TryHackMe — The Building Blocks of AI Walkthrough (Direct Answers)

Note: These are the answers I am writing after completing my rooms on TryHackMe’s official website and all the credit of it’s content directly goes to TRYHACKME. I have paid utmost attention in revealing only the answers that are available on any other platform and not to compromise with the learning process of users on TRYHACKME!

Task 1 Introduction

1. I’m ready to learn about AI/ML security! No answer needed

Task 2 Introducing TryHackMe’s AI Agent Platform

Just open the agent and play with it.

Task 3 What is AI and Machine Learning?

1. What is the term for when a model becomes too familiar with its training data and fails to generalise to new data? Overfitting
2. What is the subfield of AI that enables systems to learn from data without being explicitly programmed? Machine Learning

Task 4 Machine Learning Algorithms

1. Which category of ML algorithm learns by receiving rewards or penalties based on actions taken in an environment? Reinforcement learning
2. Which category of ML algorithm uses a small amount of lavelled data to guide learning across a larger unlabelled dataset? Semi-supervised learning
3. What’s the flag? THM{something related to the algorithm} (Donot cheat. Uplift your skills and try to find the flag on your own)

Task 5 Neural Networks and Deep Learning

1. What is the first layer in a neural network that receives raw input data? Input Layer
2. What term describes the weighted connections between nodes in a neural network? Synapses
3. What’s the flag? THM{ the cell of the brain} (Try to find on your own)

Task 6 Large Language Models

1. What type of neural network, introduced by Google in 2017, powers modern LLMs? Transformer neural networks
2. What is the name of the process where humans review and flag model outputs to refine its behavior after pre-training? RLHF
3. What mechanism do transformer networks use to assign different levels of importance to different words in a sequence? Attention
4. What algorithm is used to adjust a model’s parameters based on the difference between its prediction and the correct answer? Backpropagation

Task 7 Practical

1. What’s the flag? THM {you have to try}

Task 8 Conclusion

1. All done! No answer needed