About itinai.com Team
Our teams are a diverse group of talented individuals working remotely from different corners of the world. With members proficient in seven languages, we value and embrace diversity. However, what truly unites us is our shared passion for the language of modern technology. We come together to collaborate, innovate, and harness the power of cutting-edge technology to create exceptional solutions.
Our Mission
itinai.com is a global AI lab, product incubator. We make artificial intelligence accessible, applicable, and transparent for professionals across industries. Every article, tool, and product is driven by our belief that AI should be practical, verifiable, and human-centered.
Our Global AI Teams
At itinai.com, we build AI products and launch innovation programs in collaboration with expert teams across 12 countries.
- 🇷🇺 Russia
- 🇺🇦 Ukraine
- 🇰🇿 Kazakhstan
- 🇬🇪 Georgia
- 🇦🇪 UAE
- 🇺🇸 United States
- 🇵🇭 Philippines
- 🇻🇳 Vietnam
- 🇦🇷 Argentina
- 🇪🇪 Estonia
- 🇹🇭 Thailand
- 🇩🇪 Germany
Community of AI Builders
We are not just a tech company — we’re a decentralized network of creators, researchers, and entrepreneurs. Each team contributes to building AI-driven tools, bots, content engines, and monetization models tailored to local markets.
Editorial Principles
- Trustworthiness – We cite sources, check facts, and avoid hype.
- Experience-first – Written and reviewed by domain experts.
- Human in the Loop – AI is a tool, not a replacement for judgment.
- Transparency – Author names, background, and intent are disclosed.
AI Accelerators & Product Labs
In every region, we run AI Product Accelerators — programs that help local talent and businesses turn ideas into profitable, autonomous AI-powered businesses in just weeks. We provide infrastructure, AI models, training, and monetization pipelines.
Your Global AI Accelerator Partner. Ask me, I will help you
Get Involved
Follow us, contribute insights, or propose partnerships. We welcome collaboration from researchers, writers, and product leaders passionate about building ethical, usable AI.
Our Team’s the Most Interesting Articles Picks
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This AI Paper Unveils HyperDreamer: An Advancement in 3D Content Creation with Advanced Texturing, 360-Degree Modeling, and Interactive Editing
Researchers from various institutions have introduced HyperDreamer, a framework that can create detailed 3D content from a single 2D image. The study discusses existing 3D generation methods and emphasizes the need for advanced content creation. HyperDreamer…
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Model Openness Framework (MOF): Enhancing AI Transparency with 17 Essential Components for Full Lifecycle Openness and Reproducibility
Revolutionizing AI Transparency and Reproducibility with Model Openness Framework (MOF) Challenges in AI Transparency and Reproducibility AI has transformed various sectors, but faces challenges in transparency and reproducibility, hindering trust and collaboration. Model Openness Framework (MOF)…
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Shanghai AI Lab Releases OREAL-7B and OREAL-32B: Advancing Mathematical Reasoning with Outcome Reward-Based Reinforcement Learning
Mathematical Reasoning in AI: New Solutions from Shanghai AI Laboratory Understanding the Challenges Mathematical reasoning is a complex area for artificial intelligence (AI). While large language models (LLMs) have improved, they often struggle with tasks that…
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Efficient Function Calling in Small-Scale LLMs: A Game-Changer for AI Reasoning Tasks
Advancements in Language Models Recent improvements in Large Language Models (LLMs) have shown remarkable abilities in understanding and generating human language. These models can now perform tasks beyond simple text prediction, such as calling software APIs,…
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Meet SynthIA (Synthetic Intelligent Agent) 7B-v1.3: A Mistral-7B-v0.1 Model Trained on Orca Style Datasets
SynthIA-7B-v1.3 is a robust and flexible large language model with 7 billion parameters. It can be used for various purposes such as text creation, translation, generating original content, and answering questions. It is suitable for researchers,…
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Develop generative AI applications to improve teaching and learning experiences
Teachers and students can use a generative AI solution to create course materials and learn English words and sentences. The solution provides real-time assessments and personalized feedback for students. Teachers can generate questions and answers, create…
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Top 40+ Generative AI Tools (October 2023)
GPT-4 is the latest language model developed by OpenAI, known for its accuracy and safety. It can process various formats such as images, PDFs, and CSVs. Other AI tools mentioned include Bing AI for accurate answers,…
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A computer scientist pushes the boundaries of geometry
Greek mathematician Euclid, known as the father of geometry, revolutionized the understanding of shapes over 2,000 years ago. Today, MIT professor Justin Solomon applies modern geometric techniques to diverse problems, from machine-learning model testing to medical…
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UC Berkeley Researchers Introduce ThoughtSculpt: Enhancing Large Language Model Reasoning with Innovative Monte Carlo Tree Search and Revision Techniques
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Exploring Cooperative Decision-Making and Resource Management in LLM Agents: Insights from the GOVSIM Simulation Platform
Ensuring Safe and Reliable AI Decision-Making As AI becomes part of everyday life, it’s vital to make sure that Large Language Models (LLMs) are safe and reliable when making decisions. While LLMs perform well in many…
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This AI Paper from China Introduces ‘AGENTBOARD’: An Open-Source Evaluation Framework Tailored to Analytical Evaluation of Multi-Turn LLM Agents
AgentBoard, developed by researchers from multiple Chinese universities, presents a benchmark framework and toolkit for evaluating LLM agents. It addresses challenges in assessing multi-round interactions and diverse scenarios in agent tasks. With a fine-grained progress rate…
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Is Generative AI Boosting Individual Creativity but Reducing Collective Novelty?
Generative AI: Boosting Individual Creativity and Reducing Collective Novelty? Practical Solutions and Value: Generative AI technologies, such as Large Language Models (LLMs), can accelerate programming processes, enhance customer service productivity, improve work quality, reinforce messaging, and…
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Hugging Face Just Released SmolAgents: A Smol Library that Enables to Run Powerful AI Agents in a Few Lines of Code
Creating Intelligent Agents Made Easy Building intelligent agents has often been complicated and time-consuming, requiring technical skills and significant resources. Developers face challenges like API integration, environment setup, and dependency management. Simplifying these tasks is essential…
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25+ AI Companies from Y Combinator that have Trained their Own AI Models Instead of Using Someone Else’s Closed Model Through an API like a Black Box
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Some Commonly Used Advanced Prompt Engineering Techniques Explained Using Simple Human Analogies
Chaining Methods Analogy: Solving a problem step-by-step Chaining techniques direct AI through systematic procedures, similar to how people solve problems step by step. Examples include Zero-shot and Few-shot CoT. Zero-shot Chain-of-Thought Zero-shot CoT prompts AI to…
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Researchers from the University of Auckland Introduced ChatLogic: Enhancing Multi-Step Reasoning in Large Language Models with Over 50% Accuracy Improvement in Complex Tasks
Enhancing Multi-Step Reasoning in Large Language Models Practical Solutions and Value Large language models (LLMs) have shown impressive capabilities in content generation and problem-solving. However, they face challenges in multi-step deductive reasoning. Current LLMs struggle with…