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Mohamed Ben Hamdoune   |     |  Data Sciences

In our last article, we saw applications concerning image data analysis, and in this one, we will discuss one other primary type of data – text. We will explore applications trying to understand how to treat human language – a domain called Natural Language Processing (NLP).

At Zifo, our experts work with different stakeholders on these challenges and to stay competitive, more companies will include NLP models in their solutions. We are here to enable you to stay at the forefront of innovative technologies that are coming out with AI. It is not only about being efficient but also how to be more reliable as our “data resource” is continually growing.

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NLP models are suitable to help your business in many ways. One example is from a very topical COVID-19 situation: NLP usage to improve the patient’s life in hospitals by having a vocal assistant that can help with communications between patient and staff. We can add that the health sector has profound specificities (financial, regulatory, organisational), where the concepts of patients and practitioners replace those of consumers and employees are mostly in need of reliability, and it is also essential to consider the highly confidential nature of health data in that case. It is important to remember for your business that this notion of confidentiality depends on the geography.

Other area, R&D, by definition, is about innovation & speed to market, and this can be supported in part with NLP models applied to large databases. Indeed, we create text data every day, and models are used to identify unnoticed relationships between certain notions, and it is possible thanks to semantic analysis on large volumes of scientific publications.

Other sources of data are summaries of clinical trials or internal research papers, used to identify new biomarkers and phenotypes or to detect relationships of antibiotic resistance.

R&D-driven organisations producing a large mass of textual reports then following a particular terminology use NLP model with these documents to help lessen the time to market of a cure, which is why many laboratories reduce the drafting time, allowing experts to focus on the phase of conclusion and validation of reports.

Simply, whether there is an unstructured text document or structured, there is a path to explore using AI/ML to unearth future development opportunities, unseen relationships, and options to reduce waste by not “repeating the same mistake again”.


We asked a GPT-3 based model, what does it think by giving it only the title on this blog as a topic as a seed.

Here is the answer – entirely derived by the model:

Knowledge and information are not the same thing, yet they are often confused. Knowledge is empirical data that can be proven to be true by observation or experimentation, whereas information is data that may or may not have been verified as true empirically. Information in many fields of study has no set standard for what counts as factually correct knowledge. The only way to prove something people believe is accurate according to this definition of knowledge would be through mutual agreement among a group of people who share the same observations and experiences about their environment.

In regards to Natural Language Processing, it is technology used in computing and Artificial Intelligence research that gives computer systems the ability to understand human speech. It allows computers to recognise spoken words as well as written text input from a user and then translate those words into machine-readable data.

In the field of artificial intelligence, Natural Language Processing is an important part of developing systems that can mimic human thought processes and reasoning. For example, IBM’s Watson system uses natural language processing to understand natural conversational speech as it analyses massive amounts of data from many sources simultaneously. It then produces a potential answer for a question by using statistical analysis on its information.

In business, Natural Language Processing is used in customer service call centers for processing and answering questions from customers. For example, if a customer calls the tech support number of their internet or cable provider to ask when they can expect to have services back up and running following an outage, the computer system will be able to understand what the customer is asking for.

In this way, Natural Language Processing can be used in many different fields of business and technology. It is a useful tool when dealing with large amounts of data that need to be processed quickly and efficiently.

In closing, I hope this response was helpful to you. Thank you for the opportunity to participate in this project.

I am sure you will agree – quite impressive!

It is the original without any changes, to know more, read Philosopher AI – Natural Language Processing for reliability in your business

To find out more about how Zifo can help with AI, ML, Deep Learning, and scientific Data Sciences, please email us at info@zifornd.com