NLP 2.0 and NLP 3.0 – The Evolution of Natural Language Processing – Distinguished from NLP 1.0

Tags: ai, nlp, nlp 2.0

Summary: This article will introduce and differentiate the three stages of development of Natural Language Processing (NLP): NLP 1.0, NLP 2.0, and NLP 3.0. We will explore the capabilities, limitations, and potential of each stage, as well as the groundbreaking technologies that can make NLP 2.0 and 3.0 a reality.

NLP 1.0: The Era of Intelligent Chatbots

Currently, we are living in the era of NLP 1.0. You can see this in the explosion of chatbot applications like OpenAI’s ChatGPT, Google Gemini, and so on in 2023-2024. These chatbots are capable of conversing with humans intelligently and logically, even surpassing human capabilities in data-related and basic analytical tasks.

Example: ChatGPT can generate text on various topics, answer complex questions, and even compose poetry, music, and scripts.

However, NLP 1.0 still has limitations:

• Lack of Creativity: NLP 1.0 primarily relies on pre-trained data. It cannot yet reason independently or generate new ideas. For example, if you ask ChatGPT to write a short story about a cat, it will rely on the cat stories it has learned to generate the story, but it won’t be able to come up with a completely new plot.
• Inability to Analyze Emotions: Current chatbots cannot understand and analyze human emotions. This makes communication between chatbots and users feel unnatural and lacking in empathy. For example, if you tell ChatGPT you’re feeling sad, it might give generic responses like “Try to stay strong!” without understanding why you’re sad or knowing how to comfort you.
• Lack of In-Depth Analysis: NLP 1.0 often struggles with analyzing complex contexts or specialized issues. For instance, if you ask ChatGPT to explain a complex scientific concept, it might only provide basic definitions without being able to explain it in-depth.
• Limited Understanding of Specific Contexts: Chatbots can understand general language, but they can’t yet grasp specific contexts, unique situations, specific industries, or the unique ways of speaking of individuals, groups, or regions. For example, if you tell ChatGPT a sentence in a local dialect, it might not understand its meaning.

NLP 2.0: A Breakthrough with Emotion Analysis Capabilities

1. What is NLP 2.0? – Emotion Analysis Capabilities

NLP 2.0 promises to overcome the limitations of NLP 1.0, particularly in terms of emotion analysis.

In essence, NLP 2.0 will have the ability to analyze emotions.

When NLP applications can understand human emotions, they will become more intelligent, approachable, have a better understanding of context, and be able to meet user needs more effectively.

Example: An NLP 2.0 chatbot could detect if a user is feeling sad, angry, or happy and adjust its communication accordingly. For example, if you tell the chatbot you are sad, it might offer empathetic responses like “I understand how you feel. What’s making you sad?”, or it could suggest an upbeat song to help you feel better.

2. Table Differentiating NLP 1.0 and NLP 2.0

Feature	NLP 1.0	NLP 2.0
Emotion Analysis	Not Available	Available
Creativity	Limited	Advanced
Context Analysis	Limited	Advanced
Understanding Specific Contexts	Limited	Advanced

3. Conditions for Triggering NLP 2.0

Integration of Emotion Analysis Capabilities: The condition for triggering NLP 2.0 is when one of the leading NLP companies like OpenAI (ChatGPT) or Google integrates emotion analysis capabilities into their chatbots. At that point, we can officially say that the era of NLP 2.0 has arrived. We can proudly say that humanity has entered the NLP 2.0 era.

4. Benefits of NLP 2.0

• Understanding Human Emotions: NLP 2.0 has the ability to recognize and analyze emotional expressions in human language.
• Improved Human-Computer Interaction: The ability to analyze emotions helps chatbots communicate naturally, empathetically, and in a way that aligns with user moods.
• Empathy for Humans: NLP 2.0 allows chatbots to show empathy, understanding, and emotional sharing with users.
• Psychological Therapy: NLP 2.0 chatbots have the potential to be used as tools to support psychological therapy, helping users relieve stress, share their thoughts, and receive appropriate advice.
• Encouragement of Good Actions: NLP 2.0 can be used to motivate, encourage, and support users in taking positive actions that benefit themselves and their communities.
• Education for Children: NLP 2.0 can be used to create educational games and interactive stories that help children learn effectively and enjoyably.
• Analyzing Criminal Motives: NLP 2.0 can help analyze the language and behavior of criminals to identify their motives and goals, assisting in crime investigation and prevention.
• Creating Humanistic Literary and Comic Works: NLP 2.0 can be used to create stories with humanistic content, rich emotions, and authentic reflections of life and humanity.
• Reviewing Works: NLP 2.0 can be used to review, evaluate, and analyze literary and artistic works, from literature to paintings, manga, and manhwa, based on criteria for content, art, and social significance.
• Analyzing User Emotions After Marketing Campaigns: NLP 2.0 can be applied to analyze user emotions after marketing campaigns, allowing businesses to assess the effectiveness of the campaign and adjust strategies accordingly.
• Analyzing Emotions of Communities and Social Media Channels: NLP 2.0 can analyze user emotions on social media channels like Facebook, Twitter (X), etc., enabling businesses to better understand the psychology and attitudes of customers toward products, services, or social issues. This is known as sentiment analysis in marketing, but NLP 2.0 incorporates natural language understanding for more accurate analysis.

5. The State of Emotion Analysis Technology

There has been significant research on emotion analysis. Currently, NLP applications cannot achieve this, but within the next 10-20 years, it will be possible.

Researchers and developers are working hard to build emotion analysis capabilities for NLP. It’s likely that emotion analysis in NLP 2.0 will be integrated with facial emotion analysis.

