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If you’ve spotted a factual error, an outdated reference, or wish to propose an edit: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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Kosmos: The AI Scientist Revolutionizing Data-Driven Research
Understanding Kosmos: The Autonomous AI Scientist Kosmos, created by Edison Scientific, is revolutionizing the way scientific research is conducted. This autonomous discovery system is designed to run extensive research campaigns focused on a single goal. By…
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Successful AI Use Cases in Predictive Maintenance: Insights and Trends
Leveraging Predictive Maintenance with AI and IoT Leveraging Predictive Maintenance with AI and IoT As businesses increasingly adopt predictive maintenance systems that integrate Artificial Intelligence (AI) and Internet of Things (IoT) sensors, they are discovering significant…
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Top 10 Use Cases of ChatGPT
Practical Applications of ChatGPT in Business Customer Support Automation ChatGPT powers chatbots for 24/7 customer assistance, freeing human agents to handle complex issues. Content Creation Generate diverse content types, reducing workload on creative teams and ensuring…
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Exposing Vulnerabilities in Automatic LLM Benchmarks: The Need for Stronger Anti-Cheating Mechanisms
Understanding Automatic Benchmarks for Evaluating LLMs Affordable and Scalable Solutions: Automatic benchmarks like AlpacaEval 2.0, Arena-Hard-Auto, and MTBench are becoming popular for evaluating Large Language Models (LLMs). They are cheaper and more scalable than human evaluations.…
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AI networks are more vulnerable to malicious attacks than previously thought
A study reveals that artificial intelligence systems, used in areas like self-driving cars and medical imaging, are more susceptible to deliberate attacks that can trigger incorrect decisions than previously understood.
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Cobra for Multimodal Language Learning: Efficient Multimodal Large Language Models (MLLM) with Linear Computational Complexity
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Google AI Introduces Audioplethysmography (APG): An Artificial Intelligence-Powered Novel Cardiac Monitoring Modality for Active Noise Cancellation (ANC) Headphones
Google AI has developed a groundbreaking technique called Audioplethysmography (APG) that enables active noise cancelling (ANC) headphones to monitor the user’s cardiac activities without additional sensors or complex hardware configurations. APG leverages low-intensity ultrasound signals transmitted…
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Meet PIXART-α: A Transformer-Based T2I Diffusion Model Whose Image Generation Quality is Competitive with State-of-the-Art Image Generators
Researchers have developed a new text-to-image generative model called PIXART-α that offers high-quality picture generation while reducing resource usage. They propose three main designs, including decomposition of the training plan and using cross-attention modules. Their model…
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iP-VAE: A Spiking Neural Network for Iterative Bayesian Inference and ELBO Maximization
The iP-VAE: A New Approach to AI and Neuroscience Understanding the Evidence Lower Bound (ELBO) The Evidence Lower Bound (ELBO) is crucial for training generative models like Variational Autoencoders (VAEs). It connects to neuroscience through the…
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Meet ScaleCrafter: Unlocking Ultra-High-Resolution Image Synthesis with Pre-trained Diffusion Models
Researchers have developed ScaleCrafter, a method that enables the generation of ultra-high-resolution images using pre-trained diffusion models. By dynamically adjusting the convolutional receptive field, ScaleCrafter addresses issues like object repetition and incorrect object topologies. It also…
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DPLM-2: A Multimodal Protein Language Model Integrating Sequence and Structural Data
Understanding Proteins and AI Solutions What Are Proteins? Proteins are essential molecules made up of amino acids. Their specific sequences determine how they fold and function in living beings. Challenges in Protein Modeling Current protein modeling…
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AnyGraph: An Effective and Efficient Graph Foundation Model Designed to Address the Multifaceted Challenges of Structure and Feature Heterogeneity Across Diverse Graph Datasets
Graph Learning: Addressing the Challenges with AnyGraph Practical Solutions and Value Graph learning is crucial for various domains like social networks, transportation systems, and biological networks. AnyGraph is a versatile model designed to handle the diversity…
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GPU-Accelerated Ollama LangChain Workflow: Enhance AI with RAG Agents and Chat Monitoring
Building a GPU-Accelerated Ollama LangChain Workflow Creating a powerful AI system doesn’t have to be daunting. This tutorial walks you through the steps to build a GPU-accelerated local language model (LLM) stack using Ollama and LangChain.…
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How to Delete Character.ai Account (Tutorial)
This tutorial provides step-by-step instructions on how to delete your Character.ai account both via the website and the mobile app. It includes detailed guidance on logging in, accessing profile settings, and confirming the account deletion. The…
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Microsoft Research Evaluates the Inconsistencies and Sensitivities of GPT-4 in Performing Deterministic Tasks: Analyzing the Impact of Minor Modifications on AI Performance
Value of Large Language Models (LLMs) like GPT-4 in AI Practical Solutions and Insights Large language models like GPT-4 play a crucial role in artificial intelligence by performing diverse tasks such as text generation and complex…
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Sam Altman och Arianna Huffington lanserar Thrive AI Health