Introduction to Neural Network System (NN)
A neural network system (NN) is a system that works like the human brain. It is a mathematical implication that mimics the human brain through AI technology. It works structurally and functionally like the brain. Comprised of synthetic neurons just like the human nervous system. This AI technology is one of the best creations ever because its functions include; analysis, prediction, face recognition, processing, language understanding, video processing, and much more. The interconnected network enhances many functions and makes life easier.
A Deep View of Liquid Neural Networks (LNN)
This is a type of repeated neural network that processes data in a continuous manner. This system was presented by some researchers under the name of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL). So, we can regard it as one of the miraculous creations of AI Technology.
The Liquid Neural Network (short form LNN) also stores memory, processes the behavior of the input, and works according to the input that has been entered into the system. The LNN is an advanced version of the neural network system, as its architecture is different as well as it works continuously. It works more effectively due to its advanced working in time series.
The best example of LNN is its implication in video graphics. If you apply the model classification to a specific video, LNNs will work it out frame by frame and process it without the indulgence of the surrounding context. For overcoming these issues, this AI technology is used by developers to enhance the process of videos.
Creators and Idea Behind the Liquid Neural Network:
The creators are Ramin Hasani, Mathias Lechner, and their teams. They got the idea of creating this system from a type of nematode worm known as C. elegans. The reason behind this is the amazingly structured nervous system of this worm which makes it capable to carry out very complex functions; like learning, eating, and sleeping. This worm has around 302 neurons which are responsible for all the complex functions it does in its life. LNNs impersonate the interlinked impulses of the worm to forecast network behavior over time. The network states the system at any given moment during its working. This invention counts back to the year 2018 when they were first discussed in a research paper related to robotics.
Distinguishable Features of the Liquid Neural Network (LNN)
Now, coming towards the features of this amazing invention of the 21st century. They are mentioned below, please give read:
- More Active Built-up:
The neurons in LNN are more advanced and effective than the traditional neural networks. They encourage difficult multi-tasking.
- Endless Learning and Adaptations:
The liquid word used is for the adaptability of this network. The interconnected nature works in the same fashion as the human brain, processing data and adapting to the changes taking place. The LNNs are capable enough to work with proper training as they have many in-built qualities to adapt. They would predict and process data continuously without even a slight delay.
Comparison Between the Typical Neural Network & Liquid Neural Network
|Neural Network (NN)||Liquid Neural Network (LNN)|
|Larger than size||Smaller in size|
|Less advanced as compared to LNN||More effective and advanced|
|Less tough towards noise and disturbances in the input signals||More tough towards noise and disturbance in the input signal.|
|Mimics less accurately||Mimics the brain more accurately|
|Less adaptability||More adaptability than NNs.|
Some Worth-mentioning Uses of the LNNs:
AI technology is ruling the current world. Every aspect of modern life has some impact of AI, from healthcare to education, from fashion to web development, everything has the essence of AI technology in it. There are some uses of LNNs in the modern world, we will discuss them one by one.
- Forecasting and Time Series Data Processing:
If it comes to time series data processing, LNNs are some best options. They are also used in prediction.
- In Video Processing
In imaging and video processing, these LNNs are used in features such as recognition, segmentation, object tracking, and much more. They adapt to environmental changes and complex situations. Even some drones are invented having small parameters of LNNs used in the navigation of the environment. These LNNs can also work in building up the structure of vehicles. LNNs are also used in Face Recognition features.
- Natural Language Understanding
With its features of understanding long text sequences, the LNNs can be able to understand natural language. This AI can be used for understanding the emotions behind the context. These are the success behind the translators that we find in different machines nowadays.
This was the entire discussion related to the new AI technology creation which is Liquid Neural Network. Its uses are mentioned and we can conclude that they play a major role in modern AI-controlled life. The content contains the introduction of LNNs to their uses and implications in daily life.
Frequently Asked Questions (FAQS)
What is Liquid Neural Network (LNN)?
This is the network system that mimics the human brain and makes predictive data according to the input signals. There are artificial neurons present that make a controlling system like the brain and spinal cord in humans. This recurrent neural network works continuously with endless features.
Where are LNNs used?
There are different uses of LNNs such as; video processing, image processing, prediction, time series data processing, and understanding natural languages.
Are LNNs reliable?
Yes, Liquid Neural Networks are reliable AI technology inventions. As they are part of many devices of the modern world, we can rely on them and they work as effectively as any other modern device. Face recognition is one of the reliable use that is a clear proof of how we humans rely on LNNs.