AI and how AI predicts stuff about prices

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-explorers-finance-AI-and-how-AI-predicts-stuff-about-prices-r10a7

1. Why are AI predictions described as 'smart guesses' instead of certain answers?

   1. AI looks at past information to make an educated guess about what might happen
   2. AI is not very intelligent and just randomly guesses
   3. AI predictions are always wrong so they are just guesses
   4. AI has access to magic eight balls that tell the future

2. A new video game comes out that nobody has ever bought before. What can AI reliably predict about its price?

   1. Exactly how much it will cost next month
   2. Nothing at all based on past data
   3. Something about how similar games have been priced in the past
   4. Whether it will be a success or failure

3. If you notice your favorite chips go on sale every year around the Super Bowl, what does this represent?

   1. A pattern that AI could learn and use to predict future sales
   2. A promise that they will go on sale this year
   3. A coincidence that does not mean anything
   4. An error in the store's pricing system

4. An AI notices that umbrella sales increase every time it rains. Why might the AI's prediction about rainy days be useful to a store?

   1. The AI can guarantee that it will rain on specific dates
   2. The AI can make it rain whenever the store needs money
   3. The AI can force people to buy umbrellas
   4. The AI can predict when to stock up on umbrellas based on past rain patterns

5. Why can't AI perfectly predict what will happen to prices in the future?

   1. The future has never happened before, so there is no data about it
   2. AI is not smart enough to understand money
   3. AI computers are broken
   4. Unexpected things can always happen that are different from the past

6. What does the phrase 'AI gets surprised sometimes' mean in the context of price predictions?

   1. AI only predicts things that are already guaranteed to happen
   2. AI sometimes makes predictions that turn out to be wrong
   3. AI has feelings and can be emotionally shocked
   4. AI is programmed to act surprised when it makes a mistake

7. A company wants to use AI to predict winter coat prices next year. What data would be most helpful for the AI to analyze?

   1. A list of fictional future prices
   2. Random numbers generated by a computer
   3. Prices of winter coats from previous years
   4. What people had for breakfast last week

8. Why might an AI prediction about lemonade sales in summer be more reliable than a prediction about a brand new energy drink?

   1. Because AI does not like new things
   2. Because lemonade is more fun than energy drinks
   3. Because summer happens every year and lemonade has a long sales history
   4. Because the energy drink company pays AI to make wrong predictions

9. If an AI predicts that ice cream sales will be high in July, what are the limitations of this prediction?

   1. The prediction might be right or wrong—it is a guess based on past patterns, not a certainty
   2. The prediction is impossible to verify
   3. The prediction means ice cream will definitely sell out
   4. The prediction is definitely wrong because AI cannot predict food sales

10. What would happen to an AI's price predictions if a major company that sells a popular product suddenly went out of business?

    1. The AI would stop working entirely
    2. The AI might make less accurate predictions because this is a new situation
    3. The AI would predict higher prices for that company's products
    4. The AI would keep predicting the same prices as before

11. A student notices that the price of school supplies drops right before the school year starts. This is an example of what?

    1. A pattern that could be used to make predictions
    2. A promise that prices will drop every year
    3. Something that AI can never understand
    4. An illegal business practice

12. What makes AI better at guessing price patterns than a person who only looks at one year of data?

    1. AI does not need data to make predictions
    2. AI is magic and can see the future
    3. AI only guesses based on the most recent year
    4. AI can look at much more information from many more years

13. If an AI has never seen a product like a new type of flying car before, how can it still make some prediction about its price?

    1. It cannot make any prediction at all
    2. It simply guesses randomly without any information
    3. It uses a crystal ball to see the future
    4. It can look at prices of similar products like cars and airplanes

14. Why is it important to remember that AI price predictions are 'not sure things'?

    1. Because prices never change and predictions are useless
    2. Because AI was designed to be wrong on purpose
    3. Because AI is always wrong and should not be trusted
    4. Because unexpected events can happen that change what actually occurs

15. A store owner uses AI to predict that beach towels will sell well in June. The owner decides to stock up on towels. What is the smartest way to think about this prediction?

    1. The prediction is always wrong so stocking up is foolish
    2. The prediction is a smart guess based on patterns, but the owner should still be prepared for unexpected outcomes
    3. The prediction is definitely true so no risk is involved
    4. The AI is guessing without any reason