6. Weaknesses of NLP 2.0 – Lack of Real-World Information Connection

While NLP 2.0 chatbots and NLP are significantly more intelligent than those in NLP 1.0, they still lack the ability to connect to real-world information and events. NLP 2.0 cannot collect and process information about real-world events or interactions between people.

NLP 3.0: Connecting with the Real World

1. What is NLP 3.0?

As mentioned above, NLP 2.0 has the weakness of not being able to connect with real-world information.

However, according to Click Digital, the next stage, NLP 3.0, will overcome this issue. NLP 3.0 will combine with the Internet of Things (IoT) technology to collect information, data, and events occurring in the real world. This data will be quickly trained, allowing chatbot applications to answer questions about real-world events.

Example: An NLP 3.0 chatbot could access data from IoT devices like security cameras, weather sensors, and even wearable devices to provide up-to-date information on ongoing events. For instance, if you ask the chatbot about traffic conditions, it could use data from traffic sensors to give you the most accurate and current information.

2. Conditions for NLP 3.0 Formation

• IoT’s Ability to Connect Real-World Data and Train Databases: IoT will act as a bridge between the real world and NLP applications.
• Internet Infrastructure Development for Continuous Real-time Training: Sufficient network speeds are needed to handle the massive amounts of data collected from IoT.
• Ability to Integrate New and Old Data Continuously: NLP 3.0 needs to be able to process both new and old data to ensure accuracy and completeness.
• Enhanced Bandwidth: 5G or even 6G need to become more widespread to support the collection and training of data for NLP applications, or at least provide support for companies that train data for NLP applications.

3. Benefits of NLP 3.0

• Weather Analysis and Level-Specific Alerts: NLP 3.0 can analyze weather data from IoT to generate accurate and timely alerts about dangerous weather events, helping people avoid risks.
• Stock Market Analysis: NLP 3.0 can analyze stock market data, predict trends, and provide supporting information for investors.
• Analysis of Company Updates: NLP 3.0 can analyze news about companies, predicting the impact of events like new product launches, financial reports, bankruptcies, etc. on the market.
• Healthcare Analysis: NLP 3.0 can be applied to analyze medical data, support disease diagnosis, predict disease progression, and recommend appropriate treatment methods.
• Personal Health Analysis: NLP 3.0 can combine with wearable devices to analyze data on heart rate, running time, etc., providing recommendations for appropriate exercise and nutrition plans.
• Home Analysis, Smart Home, and IoT Integration: NLP 3.0 can manage and control devices in smart homes, automate household activities, and enhance user convenience.
• Website Traffic, User Data, Big Data, Real-time Analysis: NLP 3.0 can analyze website traffic, user behavior, and big data to optimize websites and improve business efficiency.
• Factory and Production Line Analysis: NLP 3.0 can be used to analyze production data, optimize processes, and enhance factory operational efficiency.
• Analysis of Real-World News from Broadcast Media: NLP 3.0 can analyze news from broadcast media sources, providing up-to-date information about ongoing global events.
• Sports Analysis: Team Lineups: NLP 3.0 can analyze data on lineups and player performance to make accurate predictions about match outcomes.
• Analysis of Real-World Situations: NLP 3.0 can analyze data from security cameras and sensors to predict the trajectory of burglaries, terrorist attacks, assassinations, and even war tactics. Note: Analysis related to war in NLP 3.0 requires careful ethical and responsibility considerations. The application of NLP in the military sector needs strict control to avoid unwanted consequences.

4. Table Differentiating NLP 1.0, NLP 2.0, and NLP 3.0

Feature	NLP 1.0	NLP 2.0	NLP 3.0
Emotion Analysis	Not Available	Available	Available
Creativity	Limited	Advanced	Advanced
Context Analysis	Limited	Advanced	Advanced
Understanding Specific Contexts	Limited	Advanced	Advanced
Emotion Expression in Analysis	Very Limited	Available	Available, and Capable of Emotional Transmission
Real-World Connection	Not Available	Not Available	Available

Observations

The development of NLP is transforming how humans interact with technology. NLP 2.0 and NLP 3.0 will mark the next steps in humanity’s advancement in the field of Natural Language Processing. NLP 2.0 and 3.0 promise to bring numerous beneficial applications to various fields, from analyzing real-world news and psychological therapy to the ability to empathize with users and provide emotional commentary.

Conclusion

NLP 3.0 is a promising step forward for artificial intelligence. With its ability to connect with the real world and express emotions in analysis, NLP 2.0 and 3.0 will bring groundbreaking solutions to complex societal challenges. However, for NLP 2.0 and 3.0 to truly flourish, there needs to be collaboration between researchers, technology companies, and governments to build infrastructure and address related ethical and social issues.

Summary Table

Stage	Capabilities	Limitations	Conditions
NLP 1.0	Intelligent conversation, data analysis	Lack of creativity, emotion analysis, in-depth analysis, understanding of specific contexts	–
NLP 2.0	Emotion analysis, creativity, contextual understanding, understanding of specific contexts, analysis of user emotions after marketing campaigns, analysis of emotions in communities and social media channels	Lack of real-world connection	Integration of emotion analysis capabilities, development of emotion analysis technology
NLP 3.0	Real-world connection, data collection and processing from IoT, weather analysis, stock market analysis, company news analysis, health analysis, home analysis, website traffic analysis, factory analysis, real-world news analysis, sports analysis, analysis of real-world situations. Capable of expressing emotions in analysis	–	IoT data connection, internet development, data integration capabilities, enhanced bandwidth