Term of the Moment
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Definition: AI in a nutshell
AI is essentially pattern recognition, which identifies objects and natural language, as well as the trends in every discipline on the planet. The largest AI systems attempt to recognize and analyze the world's knowledge.
What AI Does
In medicine and science, AI is used to explore the interactions in every molecular structure. AI is used to make marketing and financial forecasts and answer questions about almost everything. A huge step beyond the voice assistants in every phone, AI systems also provide the extraordinary service of generating content that most people think was created by humans. ChatGPT and similar AI chatbots can create essays and images and even write poems. Ask an AI to write a poem about a frog and a pickup truck, and it will create an eloquent one. Some AI systems can generate videos from a simple description.
Not Ordinary Programming
Nothing at all like ordinary application programming, most AI applications use a "neural network" made up of multiple layers that connect to each other mathematically, which loosely mimics the human nervous system (neural system). The neural network is designed and programmed by AI engineers to be a "model" that is trained and fine-tuned on huge amounts of data. The execution part that users deal with, known as the "inference engine," must also be designed and fine-tuned. The inference engine employs the model to answer questions and generate content for the user. See AI programming, AI training vs. inference and AI secret sauce.
Models Are Trained on the World's Information
The data samples used for training come from websites, blogs, articles, dictionaries, encyclopedias and books, essentially all the information ever published online. The training phases can take a huge amount of datacenter time, power and electricity.
A Simple Example
An easy-to-understand example of how AI pattern recognition is used is in x-ray analysis. If 10,000 chest x-rays showing lung cancer and 10,000 cancer-free x-rays are fed into a neural network, the system learns the differences between them. Such systems can detect diseases better than medical professionals, and most importantly, faster. An article in the Washington Post in 2025 stated that two-thirds of all radiology departments in the U.S. use AI. See large language model, deep learning and neural network.
Everything Is a Pattern
No matter what people do in life, over time, they perform repetitive patterns. When these patterns are captured as data, they can be used to train an AI model. Although human intelligence is implied, AI results are the regurgitation of historical patterns combined with varying degrees of influence programmed into the neural network algorithms by AI designers. See AI secret sauce.
Concern for the Future
What worries people is the research being done to replace human decision making with AI. For example, should AI be used to expand a company or pull back? Even more significant, do we leave the decision to go to war up to a machine? There is a huge amount of controversy regarding AI and the future (see AI anxiety). See AI, technology singularity, AI hallucination, AGI and AI stages.
AI Will Reign Supreme
A Note from the Author
Everyone has an opinion about AI whether they really understand it or not. Well, so do I... after all, I've been in the information technology industry more than 60 years and have made more than a half million edits of technical content.
What AI Does
In medicine and science, AI is used to explore the interactions in every molecular structure. AI is used to make marketing and financial forecasts and answer questions about almost everything. A huge step beyond the voice assistants in every phone, AI systems also provide the extraordinary service of generating content that most people think was created by humans. ChatGPT and similar AI chatbots can create essays and images and even write poems. Ask an AI to write a poem about a frog and a pickup truck, and it will create an eloquent one. Some AI systems can generate videos from a simple description.
Not Ordinary Programming
Nothing at all like ordinary application programming, most AI applications use a "neural network" made up of multiple layers that connect to each other mathematically, which loosely mimics the human nervous system (neural system). The neural network is designed and programmed by AI engineers to be a "model" that is trained and fine-tuned on huge amounts of data. The execution part that users deal with, known as the "inference engine," must also be designed and fine-tuned. The inference engine employs the model to answer questions and generate content for the user. See AI programming, AI training vs. inference and AI secret sauce.
Models Are Trained on the World's Information
The data samples used for training come from websites, blogs, articles, dictionaries, encyclopedias and books, essentially all the information ever published online. The training phases can take a huge amount of datacenter time, power and electricity.
A Simple Example
An easy-to-understand example of how AI pattern recognition is used is in x-ray analysis. If 10,000 chest x-rays showing lung cancer and 10,000 cancer-free x-rays are fed into a neural network, the system learns the differences between them. Such systems can detect diseases better than medical professionals, and most importantly, faster. An article in the Washington Post in 2025 stated that two-thirds of all radiology departments in the U.S. use AI. See large language model, deep learning and neural network.
Everything Is a Pattern
No matter what people do in life, over time, they perform repetitive patterns. When these patterns are captured as data, they can be used to train an AI model. Although human intelligence is implied, AI results are the regurgitation of historical patterns combined with varying degrees of influence programmed into the neural network algorithms by AI designers. See AI secret sauce.
Concern for the Future
What worries people is the research being done to replace human decision making with AI. For example, should AI be used to expand a company or pull back? Even more significant, do we leave the decision to go to war up to a machine? There is a huge amount of controversy regarding AI and the future (see AI anxiety). See AI, technology singularity, AI hallucination, AGI and AI stages.
MIT professor Max Tegmark's best-selling book postulates an AI that far exceeds human intelligence and literally takes over.
Everyone has an opinion about AI whether they really understand it or not. Well, so do I... after all, I've been in the information technology industry more than 60 years and have made more than a half million edits of technical content.