20 min readSep 16, 2023

“Transforming Titans: How NLP Elevates MNCs into 21st Century Powerhouses 🚀

“Unlocking Success: How NLP Propels MNCs to Excellence”

In an era defined by digital transformation, Multi-National Companies (MNCs) are finding an invaluable ally in Natural Language Processing (NLP). This dynamic pairing is not only enhancing products and services but is also elevating MNCs to the summit of success in the 21st century. In this article, we’ll dive deep into the collaboration between NLP and MNCs, uncovering how NLP is redefining their business landscape and making them top-notch companies of this generation.

How NLP Benefits MNCs?

Natural language processing (NLP) is a branch of artificial intelligence (AI) that enables machines to process and understand human language. NLP has many applications in various domains, such as customer service, information extraction, sentiment analysis, text summarization, and more. NLP can help multi-national companies (MNCs) to improve their products, services, and operations by analyzing large amounts of data, streamlining processes, enhancing customer satisfaction, and gaining insights. In this article, we will explore some of the benefits of NLP for MNCs and how they use NLP to gain a competitive edge in the global market.

Highlighting benefits of NLP for MNCs are:

NLP can help MNCs to perform large-scale analysis on various kinds of data in seconds or minutes, that would take days or weeks of manual analysis.
NLP can help MNCs to get a more objective and accurate analysis by using algorithms and models that can be trained to the language and criteria of the MNCs.
NLP can help MNCs to streamline processes and reduce costs by automating routine tasks and increasing efficiency and productivity.
NLP can help MNCs to improve customer satisfaction by providing personalized and timely solutions to their problems and needs in natural language.
NLP can help MNCs to better understand their market trends, opportunities, and challenges by analyzing various sources of data, such as competitor information, industry reports, market research, and more.
NLP can help MNCs to empower their employees by providing them with tools and resources that can enhance their skills, knowledge, and performance.
NLP can help MNCs to gain real, actionable insights from their data that can help them to improve their products, services, and operations.

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, to get started.

Natural language processing applications have moved beyond basic translators and speech-to-text 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.

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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.

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

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.

IBM

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.

Amazon

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.

Lemonade

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.

Google

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 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.

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.

NLP enhances their products, making them top-notch companies of this generation. 🌟

AI Powered Google Translate Can Translate Languages It’s Never Trained On

Google’s neural network learns to translate languages that it has never learned.

The legendary Google Translate will now produce more natural and better translation between languages, thereby reducing the gap between human and machine translators and enhancing the learning capabilities of Google Translates neural network.

The company is now using a new technology called Neural Machine Translation (NMT), which aims to make computer-generated translations more parallel to those done by humans and to power its translations in seven new languages. The update should make translations in those languages much more accurate and easier to understand, says Google.

“At a high level, the Neural system translates whole sentences at a time, rather than just piece by piece,” said Barak Turovsky, product lead at Google Translate during a press event at Google’s San Francisco office on Tuesday. “It uses this broader context to help it figure out the most relevant translation, which it then rearranges and adjusts to be more like a human speaking with proper grammar.”

Back in September, Google had announced that it would be switching from Phrase-Based Machine Translation (PBMT) to Google Neural Machine Translation (GNMT) for handling translations between Chinese and English. Built on a neural network, the legendary Google Translate will now produce more natural and better translation between languages.

5 Indian Natural Language Generation Startups Are Revolutionizing the Sector

vPhrase:

This Mumbai bases analytics startup was founded by Neerav Parekh in 2015 and are bringing NLG to make reports more insightful. Their core AI-based platform Phrasor analyses data derive insights and communicates these insights in multiple Indian languages. Enterprises are using it to personalize and add deep insights to the reports they send to customers as well as employees. They are demystifying the visualization landscape by generating smart insights alongside the text that makes the job of analyzing easier. Phrasor is currently working with industries such as banks, brokerage firms, healthcare, CPG companies and others. The entire product is built on Python and the team took the NLTK language toolkit for building the platform. This is a one-of-a-kind startup in the pure NLG domain in India.

