Quantum Computing and Machine Learning are two big emerging technologies of the 21st Century. While these two technologies are independent, they can leverage one another. Especially when it comes to Quantum computing helping to advance machine learning. Machine learning is a very computationally intensive process and therefore the more powerful the machine that you use in developing the algorithms the better. One area that quantum computing is expected to accelerate greatly is natural language processing.
What is Natural Language Processing?
Natural Language Processing (NLP) is a branch of Artificial Intelligence that focuses on giving machines the ability to understand text and spoken words in the same way that humans can. A relatively primitive example of this is SIRI, which can listen to human words and perform actions based on those words. A more advanced version of this would be AI that is capable of having full-on conversations with a human, understanding humor, sarcasm, and other more complex aspects of the human language. Here are some of the expected use cases of NLP:
Healthcare: NLP is expected to help in the recognition and prediction of diseases based on reading electronic health records and speaking to patients. This use case is currently being used to help with the diagnosis of cardiovascular diseases, depression, and even schizophrenia. A working example of this is Amazon’s Comprehend Medical service, which uses NLP to extract disease conditions, medications, and treatment outcomes from patient notes, clinical trial reports, and other electronic health records.
Fake News Detection: The NLP group at MIT created a system to determine if a source is accurate or politically biased, in an effort to identify if a news source can be trusted or not. As shown in our deep fake blog post, the ability to create convincing fake news has increased greatly and it is constantly used to manipulate public opinion.
Sentiment Analysis: This is the contextual mining of text that identifies and extracts subjective information in the source material. The goal of this is to understand the social sentiment of a business’s brand, product, or service through monitoring online conversations, namely social media.
Talent Recruitment: NLP is used in both the search and selection process of recruitment. It can even be used to help identify good candidates that have not yet become active on the job market based on online conversations or other habits.
Source @ towards data science
Quantum computing is expected to greatly increase the development of natural language processing by increasing the rate at which we can develop good AI algorithms. Much of the delay in the refinement of AI can be attributed to the limits that we have on our current computing power. Quantum computing would greatly increase our current capabilities and allow us to innovate at a much faster rate.
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