Explore future of tech: AI/ML, ChatGPT, industry uses w/ Ed Bailey & Steve Koelpin

Introduction

Welcome to the Cribble live stream! I’m Ed Bailey from Cribble, serving as the tech evangelist alongside Steve Koelpin, a recognized expert in machine learning. Over the years, we have tackled various data and observability challenges, and recently, the impact of AI and ML—particularly ChatGPT—on the engineering landscape has been a recurrent topic of discussion. It was only fitting that I reached out to Steve for an in-depth exploration.

Meet Steve Koelpin

Hi, I’m Steve Koelpin, and I’ve been an engineer for nearly a decade, specializing in solving complex issues through data. I have extensively utilized machine learning and am now delving into artificial intelligence. Today, we will discuss how AI, especially ChatGPT, can benefit engineers in their everyday tasks.

Topics of Discussion

We will cover several key topics regarding the application of AI and machine learning in engineering:

1. Summarizing Unfamiliar Topics: With technology evolving rapidly, staying updated with new trends is critical.
2. Learning New Things Quickly: Engineers require resources to help keep pace with technological changes.
3. Generating Better, Faster Script Results: Leveraging AI to enhance programming scripts and queries.
4. Troubleshooting Assistance: Using AI as a virtual assistant to resolve issues efficiently.
5. Evaluating Tools: Accelerating the assessment and understanding of available tools in the market.

Summarizing Complex Topics

A recent trend is observability, or O11y, which refers to understanding a system's internal state through data collection and analysis. We asked ChatGPT to explain observability in simple terms, and it aptly described it as having visibility into computer systems.

To add a touch of humor, the AI gave us sports analogies reminiscent of Stone Cold Steve Austin and Snoop Dogg, showcasing its ability to adapt explanations to various styles and audiences.

Enhancing Script Writing

With a prompt to write a Splunk query, ChatGPT generated helpful code to analyze firewall data, demonstrating how it can empower users unfamiliar with command syntax. Steve highlighted how beneficial AI could be in speeding up query creation and assisting users in crafting effective commands.

Furthermore, the AI provided recommendations to optimize the search process, like using index fields and adjusting search strings, reflecting its learning capability.

Troubleshooting Queries

Next, we tackled troubleshooting queries. By presenting a flawed example query to ChatGPT, we observed how it identified issues with the syntax and provided suggestions for correction. Although it caught some errors, it also misclassified certain aspects, indicating areas for potential improvement.

Creating Regex and Scripts

We explored the potential of ChatGPT in generating regular expressions and automation scripts—tools for engineers that typically take considerable time to construct manually. The AI created a simple Python calculator and provided detailed explanations, illustrating how it can serve as a valuable assistant in programming.

Evaluating Tools in the Market

Regarding tool assessment, Steve discussed the significance of keeping up with evolving technology. We asked ChatGPT to list observability pipeline tools, and while it offered some suggestions, certain recognitions, like Cribble, were missing. It highlighted the limitations of relying solely on AI for comprehensive information.

Conclusion

In summary, ChatGPT showcases impressive capabilities in assisting engineers across various tasks, from summarizing complex topics and generating queries to troubleshooting errors and evaluating tools. Though it has room for growth, particularly in live applications, the technology is poised for exponential improvement, promising to become an invaluable aid for engineering teams.

Keywords

AI, Machine Learning, ChatGPT, Engineering Efficiency, Observability, Troubleshooting, Query Optimization, Script Writing, Regex, Tool Evaluation

FAQ

Q: How can AI and machine learning help engineers?
A: AI and machine learning can assist engineers by summarizing unfamiliar topics, generating efficient scripts, providing troubleshooting support, and facilitating quicker evaluations of tools.

Q: What is observability (O11y)?
A: Observability refers to the ability to understand the internal state of a system by collecting and analyzing data, often through metrics, traces, and logs.

Q: Can ChatGPT help write code?
A: Yes, ChatGPT can generate scripts and even provide explanations for the code, making it easier for engineers to understand and modify it.

Q: What are some limitations of using ChatGPT?
A: ChatGPT may misclassify technical data or provide incomplete answers; thus, it should be used as a supplementary tool rather than a singular source of truth.

Q: Is AI evolving rapidly?
A: Yes, with continuous investments and innovation, AI capabilities are expected to improve exponentially, leading to more effective applications in various industries.