Last Updated on October 23, 2023 by Kevin Chen
Image source all about Circuits
Artificial intelligence (AI) has deeply penetrated every other industry. One of its products is the smart autonomous systems. Think of the automotive industry, medicine, data analytics, smart homes and many other application areas. All of them have a proof of the AI systems.
At the backbone of the AI proliferation are the IC chips. There are higky specialized AI chips that are used in these smart and autonomous systems. They are used for building and running these autonomous products.
AI chips are relevant for both the hardware and software aspects of the smart autonomous systems.
What do you mean by smart autonomous systems?
There are two terms that we need to know when it comes to defining smart autonomous systems. These are ‘Smart’ and ‘autonomy’.
A smart system means that it can work or operate based on its intelligence. It operates as a human being thanks to the power of artificial intelligence.
Autonomy refers to the ability of a system to function independently with minimal intervention from human.
In some cases, human assistance may be needed but to a very small extent.
To achieve the full levels of intelligence and autonomy, these systems must undergo continuous training which is done using machine learning and artificial intelligence.
Loads of datasets are used to train the systems just like the normal training that human beings undergo.
Once the systems meet particular parameters, they are then released to perform the real-world applications in their respective fields.
Key features of smart autonomous systems
How do I know that a system is smart and autonomous? The system should exhibit the following key features:
- Independent: These systems operate independently. They require very minimum human supervision.
- Intelligent: They are called smart systems because they are intelligent. The intelligence of these systems is acquired during training and machine learning of the models used.
- Flexible: These systems are quite flexible such that they can adapt to different conditions. All that is needed is to retrain the models
- Safety levels: Before any autonomous system is deployed, it must pass all the safety measures.
Examples of smart autonomous systems
Here are some examples of applications in which IC chips and artificial intelligence have enabled smart and autonomous systems.
- Autonomous self-driven vehicles
- Autonomous robots
- Smart home assistants
- Autonomous drones
And many other applications for both residential and commercial use.
What is the relationship between the AI chips and smart autonomous systems?
The smart autonomous systems are electronic devices. This is where the relevance of the AI chips come in.
The Artificial intelligence chips provide the hardware platform on which these autonomous systems run.
These chips are just like other ordinary IC used in other electronic devices and applications, only that they have that one additional feature: AI capability.
This implies that they are capable of performing complex tasks that require high levels of human intelligence.
These chips feature algorithms that have undergone vigorous training through machine learning.
AI chips are ideal for the smart autonomous systems because they provide all the power and speed that is required in running the systems. This is based on the fact that AI algorithms are complex and cannot be easily performed by the ordinary chips.
In short, the avail all the necessary resources for the AI tasks.
Relationship between artificial intelligence and smart autonomous systems
Artificial intelligence is the driving force of the smart autonomous systems. It enables these machines to function perfectly without any human supervision.
Whenever AI is involved, its tenets such as machine learning and algorithms must be involved. These two are heavily involved in making the smart systems operate independently.
Let’s look at the key features of the artificial intelligence that are used in the operation and running of the smart autonomous systems.
Perception
Just like human beings, smart systems are able to read and perceive their environment.
Perception is a key aspect of intelligence and it is directly linked to the autonomy.
It is from the perception stage that they will be able to take any necessary action. In the traditional computing, we can compare perception to the ability to read data. The perception is usually based on the level of training that the system has received. Once it has been trained, it will use its data recording features such as sensors ,image readers, text readers to separate different types of objects.
Decision making
This is another key feature of AI that smart autonomous systems must utilize. After reading data (perceiving) the next stage is to make a decision.
This is where the relevance of AI decision-making algorithms come into play.
A smart autonomous system will use such algorithms, together with many other factors to decided on what to do with the data it has perceived.
Again, the decision that it makes will be based on the type and level of training that the system has been subjected to.
Machine learning
Learning is a component of the artificial intelligence. Through machine learning, the smart autonomous systems are trained on how they will be able to perceive and execute actions in the real applications.
Machine learning models that have been built using large datasets train the systems to not only learn but be able to adopt depending on the changing circumstances and situations.
It is through proper learning that the systems become effective, accurate and reliable.
The above key components of artificial intelligence play big roles in the overall functioning of the smart autonomous systems.
Now when we add IC chips in the playbook, we will have perfect systems that will be able to deliver the desired results.
The role of IC chips in enabling smart and autonomous systems
We have just discussed the roles of AI in enabling the smart autonomous systems.
What do the IC chips do in the running and operations of these systems.
Well, here are some of the roles that the integrated chips play in ensuring that the autonomous systems run smoothly and effectively.
Processing power
The processors that run the smart autonomous systems are basically integrated circuits.
These processors are built to handle and process large datasets that will be critical for the machine learning and decision making of the smart systems.
IC chips are the building blocks of most processors in the market. Think of the signal processors, data processors, microcontrollers and other types of processors.
The processors used in the smart systems have AI features that enable them perform complex computations.
Sensors in the smart autonomous systems
The perception feature of the smart autonomous systems depends on their sensors. The sensors read and perceive the environment. Data collected by the sensors will then be used for decision-making.
These sensors are basically integrated circuits with the data-reading or sensing capability.
The ICs comprise of various electronic components that use their working mechanisms to read data and perceive the environment of the systems.
Common sensors used in the smart autonomous systems include temperature sensors, light sensors, pressure sensors among others.
Data chips in the smart autonomous systems
The working and operation of the smart and autonomous systems entails lots of data.Data from that has been perceived by the system must be processed and in some cases stored by the system.
Data ICs are used for all the data-related functions in the smart autonomous systems. Most of the chips are used for the storage of data.
Two common data chips used are the RAM and ROM chips. Some chips are used for the temporary data storage while others are for the long-term data storage.
Communication and network IC chips in smart systems
Despite the fact that smart autonomous systems are designed to work independently, most applications require that they communicate with other devices. This is where the relevance of the network IC chips come in.
These are chips that are specifically designed for the networking purposes. They make it possible to connect an autonomous device to the Wi-Fi network and facilitate exchange of data between devices.
Safety of the smart systems
IC chips are also designed to guarantee safety of the AI-powered smart autonomous systems.
There are different types of chips that play this crucial protection role.
For instance, we have power management chips that regulate the flow of current in the systems. They ensure that each component of the system gets the right electric current as required.
In doing so, the IC chips protect the system from the dangers of overcurrent and overvoltage.
Some sensor chips are designed to sense different types of risks and shut off the system in time to protect it from possible dangers.
There are many other types of chips used in the running of AI-powered smart autonomous systems.
When these chips are combined with AI features, we expect the smart systems to run smoothly and effectively.
Conclusion
It is clear that IC chips and AI are at the core in the running of the smart and autonomous systems.
They have prove to be safe and effective in all the smart devices. So, if you are building a smart system, you will have to consider buying AI chips from the right suppliers.
Since the future is AI, we should expect to see these chips running most devices.
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