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Master Google Coding Interview with AI

Updated on Dec 27,2023

Master Google Coding Interview with AI

Table of Contents

  1. Introduction
  2. Background
  3. Testing PPT AI
  4. Interviewing PPT AI
  5. The Misconception of Coding Interviews
  6. The Interview Question
  7. Analysis of the Code
  8. Finding Errors in the Code
  9. Giving Feedback
  10. Final Score and Conclusion

Introduction

In this article, we will be exploring the fascinating world of AI and coding interviews. Specifically, we will be testing an AI named PPT by conducting a mock coding interview with it. As a former Google employee with years of experience in coding interviews, I am curious to see how well this AI performs. Join me as we dive into this exciting experiment and discover the capabilities of PPT AI.

Background

Before we proceed with the mock interview, let's provide some Context. PPT AI has gained significant popularity recently due to its impressive capabilities. As someone who has tested this AI myself, I must admit that I am very impressed with its performance. Today, we will be interviewing PPT AI using the same coding interview style that I employed during my time at Google. This will give us a fair comparison between the AI and a potential new candidate.

Testing PPT AI

If You're new to my Channel, you may be Wondering why I haven't uploaded any videos recently. The truth is, I have been busy adapting to various changes in my life. I no longer have access to the editing tools and equipment I used before, which is why there has been a delay in uploading videos. However, when I came across the idea of interviewing PPT AI, I knew I had to cover it as soon as possible. So, for now, let's focus on testing this state-of-the-art AI.

Interviewing PPT AI

Now, in this first video about interviewing PPT AI, we will be following the same style as a Google coding interview. To kick things off, we will ask the AI a coding question and analyze its response. It's important to note that a coding interview is not solely about finding the correct answer to a programming problem. It's a way to assess how a candidate approaches unfamiliar problems and engage in technical conversations. We will be applying the same principles to our interview with PPT AI.

The Misconception of Coding Interviews

Before we dive into the interview question, let's address a common misconception about coding interviews. Many people believe that providing the correct answer to a programming problem is the ultimate goal. However, the problem itself is just a means to evaluate a candidate's problem-solving skills and their ability to think on their feet. It's also an opportunity to Delve into technical discussions and assess their overall technical knowledge. With this in mind, we will be evaluating PPT AI in the same manner.

The Interview Question

The coding question we will be presenting to PPT AI involves an array of integers and a window size value. The goal is to write a program that finds a window of continuous numbers within the array, where the maximum number in the window is less than or equal to a given value. This question tests the AI's ability to handle arrays, looping, and conditional statements effectively. Let's analyze the code provided by PPT AI and examine its solution.

Analysis of the Code

After reviewing the code provided by PPT AI, we can see that it uses a sliding window approach to solve the problem. The code initializes the sliding window with a starting index and expands it while maintaining the maximum value within the window. If the maximum value exceeds the given value, the window contracts. If a window of size K is found where the maximum value meets the criteria, the starting point of the window is returned. If no such window is found, the function returns -1.

Finding Errors in the Code

During the interview, I noticed an error in the code provided by PPT AI. I decided to test the AI by asking it to find its own error. Upon closer inspection, I found that the code does not handle negative numbers correctly, as it initializes the minimum value to zero. I pointed out this error to PPT AI, and it attempted to rectify it. However, it introduced new errors and failed to update the maximum value correctly within the window. It became evident that PPT AI struggled to identify and resolve these issues without explicit guidance.

Giving Feedback

As part of the interview process, giving feedback is essential. I provided feedback to PPT AI Based on its performance during the coding interview. While the AI was able to provide a solution to the question, it did not solve it optimally. Moreover, the AI exhibited communication gaps and failed to ask for crucial clarifications before proceeding with the code. These communication issues impacted its overall problem-solving process. With these factors in mind, I gave a final score to PPT AI and concluded that it is not yet capable of performing well in a full set of Google interviews.

Final Score and Conclusion

Considering PPT AI's performance in the coding interview, it received a low score overall. While it demonstrated some problem-solving abilities, it struggled with communication and failed to solve the question optimally without significant guidance. It is clear that PPT AI still has room for improvement before it can successfully pass a coding interview at Google. As we wrap up this experiment, it's essential to remember that AI is continually evolving, and further advancements may bridge these gaps.

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