
💡 Guest authorship is available — we credit all contributors.
Editor-in-Chief assistant
Editorial Review Process
Every piece of content published on itinai.com follows a structured editorial workflow:
- Drafting – Written by in-house authors or external contributors.
- Expert Review – Reviewed by a domain specialist (AI, product, healthcare, or law).
- Editor-in-Chief Review – Final oversight by Vladimir Dyachkov, Ph.D.
- Fact-Checking – Sources verified manually and/or via LLM-assisted tools.
- Markup – Structured data (
Article,Person,WebPage) is applied. - Publishing – With author attribution and publishing date.
- Monitoring – Regularly re-evaluated for accuracy and relevancy.
Note: If AI tools assist in drafting or summarizing, this is clearly disclosed.
User & Company Feedback, Corrections
We actively encourage users, companies, and institutions to report factual errors or request content updates.
How we handle it:
- Submissions are received
- An editor reviews the case manually within 72 hours.
- Verified changes are fact-checked again, optionally using AI models for cross-verification (e.g., citation match, entity comparison).
- If the correction significantly changes the context or outcome, we:
- Add a “Corrected on” notice to the article
- Publish a separate editorial blog post explaining the change in our Editor’s Blog
We do not silently alter content unless it’s a typo or formatting issue.
Propose a Story or Suggest an Edit
We believe in collaborative knowledge. Anyone can contribute insights or highlight gaps.
📬 To contribute:
- Factual correction – Use our correction request form
- Submit a news item – Email your pitch to editor@itinai.com
- Contribute a piece – See our Contributor Guidelines
We welcome:
- Original insights
- AI research summaries
- Localization use cases
- Startup/product case studies
Every submission is reviewed by humans. We may edit for clarity or add editorial context.
Get Involved
Follow us, contribute insights, or propose partnerships. We welcome collaboration from researchers, writers, and product leaders passionate about building ethical, usable AI.
Contact and Transparency
- Email: editor@itinai.com
- Telegram: @itinai
- LinkedIn: itinai.com company page
You can also explore:
Editorial Picks
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Diagram of Thought (DoT): An AI Framework that Models Iterative Reasoning in Large Language Models (LLMs) as the Construction of a Directed Acyclic Graph (DAG) within a Single Model
Practical Solutions and Value of DoT Framework Enhancing Reasoning Capabilities The Diagram of Thought (DoT) framework integrates multiple reasoning approaches within a single Large Language Model (LLM), improving problem-solving capabilities through a directed acyclic graph (DAG)…
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Meta AI Launches Perception Encoder: A Unified Vision Model for Images and Video
Meta AI’s Perception Encoder: A Business Perspective Meta AI’s Perception Encoder: A Business Perspective The Challenge of General-Purpose Vision Encoders As artificial intelligence (AI) systems evolve, the demand for sophisticated visual perception models has increased. These…
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s1: A Simple Yet Powerful Test-Time Scaling Approach for LLMs
Understanding Language Models and Test-Time Scaling Language models (LMs) have evolved rapidly due to advancements in computational power and large-scale training methods. Recently, a new technique called test-time scaling has emerged, which focuses on improving model…
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EPFL Researchers Releases 4M: An Open-Source Training Framework to Advance Multimodal AI
Introduction to Multimodal Foundation Models Multimodal foundation models are becoming crucial in artificial intelligence as they can handle different types of data, like images, text, and audio. These models help perform various tasks effectively. However, they…
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NVIDIA AI Introduces FACTS: A Comprehensive Framework for Enterprise RAG-Based Chatbots
Practical Solutions for Enterprise Chatbots with NVIDIA’s FACTS Framework Challenges in Developing Enterprise Chatbots Building effective chatbots for enterprises can be challenging due to issues like accuracy, context relevance, and data freshness. The FACTS Framework NVIDIA’s…
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Why Do We Even Have Neural Networks?
The text delves into the idea of using Taylor Series and Fourier Series as alternatives to neural networks. It emphasizes their application in approximating functions and their similarities to neural network structures. The author discusses the…
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Meet AlphaMonarch-7B: One of the Best-Performing Non-Merge 7B Models on the Open LLM Leaderboard
Developing a new model, AlphaMonarch-7B, aims to strike a balance between conversational fluency and reasoning prowess in artificial intelligence. Its unique fine-tuning process enhances its problem-solving abilities without compromising its conversational skills. This model’s performance on…
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This AI Paper from UCSD and Johns Hopkins Unveils the LAW Framework: A Leap in Machine Learning with Integrated Language, Agent, and World Models for Enhanced Reasoning
This study introduces the LAW framework, combining language, agent, and world models to enhance machine reasoning and planning. It addresses limitations in current language models by integrating human-like reasoning elements and real-world context. The framework demonstrates…
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Celonis vs IBM Process Mining: Who Leads in Enterprise-Scale Process Intelligence With AI?
Celonis vs. IBM Process Mining: A Head-to-Head Comparison Purpose of Comparison: This comparison aims to provide a clear, objective evaluation of Celonis and IBM Process Mining, two leading enterprise-scale process intelligence solutions leveraging AI. We’ll assess…
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Google DeepMind Unveils PaliGemma: A Versatile 3B Vision-Language Model VLM with Large-Scale Ambitions
Vision-Language Models: Practical Solutions and Value Evolution of Vision-Language Models Vision-language models have evolved significantly, with two distinct generations. The first generation expanded on large-scale classification pretraining, while the second generation unified captioning and question-answering tasks.…
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Is This the Solution to P-Hacking?
E-values are proposed as a superior alternative to p-values. This article explores their advantages and benefits in statistical analysis.
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MemoryFormer: A Novel Transformer Architecture for Efficient and Scalable Large Language Models
Transforming AI with Efficient Models What are Transformer Models? Transformer models have revolutionized artificial intelligence, enhancing applications in areas like natural language processing, computer vision, and speech recognition. They are particularly good at understanding and generating…
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Amazon Q leaks sensitive information about data center locations
Amazon’s AI chatbot, Amazon Q, has allegedly leaked sensitive internal information including AWS data centers and unreleased features. While Amazon denies security breaches, internal Slack communications show employee concerns. This leak is unconfirmed but follows past…
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Master the Desktop Commander MCP Server: A Comprehensive Guide for Developers
The Desktop Commander MCP Server is more than just a tool; it’s a game-changer for developers and tech enthusiasts looking to streamline their workflow. Imagine having a single chat interface that allows you to manage files,…
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40 ChatGPT Prompts to Boost Your Social Media and Double Your Output
The use of ChatGPT has expanded across different sectors, including students, tech enthusiasts, and business owners. While currently more oriented towards technical solutions like SEO and data science, it is expected to have widespread cultural impact,…
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AutoDroid-V2: Leveraging Small Language Models for Automated Mobile GUI Control
Revolutionizing Mobile Device Control with AutoDroid-V2 Understanding the Challenge Large Language Models (LLMs) and Vision Language Models (VLMs) have transformed how we control mobile devices using natural language. Traditional methods, known as “Step-wise GUI agents,” query…