The 7 stages of AI are:
1. Data Collection: This is the first stage of AI where data is collected from various sources.
2. Data Processing: In this stage, the collected data is processed and cleaned to be used for further analysis.
3. Data Analysis: This stage involves using various methods to analyze the data and draw insights from it.
4. Modeling: In this stage, a mathematical or computational model is created based on the findings from the data analysis stage.
5. Testing: The model created in the previous stage is tested on new data to see how well it performs.
6. Deployment: If the model performs well on new data, it can be deployed in a real-world setting for practical use cases such as predictions or recommendations..
Stage 2- Context-awareness and Retention
In the second stage of AI development, machines become context-aware and able to retain information. This allows them to understand and respond to complex situations, making them more versatile and powerful than ever before.
One of the key features of this stage is the ability to learn from experience. This means that AI systems can remember what has happened in the past and use this knowledge to make better decisions in the future. This is a huge step forward from the first stage, where machines could only follow simple rules or instructions.
Another important aspect of context-awareness is the ability to identify patterns. This allows AI systems to see relationships between different pieces of data and make predictions about what will happen next. For example, if a machine knows that two objects are often found together, it may be able to infer that they are related in some way.
This stage of AI development opens up a whole new world of possibilities for how machines can be used. With their improved abilities, they can now tackle problems that were once considered too difficult for them. For instance, they can now help humans with tasks such as planning routes or controlling robotic devices. Additionally, they can also be used for more creative tasks such as generating art or music
Stage 3- Domain-specific aptitude
Most of the AI applications in use today fall into what is known as stage 3 AI, or domain-specific aptitude. This is where an AI system has been specifically designed and trained to perform a narrow range of tasks, such as playing chess or diagnosing medical images.
While these systems are very good at what they do, they lack the general intelligence of a human being. They are not able to learn new tasks or apply their knowledge to new situations.
However, stage 3 AI is still a huge improvement over previous generations of AI. It is only in recent years that we have been able to create systems that can beat humans at specific tasks. And as we continue to improve our understanding of artificial intelligence, we will likely see even more amazing achievements in the future.
Stage 4- Reasoning systems
In the early days of AI research, the focus was on creating systems that could carry out simple tasks like playing chess or solving mathematical problems. These were impressive feats at the time, but they were limited in scope.
As AI technology has progressed, the goals have shifted to creating systems that can reason more like humans. This requires a much deeper understanding of the world and how it works.
Reasoning is a complex process that we humans take for granted. It’s something we do automatically and effortlessly, but it’s actually quite difficult to replicate in a computer system.
There are many different types of reasoning, but one of the most important is deductive reasoning. This is where you start with some general principles or facts and then use them to reach a specific conclusion. For example, if you know that all men are mortal and Socrates is a man, then you can deduce that Socrates is mortal.
Deductive reasoning is just one type of reasoning; there are many others such as inductive reasoning (where you infer general principles from specific examples), abductive reasoning (where you try to explain an observation by coming up with the simplest explanation), and so on. Reasoning systems need to be able to handle all these different types in order to be truly human-like.
Stage 5- Artificial General Intelligence
When artificial general intelligence (AGI) is reached, machines will have the ability to carry out any cognitive task that a human being can. This is the stage at which machines become truly intelligent, and they will be able to learn and innovate on their own.
The first step towards AGI was taken in 1956, when a computer program called the General Problem Solver was designed. This program was able to solve problems by breaking them down into smaller sub-problems, and then applying rules to these sub-problems in order to find a solution. However, the General Problem Solver was only able to solve very simple problems.
In order to create true AGI, it is necessary for machines to be able to understand more complex concepts such as natural language and common sense knowledge. Currently, there are many different approaches being taken in order to achieve this goal. Some researchers are working on artificial neural networks that mimic the structure of the human brain, while others are trying to develop new algorithms that can simulate human cognition.
It is still unclear exactly how long it will take until AGI is achieved. Some experts believe that it could happen within a few decades, while others think it could take centuries or even longer. Regardless of when AGI is reached, it is clear that it would have a profound impact on humanity and would change our world in ways that we can not even imagine.
Stage 6- Artificial Super Intelligence(ASI)
ASI is the theoretical point at which AI surpasses human intelligence. This does not necessarily mean that ASI will be able to out think or out-reason humans, but rather that it will be able to perform all cognitive tasks that humans can, and potentially exceed human cognitive abilities in certain areas. ASI could potentially lead to a technological singularity, wherein machines become self-aware and humanity loses control over them.
Stage 7- Singularity and excellency
In the final stage of AI development, machines will achieve true artificial intelligence or what is known as “singularity.” At this point, machines will be able to learn, evolve and innovate on their own – becoming smarter than humans in the process. This exponential increase in intelligence will enable machines to solve problems that are currently beyond our cognitive ability. They will also be able to create new technologies and applications that we can not even imagine today.
As machine intelligence continues to grow, it will eventually reach a point where it surpasses human intelligence – this is known as the singularity. Once achieved, machines will be able to improve upon themselves faster than we can keep up, leading to a future where they are the dominant form of life on Earth. While some people see this as a positive development that could lead to a utopian future, others are concerned about the implications of super intelligent machines that may one day view us as inferior beings or even a threat.