# Research

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***AANN.AI Labs*** research and development team leverages cutting-edge technologies to solve complex problems in various domains such as machine learning pipelines, natural language processing and graph data analysis.

We apply the state-of-the-art technologies to apply them to real-world problems that require extracting valuable insights from data. To achieve these goals, the team performs the following tasks:

* Researching novel techniques and methods for natural language processing, deep learning and graph data analysis, such as neural networks, large language models, sentiment analysis, named entity recognition, clustering, classification, text generation, fact-checking, and more.
* Developing and testing AI-based systems and applications that leverage these techniques and methods, such as intelligent assistants, chatbots, recommender systems, social network analysis, and more.
* Evaluating and improving the performance, usability, and reliability of these systems and applications, using various metrics and feedback mechanisms.

We store and process diverse types of data from both our own application and external sources. This enables us to provide a robust and reliable metric of social authenticity that reflects the quality and credibility of online interactions.


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If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://aann-ai.gitbook.io/social-authenticity-network/aann.ai-lab/research.md?ask=<question>
```

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Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
