Maybe leave programming to AI. Coding by GPTs: A Data Scientist's Perspective
Published: July 27, 2024
The title of the post is a quote from Jensen Huang, CEO of NVIDIA. Couldn't agree more. And a sentiment shared by many fellow analysts.
With over two decades coding and executing data science and analytics projects, GPTs have significantly increased my efficiency. Particularly in code generation, allowing me to focus more on output quality and deployments.
GPT MAGIC
Coding: Best done by AI. Just can't beat the quality and the speed. Ginormous time savings
PRACTICAL CONSIDERATIONS
Impact: A beautiful code by itself doesn't create any impact. It's part of a bigger pipeline.
Grind Still Exists: e.g. API stuff was new to me (FastAPI, GET/POST, transfers). Understanding took time... and then coding was a breeze as I knew exactly what to ask of GPTs
It's not instant coffee: We still need to iterate, check outputs, modify code, debug... until it works. No change there. GPTs do make it faster.
Domain Expertise Matters: e.g. never worked on healthcare analytics. No amount of GPT code would make me an expert quickly
Language understanding matters: Things go very fast with Python. But, React-Node.js web app? I realized quickly that just dumping codes that I don't understand doesn't work well. Though GPTs do speed up learning.
GPTs make mistakes and get stuck sometimes, needing "hooman" help (identifying issues, sharing docs/code samples).
Code privacy a likely challenge, but solutions are in development.
They can't do everything. For instance, deployments (yet. I think..)
With Devin and other full-stack bots coming up, this might all change soon. Eagerly awaiting.
CODING BY GPT: EXAMPLES
Tools I've built using GPT (links in the comments). While small in scale, these tools have helped me understand GPT's application in coding, particularly in areas like LLM apps, APIs, and deployments.
- YFIN Bots: Data transfers via FastAPI endpoints / Flowise AI Platform. Demonstrate GPT's potential for building data pipelines, as well as LLM app deployment within and outside GPT Store.
- Llama Parser Widget: File processing & transfers via API for LLM apps
- Building ML Models with ChatGPT: Demonstrates GPT4's ability to generate ML code, as well run ML models based on prompts
- Mutual Funds Allocation Analyzer (GPT): Automation and data manipulation across multiple Excel files.
All coding by ChatGPT3.5, ChatGPT4, and Gemini ~equally. End-to-end time exponentially quicker than what I could have done alone. Free GPTs are also exceptional.
Sam Altman, "AI could boost programmers' productivity by 30X. Totally agree.