Explore Artificial Intelligence
Julia Rose
Marketing & Design
12. Oktober 2020
More and more companies are investing in AI software, hardware and services, and the market is constantly growing.
In the following, we explain exemplary fields of use with Artificial Intelligence and how they can be leveraged.
Computer Vision, Natural Language Processing and Predictive analytics – brief introduction
While some of the appliances of Artificial Intelligence and Machine learning might seem complicated at first sight, we want to collect some of the use cases of artificial intelligence and its subfields in the business.
Natural Language Processing
What is it?
Natural Language Processing (NLP) is a set of techniques that enable computers to analyze and interpret human language.
NLP – exemplary use cases
- Automatic recognition of entities in texts, such as names, companies, but also names of medications, their doses, and possible side effects and even finding relations between them.
- Summarization of texts, allowing to get only the most important information from the burden of documents
- Automatic notes from spoken language, for reporting purposes but also allowing for advanced analytics and saving time
- Bots and virtual assistants analyzing the content of e-mails and messages written by humans and automating processes like checking order status, finding the right contact person, answering HR questions like remaining vacation or internal procedures.
- Recommendation of similar documents based on their content, to help finding relevant articles or to automate customer service by suggesting solutions based on historical problems.
- Automatic opinion analysis about a product based on reviews posted in the Internet
and many more…
Computer Vision
What is it?
The aim of Computer Vision (or more generally Image Processing) is enabling computers to see, recognize, and analyze the content of pictures and video sequences.
Computer vision – exemplary use cases
- Detection of missing merchandise on a shelf and informing the employees to fill in the missing assortment
- Detection of product damages on the production line, allowing to speed up the process and increase accuracy to assure the highest quality of the products
- Automatic detection of tumors on medical images, to assist doctors to find even smallest malformations and allow for fast diagnosis
- Detection of objects based on satellite images/drone movies – to detect dangers like fires, do more effective space planning or allow for control of places hardly accessible for a human
- Gesture recognition – create and use interaction forms for example when working with smartphones or mixed reality glasses
Machine Learning and Predictive Analytics
What is it?
ML incorporates methods that allow the computers to learn from data and find relations and patterns hidden within. Predictive analytics in particular concentrates on making predictions of future events based on historical data.
Where can it be used?
- Predictive maintenance – detecting possible future failures of machines based on sensor readings like vibration, acceleration, rotation, etc.
- Demand/prices/consumption prediction based on historical data and other variables
- Precise customer segmentation, allowing for sending relevant marketing and sales messages
- Product/service recommendations based on user behavior
- Fraud detection – detect suspicious transactions and behaviors to protect your business and data safety.
