What Companies Are Fueling The Progress In Natural Language Processing? Moving This Branch Of AI Past Translators And Speech-To-Text

Key takeaways

  • Natural language processing (NLP) is a subset of artificial intelligence that
  • uses linguistics and machine learning models to allow computers to process human language. As time goes on, these machines are getting better with sentiment analysis and intent classification tools
  • We experience the power of NLP in our daily lives, even if we don’t realize it. We see NLP in action when we search for something online, use predictive text, interact with chatbots or ask our smart assistant in the living room to change the song
  • Revolutionary tools like ChatGPT and DALL-E 2 are setting new standards for the capabilities of NLP. These tools use NLP to store information and provide detailed responses to inputs

Chatbots have exploded in popularity in recent months, and there’s a growing buzz surrounding the field of artificial intelligence and its various subsets. Natural language processing (NLP) is the subset of artificial intelligence (AI) that uses machine learning technology to allow computers to comprehend human language.

AI has many applications, including everything from self-driving cars to AI-driven investing. If you’re curious about what AI can do for your portfolio, download the Q.ai app to get started.

Natural language processing applications have moved beyond basic translators and speech-to-text with the emergence of ChatGPT and other powerful tools. We will look at this branch of AI and the companies fueling the recent progress in this area.

What’s natural language processing all about?

Natural language processing (NLP) is a subset of artificial intelligence (AI) that uses linguistics, machine learning, deep learning and coding to make human language comprehensible for machines. Natural language processing is a computer process enabling machines to understand and respond to text or voice inputs. The goal is for the machine to respond with text or voice as a human would.

The long-term objective of NLP is to help computers understand sentiment and intent so that we can move beyond basic language translators. This subset of AI focuses on interactive voice responses, text analytics, speech analytics and pattern and image recognition. One of the most popular uses right now is the text analytics segment since companies globally use this to improve customer service by analyzing consumer inputs.

The potential for NLP is formidable. According to Fortune Business Insights, the global market size for natural language processing could reach $161.81 billion by 2029. Market research conducted by IBM in 2021 showed that about half of businesses were utilizing NLP applications, many of which were in customer service.

How are businesses using NLP to improve operations?

The primary benefit of NLP solutions for businesses is to use automation to cut costs and improve business operations to maximize productivity and profitability. Here are a few ways that NLP is being utilized right now by businesses globally:

  • Redacting sensitive data. Industries such as insurance, legal and healthcare use NLP technology to redact personal information and protect sensitive data instead of manually going through documents.
  • Customer service. Not only is NLP technology used to offer customer service chatbots that sound more human-like, but companies then have this data extracted and analyzed to improve the customer experience.
  • Business analytics. Companies use NLP solutions to analyze sentiment and gather actionable insights from customer feedback.

What are examples of natural language processing in our daily lives?

You may be using NLP services daily without even noticing it. We enjoy more and more of these technological benefits as they advance. Here are some common examples of NLP:

  • Spam email filters: These filters determine what kind of messages reach your inbox based on results from text classification tools.
  • Smart assistants: Amazon’s Alexa and Apple’s Siri are perfect examples of machines processing natural human language. These smart assistants determine patterns in voice recognition to provide a helpful response based on context.
  • Search engines: When you search for something, the NLP technology offers suggestions to complete your query while using sentiment analysis to determine the results the search engine produces.
  • Predictive text: While we’ve likely become accustomed to this feature, the predictive text has improved drastically. It’s used by applications like Grammarly and Gmail’s Smart Compose, which even finishes your sentences for you.
  • Customer service chatbots: Whenever you speak to a customer service chatbot through a website, you see the power of NLP. These services are getting better with time.

We also can’t ignore the role of AI and NLP in everyday services like streaming platforms and e-commerce websites (Amazon), where it feels like our results are customized by someone who knows us.

What companies are fueling the progress in natural language processing?

While almost every business has to use some form of NLP and AI in its operations, some companies are fueling the recent progress in these technologies. Here are five companies in this space to keep an eye on.


