Combining AI and robotics can lead to better outcomes in many industries related to technology. Robotic automation can improve accuracy, reduce costs and maximize efficiency, regardless of whether it’s a harvesting robotics robot that picks apples at their peak ripeness or a surgical robot capable of performing key imaging and diagnostics during surgery.
Companies that use AI to power robotics rely on precise, customized datasets to train their robots to perform delicate tasks, often at the same level as humans. And that’s when UBIAI’s text annotation tool comes into play.
Although chatbots and virtual assistants have been around for a while, they are not new. They are limited in their ability to answer questions or manage tasks.
All businesses need to increase their ability to respond to customer requests. It is essential that businesses are able to respond to customer requests at all times. Chatbots and virtual assistants are well-trained and can handle basic customer queries, reducing the number of requests that staff must manage.
UBIAI is an AI-driven solution. It helps training chatbots to answer queries and schedule appointments 24 hours a day. It’s solutions aim to expand the types of questions chatbots are able to answer and the tasks they can handle before they need to refer the inquiry to a human.
We have been working with companies to create products and innovate customer experiences. UBIAI’s process data for NLP models solve problems in various industries, including technology.
Here’s how it helps:
Text-tagging refers to adding tags or annotations in text format to unstructured data. It is a basic level for preparing data to be used in NLP applications. While you can automate some of the work with a tool, you might need someone who is involved in quality control.
For example, one UBIAI client has built an AI platform that predicts the behavior of scientific material. Our tool transcribes data for another client who is creating a predictive engine to avoid fraud and misuse of expense funds.
Text mapping standardizes data based on its meaning or context. While some of this can be automated using a tool, it is still challenging to understand the meaning of the text and will require a human being to assist. UBIAI also assists in annotating contracts that are based on category instructions.
Semantic analysis requires the extraction of data. These tasks are more difficult to automate using the technology today.
UBIAI allows companies to transform unstructured or messy data into structured data for NLP and other data analysis techniques.
We use computational techniques to combine the classification, mapping, and tagging work of our contributors.
Then, a data quality framework is created around this process to ensure that final datasets are consistent.
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