(tl;dr; Nobody really knows! We don’t even know what “human” intelligence is. At GistLabsAI we use “algorithmic insights” as a pragmatic definition of how and what we build and deliver.
This question has been debated for decades. When DALL-E is used to generate an image to answer the question:
There, I’m sure that cleared everything up!
“Intelligence is a complex and multifaceted trait that can be challenging to define precisely due to its various aspects and interpretations. However, it is generally understood as the ability to acquire and apply knowledge, solve problems, adapt to new situations, and learn from experience. Intelligence encompasses a wide range of cognitive abilities and skills.”, ChatGPT answering “what is intelligence?”
The simple fact is we don’t even know how to define “human” intelligence! Defining “artificial” intelligence is even further away.
We at GistLabsAI use the word “insights” instead of “intelligence” when we are explaining what we build and deliver.
“Insight is a term used to describe the ability to gain a deep and clear understanding of a situation, problem, or concept. It often involves the sudden and profound realization or comprehension of something that was previously unclear, puzzling, or hidden. Insight is characterized by a heightened awareness or a new perspective that allows individuals to see connections, solve problems, or make decisions more effectively.” ChatGPT
Making decisions more effectively, and solving problems? Now that sounds pretty useful. We want more of this.
“The term "artificial" refers to something that is created or produced by human beings rather than occurring naturally. It is often used to describe things that are synthetic, man-made, or the result of human design and engineering. In the context of technology and science, "artificial" is frequently used to distinguish human-created objects, systems, or processes from those that exist in nature.” ChatGPT answering “what is the definition of artificial. Think artificial sweetener.
This definition is much more clear than intelligence, but it doesn’t give us any idea what is being designed, and “artificial insights” doesn’t make a lot of sense.
We prefer to be more descriptive and focus on the “how” we create insights.
What do we do? We build algorithms that solve problems. Bayesian, neural networks, LLMs, computer vision, and even heuristic approaches are all algorithmic models for problems, and solutions. Humans aren’t that great at running algorithms in their head, but computers sure are. Algorithms plus good UX/CX to convey the right information allow us to turn algorithms into algorithmic insights and those can solve interesting problems.