Microsoft has been making headlines lately since the company reportedly invested $10 billion in OpenAI, the startup behind DALL-E 2 and ChatGPT. These two tools alone have changed the entire landscape of AI and NLP innovations as the improvements bring this technology to the general public in new, exciting ways.

Microsoft Azure is the exclusive cloud provider for ChatGPT, and this platform also offers many services related to NLP. Some services include sentiment analysis, text classification, text summarization and entailment services.


While IBM has generally been at the forefront of AI advancements, the company also offers specific NLP services. IBM allows you to build applications and solutions that use NLP to improve business operations.

One of the revenue streams for the company is the IBM Watson Natural Language Understanding service which uses deep learning to derive meaning from unstructured text data. On the Watson website, IBM touts that users have seen a 383% ROI over three years and that companies can increase productivity by 50% by reducing their time on information-gathering tasks.


The significance of AI and NLP is felt at almost every level of Amazon’s business. You may have used the Alexa device to put on your favorite song or found the perfect product on the e-commerce platform based on a recommendation. These are AI and NLP in action.

Amazon also offers Amazon Web Services (AWS) for cloud storage so businesses can complete their digital transformations. They also have Amazon Comprehend, an NLP service that uses machine learning to determine text’s significance. The Comprehend service also offers sentiment analysis and custom segmentation so customers can add NLP to their apps.


When discussing AI, you can’t forget about the first insurance company fully powered by AI. Lemonade utilized AI and NLP to handle everything about the insurance process, from enrolling customers in a policy to filing an insurance claim. The chatbot, Maya, can communicate with humans in a manner that makes it feel like you’re dealing with a human on the other end.


Even though Alphabet, the parent company of Google, recently revealed that it would be cutting 12,000 employees worldwide, they’re also planning on launching 20 new products. Google has already offered a small sample group an exclusive look at a tool that will eventually be a competitor to ChatGPT, known as Bard. This chatbot is powered by LaMDA, which stands for Language Model for Dialogue Applications. Another example of Google’s innovation is sharing details of a new AI-powered tool to create music from a text prompt.

The biggest issue for Google is that they want to offer an AI-powered chatbot that’s safe, tackles misinformation, and shares factually accurate information. Google has been investing heavily in AI, and it’s no secret that management wants to bring the company back to the forefront of this field. You can see Google utilizing NLP technology in every aspect of its business, including spam filters, predictive text when writing emails, search engines and translation tools.

How can you invest in NLP and AI?

If you’re a proponent of machine learning, there are many different ways to invest in AI and related technologies. There aren’t companies that only focus on AI in the same way that Tesla focuses on EVs or Nike focuses on athletic wear because every successful business relies on some form of AI. You can, however, invest in major tech companies since they’re becoming increasingly invested in AI. With Amazon relying on AI on everything from the Alexa device to powering the warehouses, this is one company that’s all in.

OpenAI is projected to generate $1 billion in revenue in 2024. While you can’t invest directly in OpenAI since they’re a startup, you can invest in Microsoft or Nvidia. Microsoft’s Azure will be the exclusive cloud provider for the startup, and most AI-based tools will rely on Nvidia for processing capabilities. In recent weeks, shares of Nvidia have shot up as the stock has been a favorite of investors looking to capitalize on this field.

You don’t have to look any further if you want to see the capabilities of AI in investing. Q.ai uses AI to offer investment options for those who don’t want to be tracking the stock market daily. The good news is that Q.ai also takes the guesswork out of investing if you want a hands-off approach. Check out the Emerging Tech Kit if you’re a proponent of innovative technology.

The bottom line

Natural language processing and artificial intelligence are changing how businesses operate and impacting our daily lives. Significant advancements will continue with NLP using computational linguistics and machine learning to help machines process human language. As businesses worldwide continue to take advantage of NLP technology, the expectation is that they will improve productivity and profitability.

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Source: https://www.forbes.com/sites/qai/2023/02/06/what-companies-are-fueling-the-progress-in-natural-language-processing-moving-this-branch-of-ai-past-translators-and-speech-to-text/