Golang (Go) is emerging as a compelling alternative to Python for artificial intelligence applications that prioritize performance, concurrency, and scalability. While Python maintains dominance in research and model development due to its extensive ecosystem of specialized libraries, Go offers significant advantages in production environments. This article explores the growing intersection between Go and AI, examining its performance benefits, memory efficiency, and deployment simplicity. The discussion covers key libraries like Gorgonia and GoLearn, practical implementation patterns including microservices architecture and hybrid language approaches, and real-world case studies demonstrating Go’s effectiveness for recommendation engines, NLP services, and edge computing. Current limitations regarding ecosystem maturity and GPU acceleration are balanced against promising future directions that position Go as an increasingly viable option for production-focused AI systems.
Keywords: Deployment, Golang, Performance, concurrency, scalability
