🚀 DeepSeek Coder AI: Is This the Ultimate Coding Game-Changer? 🐬 (Open-Source & Powerful!)
AI Summary
Summary: Evaluation of Dips Coding Model
- Introduction
- Claims Dips is the best LLM for coding, surpassing Codex, Codalama, GPT-3.5, and GPT-4.
- Plans to integrate Dips into Visual Studio for local coding.
- Upcoming video on setting up Dips in Visual Studio.
- Dips GitHub Page
- Dips has demonstrated superiority over other models.
- Trained on 2 trillion tokens (87% code, 13% natural language in English and Chinese).
- Using Dips
- Test Dips at cod.dip.com after account creation.
- Coding Tests Conducted
- Error Detection
- Dips successfully identified an error in provided code.
- Natural Language to XML Conversion
- Dips converted a description of people into XML successfully.
- Security Flaw Detection
- Dips identified SQL injection vulnerability and provided a safer code version.
- Did not advise on using HTTPS for sensitive data.
- Problem Solving with Constraints
- Dips wrote a bubble sort function in Java without using built-in sorting functions.
- Algorithm Modification
- Dips modified Dijkstra’s algorithm to handle negative weights using the Bellman-Ford algorithm.
- Game Development
- Dips attempted to create the 2048 game in Python but failed to produce a fully functional game.
- Conclusion
- Despite the last test’s partial failure, Dips is considered the best coding model for coding tasks.
- Future content will demonstrate how to use Dips in Visual Studio Code.
Upcoming Content
- Subscribe for a tutorial on integrating Dips into Visual Studio Code.