Provides practical deployment guidance for software engineers working with data science applications.
Part 1 of a guide on deploying data science code across different environments and platforms.
Getting your data science code running anywhere The post Deploying Data Science Tools: Part 1 appeared first on Towards Data Science.
Author built a claim-checker tool using Codex that incorrectly passed a wrong claim, revealing limitations of rule-based AI verification systems.
Testing shows pasting full chat history costs 20-31x more than lookup methods with no performance benefit for AI memory.
Data scientists need software engineering principles to build AI applications that can evolve, especially as AI agents write code.
Hugging Face is hosting a livestream teaching developers how to achieve significant speed-ups in local LLMs using speculative decoding techniques.
Frontier AI models increasingly incorporate users' public online writings into prompt context, requiring awareness and proactive management.
