AI Made Easy: The Non-Techie's Cheat Sheet for Party Small Talk

Artificial Intelligence (AI) is a buzzword you're likely to hear everywhere, from professional conferences to casual conversations. As the guy often 'jabbering' about it, let me guide you...

So What is AI?

Artificial Intelligence (AI) is a field of computer science focused on creating machines capable of performing tasks that typically require human intelligence. AI is not new. It has been hiding in plain sight in things like Google Maps, Siri, and Alexa. You may have heard names like ChatGPT, BERT, or Copilot, these are Large Language Models is a type of AI designed to understand and generate human language.

First nerd term to define. A "model" is a system that has been trained to recognize patterns, make decisions, or generate responses based on data.

This latest generation of Large Language Models is different in its ability to emulate human cognition very well. A user-friendly and conversational interface makes it incredibly accessible: it's as easy as striking up a chat. AI used to be the exclusive playground of tech giants and academic researchers. Now, it's in the hands of anyone with an internet connection and a spark of curiosity.

Is it Magic?

Here are the basics of how a Generative Pre-trained transformer (yes, that's where GPT comes from) Large Language Model (LLM), works. Think of a prompt as a key. You type something like “Four score and what now?” into a chat box and hit enter. When you send a prompt, it's like turning this key. This action triggers a series of rapid mechanisms (algorithms) that scan through a labyrinth of patterns, attempting to match your key's pattern with the correct response pattern. The AI sifts through countless bits of data to find the pattern that best matches your question. Almost instantaneously, the correct pattern is selected, the lock opens, and the response is delivered to you, “The phrase 'four score and seven years ago' is from Abraham Lincoln's Gettysburg Address…”.

So, what happens if there is no exact match? What if there is no match at all? This is what separates these models from other “programs”. It's not just matching patterns; it's grasping context. This is the distinction between AI and simpler pattern-matching programs and that's a game-changer.

It's Not Magic?!

What these types of Artificial Intelligence have in common is, they are trained on vast amounts of text data, to learn a wide range of linguistic patterns, and styles. This can include books, articles, websites, and other text sources. They consist of multiple layers of neural networks – to capture and process complex patterns in data. Particularly in transformer-based models, attention mechanisms allow the model to focus on different parts of the input simultaneously, which is crucial for understanding context and generating something coherent.

The amazing capabilities of these LLMs is not due to a single discovery. The creation and operation of a system like ChatGPT involves several key components and technologies such as massive processing power and access to huge amounts of data (the Large in LLM) and innovations in neural network architecture (designed to mimic the way the human brain processes information).

Artificial intelligence, while mimicking human behavior is not human. This can be forgotten because it is easy to anthropomorphize AI, expecting it to understand things like a human. While these models generate responses based on learned patterns, it's important to remember that this doesn't equate to genuine human intuition or creativity. Models like ChatGPT do understand and create responses based on context; however, their understanding is limited to its training and the immediate conversation.

AI, Am I Right?

So, this gives you all you need to nod sagely while someone drones on about Artificial Intelligence near the punch bowl. AI is not just another buzz word; its potential is immense. There is a great debate about how to manage the integration of Artificial Intelligence and the ramifications. It is important to have diverse voices to help shape this conversation. Embracing diverse voices in discussions around AI ensures richer perspectives and fairer outcomes, making sure the technology benefits everyone.

I do suggest you try something like ChatGPT yourself.

Ask it some questions. Try” What are good conversation starters at a company party?” You won’t be disappointed; it may make an interesting story.

Cheat Notes and Bonus Points:

• Algorithm: A set of rules or instructions that systems follow to perform a task or solve a problem.
• Prompt: Input that the AI responds to.
• Prompt Engineering: Clear and precise instructions to a computer program that understands language so it can give you the answers or help you need.
• Generative: The model is designed to generate new content.
• Pre-Trained: The model is trained on a large dataset before being fine-tuned for specific tasks.
• Transformer: An advanced type of neural network architecture used in language processing, excelling in understanding context and relationships in text.
• Machine Learning: A subset of AI where machines learn from data and improve their performance over time.
• Predictive Analytics: The use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data.
• Hallucination: This is when an AI model generates incorrect, nonsensical, or unrelated output.

This article was fine-tuned with a touch of AI assistance checking grammar, spelling, and catching the more than occasional typo. The heavy lifting, however, was all human - proving that AI is a handy sidekick, not the hero of the story.