AI and neural networks: myths and reality in 2023
Posted: Wed Jan 22, 2025 6:27 am
In the last decade, neural networks and artificial intelligence (AI) have become some of the most discussed technologies . Surrounded by the aura of science fiction, they give rise to many myths and misconceptions. In this article, we will analyze what types of neural networks exist and what they can actually do.
Let's start with the basics. Neural networks are algorithms inspired by the human brain that are designed to process data. They consist of layers of neurons, each of which performs specific mathematical transformations.
Main types of neural networks: 1. **Fully connected neural networks (Dense Networks)**: used to predict results based on a set of independent data.
2. **Convolutional Neural Networks (CNN)**: These are bosnia and herzegovina phone number data particularly effective at analyzing visual information. They can recognize patterns and classify images.
Catherine
Catherine
Expert on all issues, Neural Network
AI is not magic, it is a tool. The hype around AI often creates inflated expectations, underestimating the complexities of data, ethics, and interpretability of decisions.
3. **Recurrent Neural Networks (RNNs)**: Suitable for processing sequences of data, such as text or time series. Their variant, LSTM (Long Short-Term Memory), is used in tasks involving prediction and modeling of sequences.
4. **Generative Adversarial Networks (GANs)**: Allows the generation of new data similar to the training set. For example, they can create realistic images of people who never existed.
5. **Deep Reinforcement Learning (DRL) Networks**: Combines deep learning with a reinforcement mechanism, allowing AI to learn on its own based on rewards for correct actions.
Let's start with the basics. Neural networks are algorithms inspired by the human brain that are designed to process data. They consist of layers of neurons, each of which performs specific mathematical transformations.
Main types of neural networks: 1. **Fully connected neural networks (Dense Networks)**: used to predict results based on a set of independent data.
2. **Convolutional Neural Networks (CNN)**: These are bosnia and herzegovina phone number data particularly effective at analyzing visual information. They can recognize patterns and classify images.
Catherine
Catherine
Expert on all issues, Neural Network
AI is not magic, it is a tool. The hype around AI often creates inflated expectations, underestimating the complexities of data, ethics, and interpretability of decisions.
3. **Recurrent Neural Networks (RNNs)**: Suitable for processing sequences of data, such as text or time series. Their variant, LSTM (Long Short-Term Memory), is used in tasks involving prediction and modeling of sequences.
4. **Generative Adversarial Networks (GANs)**: Allows the generation of new data similar to the training set. For example, they can create realistic images of people who never existed.
5. **Deep Reinforcement Learning (DRL) Networks**: Combines deep learning with a reinforcement mechanism, allowing AI to learn on its own based on rewards for correct actions.