T-SQL Tuesday #162 Invitation – Data Science in the time of ChatGPT
Welcome to this month's T-SQL Tuesday blogging invitation. Our topic for this month is Data Science, specifically exploring the aspects of Data Science with the presence of Chat GPT 4.0. Chat GPT is a Large Language Model based on the Generative Pre-trained Transformer architecture. It uses deep learning algorithms to generate sequences of tokens that make up a piece of text. With the help of probabilities of words and their sequences, it is great for providing human-like responses to natural language queries, making it ideal for a conversation-like experience.
Our goal is not to debate whether the end of data science is near or whether Artificial General Intelligence (AGI) will replace data scientists. Instead, we want to hear from you about how you have embraced the use of Chat GPT and what were your first impressions. How did it help you (if at all)? What did you use it for? Have you encountered any traps?
Imagine using SQL, R, Python, Julia, or Scala and being able to ask Chat GPT anything, and it will return a relatively coherent and good answer. If you need an explanation, it will excel. Here is a list of some scenarios where you might have used Chat GPT:
- Debugging code
- Answering general knowledge questions
- Generating text and articles
- Classifying text
- Translating text
Feel free to make a general comparison and add some explanations on how Chat GPT has helped you. Also, mention if its usage has compromised your work as a data scientist in any way, positively or negatively.
As we know, many controversies have emerged around the use of Chat GPT, with some European Union countries banning it. There is a concern not only about its impact on humanity and empathy, but also about the misuse of personal data, privacy issues, and leaking of relevant corporate information.
Have you considered the responsible usage of Chat GPT? Here is a list to help you:
- Training the model on snippets of text, instead of entire documents
- Limiting access to the model
- Testing results with sample data before using it in production
- Providing explanations for the output
Have you tried using Chat GPT more responsibly? Which cases have you come across, and did it have any consequences for you? Share your experiences with us.
In conclusion, Chat GPT offers interesting answers and is an excellent learning source. However, it may be more helpful for entry/junior positions than experienced data scientists who work on abstract and complex topics frequently. It is important to use this technology responsibly and be aware of its limitations and controversies.
