AI vs. AGI vs. ASI – What's the Actual Difference? (bignorthmarketing.com)

This explainer disentangles AI, AGI, and ASI and why those distinctions matter now that large language models and chatbots have pushed AI into the mainstream. “AI” covers today’s narrow systems that excel at specific tasks; “AGI” denotes human‑level, cross-domain adaptability (debated how to measure or define); and “ASI” describes hypothetical intelligence far beyond humans with existential risk implications. The piece highlights a spectrum of expert views—optimists like Jensen Huang and Marc Andreessen see creativity and growth, while voices such as Dario Amodei and Elon Musk warn of mass job disruption and infrastructure limits—illustrating that terminology shapes policy, funding, and public perception. Technically, the article flags two concrete trends: agentic AI (autonomous agents that take actions and orchestrate specialist models) may functionally blur into AGI, and hardware/energy constraints are becoming bottlenecks—global AI electricity use was estimated at 53–76 TWh in 2024 and could triple by 2028, while training frontier models can consume as much power as a small city for days. Timing for AGI/ASI remains contested (some firms predict rapid progress; skeptics point to gaps in reasoning and memory), so near‑term watchers should track agent capability growth, regulation, and large‑scale infrastructure investment that will determine whether advances are accelerated or constrained.