Top Programming Languages 2025
- This article explores the potential impact of AI, particularly Large Language Models (LLMs), on the future of programming languages.
- * AI struggles with less-used languages: LLMs perform considerably worse when coding in languages with smaller datasets and less online presence.
- * Abstraction: Languages simplify data processing. This has been a goal since early languages like Fortran and Cobol.
the Future of Programming Languages: A Summary
This article explores the potential impact of AI, particularly Large Language Models (LLMs), on the future of programming languages. Here’s a breakdown of the key points:
The Problem: AI Favors Popular Languages & Hinders New Ones
* AI struggles with less-used languages: LLMs perform considerably worse when coding in languages with smaller datasets and less online presence.
* AI doesn’t help new languages gain traction: While research aims to make AIs more versatile,it doesn’t inherently promote the adoption of new languages.
* New languages arise from programmer needs: Historically, new languages emerge to solve specific problems or address design philosophies (e.g., annoyance with semicolons, basic views on computation). AI, by smoothing over the issues with existing languages, might stifle the motivation to create new ones.
* Potential for stagnation: the article questions whether the popularity of current languages will become “frozen in time” due to AI’s ability to address existing frustrations.
The Core Functions of Modern languages
* Abstraction: Languages simplify data processing. This has been a goal since early languages like Fortran and Cobol.
* Preventing Errors: Modern languages aim to prevent programmers from making mistakes that lead to tough-to-debug code (“shooting themselves in the foot”). This was heavily influenced by Dijkstra’s “Go To Statement Considered Harmful” paper, advocating for structured programming.
The Illusion of Structure
* Underlying Reality: It’s all Go Tos: Despite the structured nature of modern languages (functions, blocks), at the CPU level, program flow is ultimately controlled by jumps – conditional, unconditional, and subroutine calls (essentially, Go Tos).
* Data Types Dissolve: Strict data types, designed for safety, ultimately translate into anonymous bits in memory.
The Question for the Future: How Much Structure Does AI need?
* AI-assisted hardware design offers a clue: Research like dall-em in AI-assisted hardware design suggests that a highly advanced coding AI might not need the same level of abstraction and error prevention that humans do.
In essence, the article poses a thought-provoking question: If AI can effectively navigate the complexities of existing languages, will the drive to create new ones diminish, possibly leading to a less diverse and innovative landscape of programming languages?