Stride:

Stride.ai pioneers in understanding customer need by performing AI-based text analytics. The underlying technology is natural language generation where Stride’s TEXSIE platform provides advanced analytics using some of its very own proprietary algorithms to provide sentiment analysis, name matching, language detection and translation, categorization of documents and more. The algorithms power their products and are available as developer APIs. Their platform mines and analyses the existing data to provide a meaningful inference that would businesses improve their customer experience. By using natural language processing ability, Stride provides graphical patterns of the unstructured data in a structured format to easily understand customer’s behavior. It is currently being leveraged by banks and financial institutions.

Recommenderlabs:

This startup founded in 2016 uses sophisticated machine learning and customizable algorithms to help users in the decision-making process. It does so by generating meaningful recommendations that are tailored to user’s preferences, aptitudes and skills. The core technology is artificial intelligence, NLP, NLG, that facilitates the overall working of the services offered by the company. Their conversational AI uses the best of NLP techniques to address specific customer queries and take the conversation ahead. The startup is using the power of machine learning in the best way possible in their applications which further help through filtering data and playing with data slicing to offer powerful recommendations.

Contentop:

This startup founded in 2015 is building a next-gen engine or content generation using a wide range of AI approaches such as Natural Language Generation, ML and data mining. The product offering by the company, the intelligent data miner can help enterprises understand and extract meaningful information from raw text using NLG. It facilitates SAAS based automated AI writing software that requires no complicated setup and download. It basically is an article-writing app which uses NLG to bring down the writing time by eliminating the time wasted.

Senseforth.ai:

This 2012 founded startup offers a humanlike conversation platform powered by AI and can address queries quite efficiently. The product by the startup is called Aware, which is essentially a neocortex that mimics human cognitive abilities and performs tasks such as reading, comprehending, interpreting and conversing. The entire process makes extensive use of NLP and NLG technologies that pose the feature of continuous learning and evolving based on guided learning principles. These characteristics make it perfect for catching customer emotion and delivering better results each time. It is currently helping companies in banking, healthcare, telecom, e-commerce, travel and others to get them the best of customer experience.

AI powered NLG software lets data convey compelling stories that are self-created!

Big data characterized by its V’s, namely volume, variety, velocity, and veracity has led to an information overflow. Massive amounts of data are accumulated from organizations and system landscapes. However, manually documenting this information is often a tedious task involving a lot of time and enterprise resources. This is the reason why companies are shifting to technology to solve their data woes. This means increased dependence on Artificial Intelligence (AI)-based solutions, which can reduce manual errors and time taken by human interference. No wonder enterprises are shifting their gaze to NLG a subfield of AI, to convert their data to produce texts, known as narratives. The implementation of NLG software can help enterprises manage and utilize humongous volumes of data. For instance, allowing service providers to send personalized messages rather than sensing generic text to thousands of customers. Analytics Insight compiles the Top 10 Natural Language Generation Companies-

1. MS Azure

The Azure Text to Speech API helps to build apps and services that speak naturally. Users can choose from more than 110 voices and over 45 languages and variants to differentiate their brand with a customized voice. With MS Azure users can access voices with different speaking styles and emotional tones to fit their use case in their preferred programming language. • USP/ Offerings — Lifelike speech, Customisable voices, Fine-grained audio controls, Flexible deployment.

2. IBM Watson

IBM Watson Text-to-Speech lets users generate human-like audio from written text. Watson text-to-speech is a great way to improve the customer experience and engagement by letting the algorithms interact with users in multiple languages and tones. With Watson’s text-to-speech users can develop interactive products for a varied number of industries for seamless call center interaction, hands-free communication, provide audio options to avoid distracted driving, or automate customer service interactions to increase efficiencies. • USP/ Offerings — Offers customised pronunciation, Detects different dialects.

3. Amazon Polly

Amazon Polly offers Neural Text-to-Speech (NTTS) voices which help to deliver advanced improvements in speech quality through a new machine learning approach. Polly’s Text-to-Speech (TTS) service uses advanced deep learning technologies to synthesize natural sounding human speech. With dozens of lifelike voices across a broad set of languages, users can build speech-enabled applications that work in many different countries. • USP/ Offerings — Natural sounding voices, Real-time streaming, pay-as-you-go pricing model, Customize & control speech output.

