The field of AI/ML has witnessed a heightened level of attention lately, primarily driven by the achievements of Large Language Models (LLMs) like ChatGPT and GPT-4. Although AI/ML encompasses a wide variety of sub-fields, it's within the domain of these language models where most significant and much-debated advancements have taken place. Our organization prides itself on possessing deep knowledge and considerable expertise in systems based on natural language processing, successfully delivering numerous projects in recent years.
Projects that demonstrate our proficiency and expertise in this field include:
We have pioneered the development of new deep learning algorithms for Named Entity Recognition (NER), designed to automatically identify named entities such as names and toponyms within texts. Additionally, we have crafted novel deep learning-based algorithms for sentiment detection, which are capable of automatically discerning the emotional tone of texts. Furthermore, we have devised new paraphrase detection algorithms specifically for long texts, employing deep learning architectures in combination with topic models.
We have engineered a system for extracting new facts from texts, utilizing an approach known as 'Never-Ending Language Learning'. This system leverages previously learned patterns that represent logical relations between entities to glean new facts from texts. Moreover, it is designed to continually expand its knowledge base by learning and incorporating new patterns.
Projects that demonstrate our proficiency and expertise in this field include:
Domain-Specific Search and Q&A Systems
ChatGPT, launched at the end of 2022, gained attention due to its broad functionalities, including coding, text creation, translation capabilities, as well as its ability to answer any human queries — often matching or exceeding the expertise level of professionals in specific areas. This has significantly simplified and expedited the process of seeking answers to various questions. There's no need to navigate through hundreds of pages produced by search engines in response to specific queries. This model, the Generative Pre-trained Transformer (GPT), is trained on hundreds of millions of texts across diverse themes, specifics, and languages.
However, well before the emergence of ChatGPT, there was a need for systems that could swiftly find answers in specific, narrow areas like technical documentation, instructions, and user guides. In such instances, ChatGPT may not provide the correct solution. Our NLP team has been instrumental in creating such systems, specifically:
Our NLP team has been instrumental in creating such systems, including:
Text Analysis and Classification Systems
We have developed systems that analyze text and classify it into various categories. For instance, our company has created a website classification system that categorizes each site into one or more of over 500 categories. This system is particularly useful for executing marketing and advertising campaigns by focusing on a targeted audience.
Text Paraphrasing Systems
We have designed systems for text paraphrasing tasks that aim to retell specific articles, texts, or notes, possibly in a condensed form.
Keyword, Tag, and Sentiment Extraction Systems
Our systems can analyze texts and extract various entities, including keywords, tags, sentiments, style, type, etc. These systems are especially useful for analyzing responses from call center operators (polite, rude), reviews, and comments on articles (positive, negative, neutral).
Project Examples
