State of the Art Natural Language Processing

ChatGPt and other Large Language Models are radically changing what we thought was possible.

Automatically read your documents and distill valuable insights across your corpora with NLP.

Modern applications generate troves of documents; if mined effectively, these documents can provide valuable insights. In order to effectively mine text, we must teach machines to read these vast collections and understand the content. State of the art NLP technologies like Large Language Models (LLMs) allow us to leverage hard fought machine knowledge gained from public texts available on the Internet.

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“I don’t think a five out of five really encapsulates the work that they do. The work is top-notch. It’s what we ask for and more. They go the extra mile in terms of letting us know that whatever we need, they’re there for us to lend their expertise, to be in a meeting if they need to, to explain the project in more detail. So it’s really going above and beyond.”

Dominique Grinnell, Sr. Product Team Manager at Delta Dental of Washington [more]

Enhanced conversation understanding

What almost all conversational interfaces have in common are problems with machine reading comprehension. Leveraging state of the art technologies like ChatGPT, LLMs, and our team's more than 60 years of combined deep NLP experience, we've helped a number of companies transform their conversational understanding capabilities.

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Automatic content creation

Modern AI algorithms are trained on billions of media items including text, audio, images and video, and can be harnessed to author text that is nearly indistinguishable from human-authored text. With the release of ChatGPT and other LLMs, the business world is just now realizing what our team has known for decades, that NLP and AI can transform your business by automatically generating content ready for immediate human consumption.

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Comprehensive sentiment analysis

Discover advanced sentiment solutions that offer a deeper assessment of language sentiment. Easily customizable machine text readers accurately analyze your documents regardless of how nuanced the language is.

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Featured Natural Language Processing Articles

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From RAG to Riches: A Practical Guide to Building Semantic Search Using Embeddings and the OpenSearch Vector Database

In this article, we delve into the evolution of search technologies, tracing the journey from the conventional keyword-based search methods to the cutting-edge advancements in semantic search. We discuss how semantic search leverages sentence embeddings to comprehend and align with the context and intentions behind user queries, thereby elevating the accuracy and relevance of search outcomes. Through the integration of vector databases such as OpenSearch, we illustrate the development of sophisticated semantic search systems designed to navigate the complexities of modern data sets. This approach not only delivers a more refined search experience but also enhances the precision of results by accurately interpreting the intent of user inquiries, representing a notable leap forward in the progression of search technology.

AI Gone Wrong? The Critical Role of Chatbot Testing and Certification

AI chatbots are transforming customer service by providing 24/7 availability and interactions that resemble human conversation. It's anticipated that by 2025, 80% of customer support will utilize Generative AI to improve the customer experience and increase agent efficiency. However, the swift adoption of this promising technology has faced obstacles, particularly miscommunications that have risked brand reputations. To prevent inaccuracies it's essential to adopt thorough AI testing and certification processes. In this article, learn more about why rigorous testing and certification are critical for the successful integration of AI chatbots in customer service.

Measuring Accuracy and Trustworthiness in Large Language Models for Summarization & Other Text Generation Tasks

Large Language Models (LLMs) are increasingly popular due to their ability to complete a wide range of tasks. However, assessing their output quality remains a challenge, especially for complex tasks where there is no standard metric. Fine-tuning LLMs on large datasets for specific tasks may be a potential solution to improve their efficacy and accuracy. In this article, we explore the potential ways to assess LLM output quality:

UNDERSTANDING HUMAN CONVERSATIONS IN AI

Training machines to understand languages can be a challenge for most data scientists. This episode of “Your AI Injections” starts with the basics of how to start training these machines to understand languages. Listen and learn how AI can be used in everyday business practices.

