Photo via editor Chatgpt
# Entry
Everyone talks Artificial intelligence (AI) Recently and there are opportunities, depending on who you ask, they can explain what AI is in a different way: often using technical, almost foreign terms, and sometimes in elementary categories. This article is aimed at Take the second direction, and explain simply what artificial intelligence, its possibilities and limits are, and Some key areas or components which are currently part of AI.
# What is AI? Possibilities and limits
And is a branch of computer science that focuses on Developing computer systems capable of imitating the skills of human or animal intelligence to solve a specific problem or task. Smart features that can imitate, depending on the specific AI system, include reasoning, predicting future or unknown facts, visual perception, communication with people or other AI systems and interactions with the environment to mention only a few.
One critical ability in most newfangled AI systems that penetrate virtually all of the above -mentioned skills Learn based on data. Like a compact child who learns, observing and exposed to examples of everything (words, images, actions, etc.), AI systems learn from many examples of data to perform intricate tasks, such as forecasts, inference, communication in human language and much more.
Some may be surprised when I hear it And is not an invention of the 21st century: In fact, the field was born in the middle of the last century. However, thanks to achievements in learning based on data-and thanks to the development in terms of calculations and the availability of data-AI has experienced its greatest progress over the last one and a half decade, with generative and language models, such as chatgpt, are clear examples of the latest high-impact achievements.
But AI also has its limitations: He doesn’t really “understand” the world, just like people (everything is understood and advised with mathematically, so to speak!), He can make mistakes if he learned from low quality data and usually fights tasks that require common sense or human sensitivity. Huge needed computing energy and computing energy are also high costs.
# AI areas
Outline the main areas of AI and some key points to better understand them.
Areas of artificial intelligence and common symbiotic relations between them Photo by the author
- In the early years of AI, Knowledge representation and reasoning They were dynamic subjects of research, focused on creating programs that could reason and draw conclusions about real facts and knowledge represented in a way in which possible. A significant part of the logic between autonomous agents (sometimes implemented in robotic systems capable of interaction with the real world) is based on these techniques and the recent uprising Agentic ai Solutions enliven interest in this subdomain.
- Machine learning It is by far the most widespread area of artificial intelligence: almost every newfangled AI system uses approaches to learning from data to solve a task, such as classifying photos, predicting prices or future sale, recommending products for customers and more.
- Deep learning It is like a “developed form” of machine learning: larger and more intricate systems that learn from huge data sets to solve more hard tasks. Interestingly, Computer vision AND Natural language processing Applications – such as visually recognizing objects and conversation with man – recently resolved mainly with the lend a hand of deep learning systems, hence their close relationship.
- So where do the latest trends do Generative AI AND Language models (LLM) sit? These systems are massive architecture of deep learning transferred to a higher level.
It was a concise, gentle introduction to AI. I hope you liked it!
IVán Palomares Carrascosa He is a leader, writer, speaker and advisor in artificial intelligence, machine learning, deep learning and LLM. He trains and runs others, using artificial intelligence in the real world.