4. Wordsmith

Wordsmith is a self-service platform offering complete narrative customization, real-time content updates, and a powerful API for flexible publishing. From BI dashboard analysis and client communications to video game narrative and fantasy football recaps, Wordsmith delivers enterprise-ready NLG solutions. The company has partnered with Tableau. Tibco, Power BI to drive the best NLG services. • USP/ Offerings — Real-time analysis, fully customizable, easy scalability and publish anywhere feature.

5. Quill

Narrative Science’s NLG technology delivers information from data that is relevant, its NLG platform, Quill communicates the way humans do by analyzing the data to identify what is interesting and important and then automatically transforming those insights into relevant, intuitive, and timely information generating insightful narratives at a scale. Quill allows users to automatically create data-driven stories at scale over Tableau, Power BI, Qlik data visualization tools. • USP/ Offerings — Delivers data stories in any dashboard or domain, transforms data into stories, and embeds them directly into dashboards.

6. AX Semantics

AX Semantics is a self-service Natural Language Generation (NLG) software with integrated e-learning modules that allow customers to start self-automating text within 48 hours. AX Semantics works with some of the world’s best-known brands on content generation, including Porsche, Deloitte, Mytheresa, and Nivea, amongst others. • USP/ Offerings — Multi-lingual content, Gartner representative vendor

7. Readspeaker

ReadSpeaker gives users text-to-speech capabilities like reading selected sections or entire pages, writing assistance tools enabling brands, companies, and organizations to deliver enhanced end-user experience while minimizing costs. It offers a range of powerful text-to-speech solutions for instantly deploying lifelike, tailored voice interaction in any environment. Readspeaker is available in British and Australian English, Dutch, French German, Italian, Spanish and Swedish languages. • USP/ Offerings — 10,000+ global customers, 200+ voices in 50+ languages available in its SaaS solutions, 20+ years of experience.

8. Arria

Arria NLG platform develops NLG software technologies that transform structured data into natural language. Through data analysis, knowledge automation, language generation, and tailored information delivery, Arria software replicate the human process of expertly analyzing and communicating data insights. Arria platform dynamically turns data into written or spoken narrative at machine speed and on a massive scale by giving data the power of language. • USP/ Offerings- Arria NLG Studio, Arria for BI, Arria Answers, Arria Connect, Arria for RPA, Arria for Excel

9.Yseop

Yseop is a pioneer in natural language text generation (NLG) technology offering solutions that utilize artificial intelligence (AI) to make sense of complex data sets, generating high-quality written narratives accurately, quickly, and at scale. With specialist tools for complex financial and medical report writing, as well as sales automation, Yseop is trusted by leading global businesses to help automate and industrialize processes, empowering workers, and driving digital transformation. Yseop develops a suite of solutions that translate data into a written narrative in English, French, German, and Spanish languages. • USP/ Offerings- Augmented Financial Analyst, Augmented Medical Writer, Smart Personal Advisor

10. textengine.io

textengine.io is an innovative SaaS solution platform for automated text generation that brings artificial intelligence to content marketing strategy, suited for multi-size and in any industry.textengine.io uses structured data to create custom stories on any aspect of the company offering. Textengine.io self-service platform opens up a whole range of opportunities for implementing custom NLG products and enables organizations to integrate automated content stories into their day-to-day business themselves. • USP/ Offerings- Intelligent linguistic analysis, intuitive interface, automatic translation function, limitless scalability, personalized onboarding support, creation of SEO texts.

NLP BELIEFS OF EXCELLENCE

The power of Neuro Linguistic Programming beliefs can be best understood by imbibing the beliefs of excellence. These beliefs are very practical and easy to adapt. They are also called the NLP presuppositions or the principles on which our mind and brain works. The essence of these beliefs is that ‘people work perfectly’. It also means the programmers, which have conditioned our brains work perfectly. That is the reason 95% of our behavior is patterned and hence our behavior and attitude is predictable.