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Dec 20, 2021

Matt Leibel

Dec 20, 2021

“We talked to 15-20 different companies. We chose to go with Xyonix because they understood our problem better than other firms. Deep is an expert in his occupation. He knows what he's doing and clearly understands this world. ”

Matt Leibel, CTO @ Xometry [more]

Dec 20, 2021

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Recent NLP Projects of Ours

AI Driven Video Summarizer

For an extremely rapidly growing startup, we built an AI system that transforms lengthy, often instructional videos into concise, optimized segments. The system cleanses transcripts, then leverages LLM models we fine tuned using training data meticulously annotated by a combination of other LLMs and our human team at Xyonix. It's adept at extracting key topics, generating summaries, easing navigation, and producing short, impactful videos in various formats. Already in public use and benefiting millions daily, this system is a game-changer for educational and instructional content, making complex information more accessible and engaging.

Video Content Creator

In collaboration with a rapidly growing startup, we've crafted an AI-driven solution for helping users rapidly create high-quality video content by automatically analyzing user generated movie scripts and identifying optimal video assets for inclusion in short videos. Our role extended beyond data science; we engineered and now host a fully scaled system. This platform excels in generating scene text and keywords, leveraging semantic search within a bespoke imagery index, and creating video metadata from video frames. Designed to facilitate the production of engaging videos and scripts for social media and advertising, this service is robust, fully managed, and caters to millions of users daily.

Vaccine Hesitant Persona Mapper

We were asked by Columbia University to help build a map of vaccine hesitancy to assist public health officials in increasing vaccination rates. We built a corpus of millions of social media messages from platforms like Twitter, Reddit and Youtube comments. We are now analyzing this data by manually annotating thousands of training examples using a multi-parent taxonomy and iteratively (active learning driven) training a multi-label machine learning and NLP powered parser. If we are successful, we hope to save lives by convincing the vaccine hesitant to protect themselves and their communities.

Virtual Patient Intake Specialist for Online Health Services, A Case Study

Virtual Intake Specialist

We helped a company build a powerful virtual intake specialist that automatically communicates with patients to route them to the best care for their condition. Our AI system listens to patients and asks them just the right follow up questions, much like a traditional intake nurse might, to help schedule the best care option.

AI Med Spa Assistant

Xyonix teamed up with an early-stage startup to launch an AI iPhone app based assistant to help Med Spa nurse practitioners. The AI technology adeptly categorized facial features, aiding in the assessment of treatments and spotting issues like temporal visual changes, ineffective product batches or injector performance. Integrated with iOS for precise patient driven photo alignment, the system enabled consistent treatment tracking. We played a pivotal role in technology development and strategic product planning; our involvement was key in fusing medical accuracy with technological innovation in product development.

AI Backed Surgery

For a fortune 500 company, our Xyonix built models are in production today constantly analyzing thousands of recent in body surgery videos and reviews across many hundreds or thousands of surgery rooms around the world. Our models watch never ending streams of surgery videos, and read countless reviews. Our models power dashboards that help surgeons improve.

Medical Treatment Author

We worked closely with a company to empower consumers with readily accessible quality health information by building systems that read large volumes of unstructured medical texts using deep NLP relation parsing techniques, and automatically authored millions of web pages. Our work resulted in site traffic growth of 10,000% averaging 6% week over week growth. The site attracted primarily physicians, physician specialists, and other researchers due in large part to the quality of the automatically generated text.

Fan Response Parser

We built a system that helped our client help popular artists like Metallica and Beyonce communicate with their massive fan base by automatically interpreting millions of fan text messages sent to artist’s personal phones. Our parser was capable of accurately recognizing over 70 detailed conversation statements.

Sales Lead Conversation Bot

We worked closely with executives and data scientists of a major automated sales lead generation system to define an AI path forward that enabled their system to not only understand conversations, but to also generate responses for human consumption. We were able to efficiently extend one conversational domain from the recognition of just a handful of response categories, to over 50, all with very high accuracy.

Depression Text Analyzer

We built a system that helps artists like Metallica and Beyonce interpret the results of millions of fan text messages. During our analysis, we found that many fans were expressing depression related thoughts. We honed our AI models to more accurately differentiate between those discussing sad things and those more at risk of self harm. The results help get these fans professional help.