Adding up the hidden costs of generative AI

"For decades, developers have dreamed of a higher-level abstraction that would free them from boilerplate code."

"Generative AI comes closer than ever, with senior engineers already letting it take on more of the work."

"But the vision of an effortless AI-driven future is colliding with hard realities like climbing prices and alarming security issues."

"Could smaller, more specialized models be the way forward?"

Developers have long sought higher-level abstractions to eliminate repetitive boilerplate code. Generative AI now approaches that goal and is already assuming substantial implementation tasks for senior engineers. The shift yields productivity gains but introduces significant challenges, including rising operational costs and concerning security vulnerabilities. These economic and safety pressures complicate expectations of an effortless, AI-driven development future. Adopting smaller, more specialized models could mitigate cost and risk by focusing capabilities and reducing attack surfaces. Strategic selection of model size and scope may become essential for balancing efficiency, affordability, and security in production engineering.

Read at InfoWorld