The NLP beliefs of excellence provide a different perspective on altering our limiting behavior patterns.
Each person is unique (The map is not the territory)
There is no right or wrong in life. It is essentially the outcome of the way our thought process interprets the event. It is important to understand that we respond to our ‘mental maps’ or our interpretations of our world to arrive at a conclusion. These conclusions are different for different people. The difference is essentially a reflection of our past experiences and thus the way we interpret the present situation. Through new experiences we keep updating our old mental maps which is why, the more problems we face in life we have a better chance of succeeding.
Each experience has a structure.
This is also interpreted as, ‘knowledge, thought, memory and imagination are a result of combination and sequence of the way we filter and store information’. Our thoughts and memories have a definite pattern or a structure and that is what decides our emotional state. Thus, whenever we face a situation, we trigger these old structures resulting in a specific behavior or an action. Changing the way we think, can change the experience and thus the resulting emotion and action. This is ideal for generating a new behavior pattern. A typical example would be few people would like to take up challenging assignments because the thought patterns are programmed for new experience and learning. While the others may prefer to do things, they are comfortable with because they are programmed for doing the jobs they know over and over again.
If one person can do something, then anyone can do it
This belief is the base of programming or modeling in NLP. This belief talks of understanding the mental map of the achievers and eliciting them to model excellence. Thus, everyone is capable of delivering excellence. It is just a question of whether we have programmed ourselves for excellence.
There is a solution to every problem.
If you repeat the same pattern of thought and action, it will always result in similar outcomes. If the outcome has to be different then you need to do things differently. The thinking pattern needs to be conditioned to look for a solutions approach. A problem persists as long as you treat it as a problem. A solution oriented or a result-oriented mind always looks for solution.
The mind and body are the parts of the same system.
NLP advocates the principle of congruence very strongly. It means that the values, beliefs, thinking patterns, capabilities and behavior should not be in conflict. Our thoughts instantly affect our muscle tension, feelings, etc. which in turn have an impact on our thoughts again. Thus, by changing any of these you can effect a change in the entire system. That is why when we are in a difficulty our facial expressions say it all.
You cannot not communicate.
We are always communicating through our language and subtle actions. Our internal thoughts also keep communicating with us, which is reflected through our physiology to others. At all intervals of time there exists a verbal or nonverbal communication.
The meaning of communication is the effect.
The intention behind the communication is not always its effect. This belief can go a long way in interpersonal relationships. Our communication is received as per the mental maps of the listener. Noticing how the communication is being received allows us to make adjustments. Linguistics gives us specific patterns of communication, which enhances the quality of communication.
Behind every behavior is a positive intention
This is the best belief to carry because it sets off a very positive feeling. Every behavior has a positive intention somewhere or the other. Even if the intention is not good for us it is good for someone else. This belief is best understood with respect to the next belief.
People are always making the best choice(s) available to them.
This takes care of the cliché “I did not expect this from you.” Everyone has a unique personal history, which shapes experiences and thoughts, which result in the effect. Thus, different people have different value of hierarchies and beliefs. The choices they make are an outcome of these combinations. Thus, the choice they make is the best possible available at that point in time to them.
There is no failure, only learning.
Fear of failure is the most immobilizing emotion. This is an empowering and enabling belief to carry. There is no success or failure but learning. Learning can result in an experience and an improvement in subsequent actions. Fear of failure is the fear of unknown. Success is an outcome of facing the fear of unknown. Thus every successful person treads into the zone of fear of the unknown and keeps learning for subsequent challenges.
People have all the resources they need.
We are born with all the sensations, feelings, mental images inner voices based on all the five senses, which are the building blocks for excellence. Over the years we get conditioned with certain set of skills we are most comfortable with. The repeated application of these skills, result in further conditioning. This conditioned pattern of behavior thus does not create the need to develop additional skills or patterns which may be better. It is therefore important to note that we can learn and develop all the necessary skills. It is just a question of effort.

Our brain is like a computer, the only difference being we are not born with a ‘user manual’. Discovery of NLP provides this necessary manual for the software to run the brain the way we want.

This is the first step in NLP towards enriching your experiences and lives. These insights clearly bring out a fact that NLP provides a new approach to the way we process our thoughts and thus the resulting action i.e. the behaviour. Once NLP as a skill is available, one can start looking at the limiting patterns and change them by learning the skill of programming.

THANKYOU!