The article artificial intelligence: You should know these 10 AI terms from Beatrice Bode first appeared on Basic Thinking. You always stay up to date with our newsletter.
The rapid development of artificial intelligence (AI) shapes our society like hardly any other technology. However, not everyone feels comfortable with it – also because some basics are difficult to understand. We therefore explain ten AI terms that you should know and understand.
“Artificial intelligence (AI) is the ability of a machine to imitate human skills such as logical thinking, learning, planning and creativity”: European Union the term. AI is based on algorithms and technologies such as machine learning and neuronal networks. They enable computers to learn from data independently and to recognize patterns.
Originally developed as a scientific concept, AI has now received its way into many areas of life. From voice assistants such as Alexa to self-driving cars, it is no longer just a topic for tech professionals and enthusiasts. The technology influences our everyday life in a variety of ways. For example, we use Chatgpt to maintain medical advice or to do work and school tasks. AI systems also deliver recommendations for streaming services, personalized advertising or translation text automatically.
You should know these AI terms
People without a technical background should also know the basics, since AI is now almost omnipresent. A basic understanding not only helps to better assess opportunities and risks, but also to actively participate in discussions about the use of technology. In the following overview, we therefore explain the ten most important AI terms.
Llms
LLM stands for “Large Language Model”. The term describes large voice models such as chatt, which are trained with the help of amounts of data. Because they are based on neuronal networks, they can understand and reproduce human language. LLMS use techniques of mechanical learning to process language and thus imitate human communication.
The article artificial intelligence: You should know these 10 AI terms from Beatrice Bode first appeared on Basic Thinking. Follow us too Google News and Flipboard.
As a tech industry expert, it is crucial to have a solid understanding of artificial intelligence and the key terms associated with it. Here are 10 AI terms that every expert should know:
1. Machine Learning: This is a subset of AI that enables machines to learn from data without being explicitly programmed. It is used in various applications such as predictive analytics and natural language processing.
2. Deep Learning: A subset of machine learning that uses neural networks to mimic the way the human brain works. It is particularly effective in tasks such as image and speech recognition.
3. Neural Networks: These are a type of deep learning algorithm that is inspired by the structure of the human brain. They consist of interconnected nodes that work together to process information.
4. Natural Language Processing (NLP): This is a branch of AI that focuses on enabling machines to understand, interpret, and generate human language. It is used in applications such as chatbots and language translation.
5. Computer Vision: This is a field of AI that enables machines to interpret and understand visual information from the environment. It is used in tasks such as facial recognition and object detection.
6. Reinforcement Learning: This is a type of machine learning where an agent learns to make decisions by interacting with an environment and receiving feedback in the form of rewards or penalties.
7. Supervised Learning: This is a type of machine learning where the model is trained on labeled data. The goal is to predict or classify new data based on the patterns learned from the training data.
8. Unsupervised Learning: This is a type of machine learning where the model is trained on unlabeled data. The goal is to find patterns or relationships in the data without any predefined labels.
9. Artificial Neural Networks: These are computational models inspired by the structure and function of biological neural networks. They are used in deep learning algorithms to process complex data.
10. Ethics in AI: With the increasing use of AI in various industries, it is important to consider the ethical implications of AI technologies. This includes issues such as bias in algorithms, data privacy, and job displacement.
Overall, having a strong understanding of these key AI terms is essential for any tech industry expert looking to stay up to date with the latest advancements in artificial intelligence.
Credits