RAMageddon, AGI, and AI Agents The AI Terms Everyone Is Talking About Right Now
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Some AI terminology has moved from technical jargon into mainstream conversation so quickly that it is worth pausing to establish exactly what these terms mean before they become further abstracted by hype. AGI — artificial general intelligence — is perhaps the most consequential and most loosely defined term in the entire field. It generally refers to AI that is more capable than the average human at most tasks, but even that definition is contested: OpenAI describes it as a system that outperforms humans at most economically valuable work, Google DeepMind frames it as AI at least as capable as humans at most cognitive tasks, and experts at the frontier of AI research openly disagree on the specifics. The practical implication is that when a company claims to be building toward AGI, they may mean something meaningfully different from what a competitor means by the same phrase. An AI agent is a more grounded concept: it refers to a system that can perform a series of tasks autonomously on your behalf — filing expenses, booking travel, writing and debugging code — by drawing on multiple AI systems and taking multistep actions without requiring human input at every stage. Coding agents are a specialized version of this, capable of writing, testing, and debugging software across entire codebases with minimal oversight.
RAMageddon is the newest term to enter the lexicon and captures a genuinely significant economic trend: the AI industry's insatiable demand for random access memory chips is creating a supply shortage that is flowing through to consumer electronics, gaming hardware, and enterprise computing in the form of higher prices and constrained availability. The largest AI labs and tech companies are purchasing memory at a scale that leaves less for everyone else, and that dynamic is not expected to resolve quickly. Open source versus closed source is another distinction that has become one of the defining debates in the industry: open source AI means the underlying model weights and code are publicly available for anyone to use and modify, as with Meta's Llama family, while closed source means you can use the product but cannot inspect how it works, as with OpenAI's GPT models. The open source debate matters because it touches on questions of safety, competition, independent oversight, and who ultimately controls the most powerful AI systems — questions that are becoming more consequential as model capabilities continue to advance rapidly.