Types of AI
Hey! What’s up lovely readers hope you all are doing well.
In my previous article, I talked about AI.
https://medium.com/@Akshali/hello-everybody-today-i-am-gonna-to-discuss-about-soft-skills-that-why-soft-skills-are-important-c02d76fbe53c
But now in today’s article, I will discuss the types that we are not aware of as such of now in-depth
We all are familiar with the term AI but do you know it has different types too?
Yes so the types are -
- Theory of mind.
- Reactive machines.
- Artificial superintelligence.
- Robotics .
- Machine learning .
- Natural processing language.
There are many more types but here I have discussed the main ones.
Let’s begin ......
- Theory of Mind
This is currently the third level of AI and understands the needs of other intelligent entities. Machines aim to have the capability to understand and remember other entities' emotions and needs and adjust their behaviour based on these.
Characteristics of Theory of Mind AI.
- Computers embedded with the Theory of Mind AI can infer the objectives of entities around them.
- Theory of Mind AI systems will be able to understand the importance of their awareness and the different consequences it could lead to.
- Robots or Theory of Mind AI systems will communicate with human beings better than the current generation of AI, which cannot explain their actions.
- Theory of Mind AI will be implemented with a Machine Learning system that can explain decisions in various languages, helping the user (human being) understand.
A Robot or Theory of Mind AI system should be able to understand the intention of other similar Robots or Theory of Mind embedded systems.
Theory of Mind AI is nothing but the level of AI that works like the human mind with the same emotions.
We can see examples of chatbots when we try to talk with some emotional as we talk like a friend or somebody it answers like that.
So this is what?
It is AI using the theory of Mind.
AI systems can leverage aspects of the theory of mind (ToM) to understand human emotions, even if they don’t experience emotions themselves.
This understanding helps AI respond in a way that aligns with the perceived emotions, making interactions more relatable and natural for humans.
- Reactive AI
So AI bots are designed in such a way that they can react to the message or the prompt that we put into it.
Example
Me : Hi! Google how are you ?
Google assistant (Gemini) :
Hi Akshali! Thank you for asking Nice to meet you so what can I help you?
Hi Akshali! Thank you for asking Nice to meet you so what can I help you?
As we react in different situations likewise AI bots also do the same.
Or we can say that AI bots and robots are the kind of machine humans. Agree?
We all read about Human psychology but we also need to know behind story of these machine humans (AI BOTS).
These reactions are based on the large language model.
Lage language model (LLM)
It refers to the model which decides how bots and robots will answer the questions.
It reflects its message in the human language.
Because of this, we can talk to the bots in our native and regional languages like (Hindi, Gujarati, Marathi, Tamil, Telegu, Sinhala, German French, Marwa Adi (a Rajasthani language) etc there are many more languages worldwide.
- Artificial super intelligence (ASI)
Artificial superintelligence (ASI) is a hypothetical type of AI that would surpass human intelligence in all aspects. It’s a concept that sparks both fascination and concern as it raises questions about the future of humanity and our place in it.
While ASI is still the realm of science fiction, continued advancements in AI research and development make it a topic of serious discussion among experts.
It the advancement in AI we can say it is futuristic AI.
Artificial superintelligence (ASI) and discussions around its rights are hypothetical at this point.
ASI is envisioned to surpass human intelligence in all aspects, making attributing human rights to it a complex issue. Here’s why:
* Human Rights Framework: Current human rights frameworks are designed for humans, considering our social and biological makeup. Applying these directly to an ASI might not be suitable.
* ASI’s Value Systems: An ASI’s goals and value systems could significantly differ from ours. Its concept of "rights" might be entirely alien to us.
* Understanding of sentience: Whether ASI would achieve sentience or consciousness, the capabilities we typically associate with deserving rights, is still up for debate.
The focus for now should be on developing AI responsibly and ethically, ensuring its alignment with human values.
This would be crucial groundwork for addressing potential rights questions if and when ASI becomes a reality.
We can take the example of how ASI is reacting as a human right it can be a good example of artificial superintelligence rights.
- Robotics
Machines that are designed to act like humans with some emotions are robots.
These are the dangers for the future. We have to control them.
https://youtu.be/0HoSwHNUOHg?si=RGIv9id4tygvju3F
This is the video in which the interviewer, interviewed an AI robot (Sophia)
Go check it out once and you can realise how AI robots are becoming powerful these days.
If we don’t take action or control them then it will be not wrong to say that AI will run our companies.
It is right that they don’t have emotions like us but the companies are working on this.
So we have to be careful and alert.
- Machine learning and natural processing language
Machine learning (ML) is a type of artificial intelligence (AI) that allows systems to automatically learn and improve from data without being explicitly programmed.
It’s like learning from experience. Machine learning algorithms use data to identify patterns and make predictions.
Natural language processing (NLP) is a subfield of AI that deals with the interaction between computers and human language.
NLP uses machine learning techniques to enable computers to understand and process information written or spoken in natural language.
Here's an analogy to understand the relationship between machine learning and NLP:
Imagine if you are learning German so firstly you collect the resources that you have to study then you study it from the beginning and then after it we can analyse the grammar rules, vocabulary etc.
Now with the help of these, you can translate and understand German.
And another example
The computer‘s binary system (0–1) translates our input data into a binary system so that it can give us the relevant output.
Similarly, NLP systems are trained on large amounts of text data.
They learn to identify patterns in language, such as the relationships between words, the structure of sentences, and the meaning of text.
This knowledge can then be used to perform a variety of tasks, such as:
Machine translation
Text summarization
Sentiment analysis
Speech recognition
Chatbots
Machine learning is a powerful tool that can be used to improve the performance of NLP systems. For example, machine learning can be used to automatically identify and correct errors in text data, or to improve the accuracy of machine translation.
In short, machine learning is the engine that powers NLP, and NLP is one of the most important applications of machine learning.
Difference between AI and Human .
The difference is that humans have emotions but can’t memorize huge data.
Whereas AI comparatively have fewer emotions as such now they can memorize huge data.
AI is a vast to go through so we have to be updated because it is rapidly updating.
I have put a reference link so that you can read it in more depth
Refrence
- https://www.sciencedirect.com/topics/neuroscience/theory-of-mind
- https://www.coursera.org/articles/types-of-ai
- https://uq.pressbooks.pub/digital-essentials-artificial-intelligence/chapter/types-of-ai/
Thank you for reading my article
Let’s Learn and grow.
