NLP
Chat-GPT, Large Language Models andOpenAI, they are hot topics and all part of Natural Language Processing (NLP). How do you purposefully use these tools to make your organization smarter, more efficient and more customer-friendly? After all, there is a lot of value hidden in your textual data. How do you extract it?
What is NLP?
NLP helps computers understand human communication. These language models can analyze and process large amounts of data. This is interesting as it allows you to gain valuable insights, start automating tasks and improve user experiences. From chatbots and virtual assistants to sentiment analysis and text classification, NLP plays a crucial role in how we interact with technology.
The best of both worlds
Putting the model live
Keeping track of model versions
Compare + monitor metrics
Why do you make use of NLP techniques?
Simple.
NLP combines the best of both worlds.
On the one hand, you have great language models such as Chat-GPT ( LLMs), which generate lyrics that feel very natural.
On the other hand, there are the traditional NLP models that excel at accurately executing specific taken.
Door this together, you unlock a world of possibilities!
NLP examples
We have MLOps solutions that solve these problems with a standardized approach:
- Intelligent document processing:
This method converts text into a usable format and replaces manual processing.
AI extracts the essential information, such as date and price, and creates a clear dataset.
This can be integrated into a backend system.
Perfect for organizations with a lot of paperwork.
Consider invoice processing, contract analysis or, for example, reviewing medical records; - Conversational AI:
Does your organization have many files that are difficult to search?
Our solution combines Chat-GPT with a smart search engine linked to your resources.
Our AI extracts the information you need.
Think virtual assistant, document Q&A and chatbots; - Text analysis:
AI discovers patterns and trends in large amounts of text.
It organizes feedback, identifies sentiment in reviews and can refine search results.
Use AI for text analysis and make informed decisions.
Consider customer feedback, market research and search engines; - Content generation:
AI generates texts in a consistent style.
With examples and human input, it can create content in your organization’s tone of voice!
Think tenders, social media and templates.
Technical details
Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Medium length section heading goes here
Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Suspendisse varius enim in eros elementum tristique.
Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat.
Medium length section heading goes here
Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Suspendisse varius enim in eros elementum tristique.
Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat.
Medium length section heading goes here
Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Suspendisse varius enim in eros elementum tristique.
Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat.
Medium length section heading goes here
Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Suspendisse varius enim in eros elementum tristique.
Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat.
Blogs about NLP,
Read the latest blogs on data strategy, data engineering and data science & AI here.
What are the possibilities of GenAI, Large Language Models (LLMs) for the internal organization? How to implement an LLM effectively for organizations….
Large language models (LLMs) like ChatGPT are popular. Not only for personal use, but also within organizations. Searching business documents for specific…
Since the rise of ChatGPT no one can ignore it anymore: ‘Large Language Models‘* (LLMs) are here to stay‘. Several technology companies…
What do you want to do with data?
