Did you know that ChatGPT has over 400 million weekly users? This makes it the 8th most visited website, surpassing X!
Many people use Artificial Intelligence almost every day, even when they're not aware of it. However, understanding what it is can be complex.
We'll break down what Artificial Intelligence is, how it works and why it is crucial nowadays, all in simple words.
What is Artificial Intelligence for Dummies?
Artificial Intelligence refers to machines, tools or systems that can simulate human capabilities.
In other words, AI systems can solve problems and complete tasks that would typically require human intelligence.
Examples include Amazon, which analyzes interactions to recommend products, films, and songs.
Virtual assistants, such as Siri, also leverage AI to understand human language and respond naturally.
These tools process information, simulate thinking and provide responses like humans do, without constant supervision.
Current AI tools can create images, audio, video, code and text conversationally through Generative AI (GenAI).
Some GenAI tools, such as ChatGPT-4.5, have even led users to believe they are interacting with a human up to 73% of the time!
How? As AI learns to recognize patterns in human communication, it can generate answers that replicate the tone or style.
As interactions flow naturally and with minimal delay, in some cases, people forget they're talking to an AI.
Main Types of AI
1. Narrow AI
Narrow AI, or weak AI, refers to tools that perform specific tasks, such as content writing or image generation.
These systems can only work on tasks they've been trained to do without being able to learn to face new challenges.
All current AI tools could fit into Narrow AI because they're designed to perform specific tasks.
Since they can go beyond the scope for what they're trained for, an AI trained to play chess couldn't suddenly write poetry or do your taxes.
An AI trained to play chess is built with data, algorithms and optimization techniques only for that task.
It can't transfer this "knowledge" to something totally unrelated.
2. General AI
General AI, or Artificial General Intelligence (AGI), systems are capable of learning and self-teaching to perform new tasks.
Theoretically, AGI could match human reasoning, as it could learn and improve without the need for human intervention.
In this way, an AGI system trained for playing tic-tac-toe could learn an entirely new task, such as calculating your taxes.
A clear example of an AGI system would be J.A.R.V.I.S. from Iron Man.
Unlike today's AI, this system could adapt to entirely new tasks without retraining.
J.A.R.V.I.S. could switch between domains, like playing chess, writing poetry and calculating your taxes, while doing other tasks simultaneously.
It's worth noting that AGI is a hypothetical concept, and no one knows for sure if it'll ever exist.
3. Super AI
Lastly, Artificial Superintelligence (ASI), or Super AI, goes a step beyond AGI.
While AGI could theoretically match human reasoning and learn new tasks independently, ASI would surpass human intelligence entirely.
These systems wouldn't just replicate human thinking.
To work, ASI would need capabilities to refine its own code iteratively.
Additionally, it would require access to near-unlimited computing resources, such as quantum computing.
Finally, it'd require advanced multi-modal integration, combining reasoning, sensory perception, emotional intelligence and long-term planning, all into a single system.
Since ASI is theoretical, there are no current examples of how it would work in real life.
However, sci-fi movies offer examples of ASI systems, such as the super-intelligent personal assistants in Her.
How Does AI Work in Simple Terms
AI systems undergo a training process in which they learn to identify patterns within training data.
The data and patterns learnt in the training process will depend on the AI system's purpose.
If developers want the AI to learn to recognize cats, the training data should include a large number of images of cats.
During training, the AI would learn to recognize specific patterns, such as the shape of cats' ears, eyes, whiskers and paws.
Additionally, by identifying these specific details, the system can distinguish cats from other animals.
A great example is our collaboration with Sylvester.ai, an AI app that analyzes images of cats to determine their emotional state.
Consider this training process as "homework," which is reviewed by teams to ensure the system works correctly.
Based on its outcomes, teams make adjustments and repeat the process until it's refined.
This process involves Machine Learning (ML), where systems learn to make predictions without supervision.
Teams use this technology to teach systems to anticipate users' needs.
A retailer using AI can optimize inventory by predicting demand based on previous data.
As a result, they can ensure products are available when and where they're needed.
How Do AI Models Work
An AI model is the trained "brain" of an AI system, created by feeding large amounts of data into an algorithm.
These models are the core of AI systems such as image generators, text-to-speech tools, and conversational chatbots.
Speaking of which, modern AI chatbots, like ChatGPT, combine ML with Natural Language Processing (NLP).
These AI models receive massive amounts of data during their training process to learn the rules and syntax of human language.
As a result, AI chatbots can understand human language and combine words in response to users' prompts.
Devs also use Reinforcement Learning (RL), an advanced ML technique, where teams give feedback to the AI's outcomes.
This enables teams to refine AI models, improving their responses and making them safer and more reliable.
However, considering that AI systems can still hallucinate, teams should always fact-check responses.
The Artificial Intelligence for Dummies Book
The Artificial Intelligence For Dummies book is a great resource for learning more about AI.
This book explains how AI works, using detailed examples of AI in daily life without excessive jargon.
Additionally, it examines how AI influences various fields, highlighting some of its most common applications, including automating tasks and improving decision-making processes.
The best part is that it also provides useful tips for using GenAI tools ethically while maximizing their benefits.
Conclusion
Beyond the buzz, AI's real power lies in the value it creates for businesses.
However, you shouldn't question whether AI should be part of the workflow. Instead, you should consider how soon.
When integrated into business workflows, AI can automate repetitive tasks, improve decision-making and uncover new growth opportunities.
As a Product Growth Partner, we can guide you through the process of building AI tools to drive measurable impact.
Reach out today!
