Let's Go To An AI Conference Trivia Quiz

Answer: Artificial Intelligence

AI, or Artificial Intelligence, is the ability of machines to learn, infer and reason. Surprisingly, it was first mentioned in 1955 by American computer scientist John McCarthy. He used the term in a proposal for a summer workshop that year, titled the "Dartmouth Summer Research Project on Artificial Intelligence".

Instead of being explicitly programmed for every single instruction, AI systems work by processing large amounts of data to learn patterns and improve their performance over time. AI systems can digest and learn data, apply logic against the data, and adapt to changing scenarios.

Answer: Gen AI excels at creation of content

Whereas traditional AI excels at pattern recognition, generative AI excels at pattern creation. It can create new content including text, images, video, audio and code based on patterns it has learned from existing data.

Unlike traditional AI, Gen AI does not copy existing content that it has learned, but generates outputs that are statistically likely. The output could be text, videos, code, audio output, or images. In fact, the picture attached to this quiz question is an output of Gen AI. I had simply asked the engine to create an image of an AI conference with multiple booths and vendors.

Answer: Predictions

A large language model (LLM) is a type of artificial intelligence model that has been trained on vast quantities of text data to understand and generate human-like language. They can predict and generate words, sentences, and entire conversations or documents. They are fundamentally based on prediction, specifically predicting the next token (e.g. word) in a sequence. This predictive ability is learned from the massive datasets they are trained on.

An example might be (with myself living in Alabama) its ability to complete my sentence "I like my iced tea with.." with it predicting the next word is likely "sugar," based on the massive amounts of text it was trained on. There are multiple companies that offer LLM services.

Answer: True

Whereas traditional AI models respond to a user's prompt, an agentic AI offers a multistep process that can plan, reason and take action in the real world to solve a problem or carry out a task. It can make decisions and take action independently without constant human input.

For example, an agentic agent can be a virtual travel assistant that plans and books a trip for you. It can understand your request for a "vacation to the mountains in March under $3000", then uses its ability to interact with other systems (like airline and hotel booking sites) to research options, compare prices, and make the bookings for you, all without direct human input.

Answer: Text

Large Language Models don't "see" sentences as we do. Instead, they convert everything into tokens which is a basic unit of text that the model processes. Tokens can be as short as one character or as long as a full word. Spaces, punctuation, and partial words all contribute to token counts. It could be a word, a partial word, a punctuation mark, or even a space!

Tokens are converted into a numerical format that the AI can process. This converts the "language" of the text into the "currency" of the AI. By working with smaller units, AI models can process and analyze vast amounts of text much more efficiently than if they tried to process whole words or sentences at once. Most AI services (like OpenAI, Anthropic, Gemini) charge based on the number of tokens processed.

Answer: Creativity

In AI, temperature is a parameter that controls the randomness and creativity of a model's output.

A low temperature, e.g. 0-0.3, will produce more predictable and less random results. The model will choose the most likely words, and outputs will be more factual and consistent. This is useful for tasks that require accuracy and consistency, such as summarizing factual information or generating code.

A high temperature, e.g. 0.7-1.0, will create more randomness in results with a larger variety of words - sometimes less common. Outputs will be more creative and varied. This encourages more varied, creative, and novel outputs, which is ideal for creative writing or brainstorming.

Answer: Hallucination

There are a variety of reasons why these Large Language Models hallucinate, and often they relate to LLM training data or LLM design. LLMs are designed to produce answers using statistical probability based on their training data. If the training data is incomplete or not up-to-date, gaps will occur, causing the AI engine to fabricate information to fill the gaps.

When hallucinating, the AI has no idea it is wrong, it's simply using its available resources and most plausible output based on patterns and statistical probability. However, if left unchecked, AI hallucinations may result in legal, ethical, and economic issues.

Answer: False

RAG stands for Retrieval-Augmented Generation. It gives AI models access to external, specific information. These can be text files, Office documents (e.g. *.pdf, *doc, etc.), as well as audio and visual files.

The AI model will search these files looking for information. Next it will retrieve the information as context. Finally, it generates an answer. An example would be an AI model "reading" a company's sustainability report as a .pdf. Then it responds to a question about that document as if it were a librarian looking up an answer.

Answer: Facial recognition

AI is built into everyday life in many ways people do not think about. A perfect example is unlocking your phone using facial recognition.

The phone first uses its camera to detect a face in the image. Advanced systems create a 3D map of the face, measuring the distance between features and capturing depth information with infrared light. This data is converted into a unique numerical code, or "faceprint". When you look at the phone, AI compares the new faceprint to the one stored on the device in order to, hopefully, unlock it.

Answer: As a partner

AI is not meant to replace humans but to help us as a powerful tool. Start with small tasks like chat-bots to ask open ended questions or to send hands-free text. Use "smart" appliances like refrigerators or thermostats to help with everyday tasks. Use AI image generators to brainstorm designs. (Most of the photos in this quiz were done with AI). Have fun with it!