Fatsto

Fatsto is a term that has appeared in online discussions and speculative writing to describe a hypothetical concept in computing. There is no single, widely accepted definition, and the meaning of fatsto varies across contexts. In general, it is used to refer to a class of ideas that combine fast data storage with probabilistic or stochastic processing.

In hardware-oriented discussions, fatsto is described as architectures that integrate storage more closely with computation to reduce data movement, lower latency, and improve energy efficiency. The "fast storage" aspect emphasizes memory technologies or memory hierarchies that can be accessed with near-DRAM speeds; the "stochastic" aspect refers to algorithms or processors that use randomness or probabilistic reasoning to solve problems such as optimization or inference.

In software and AI contexts, fatsto can denote algorithms that exploit probabilistic sampling, randomized optimization, or approximate computing to handle large-scale data with lower compute or energy costs. Some writers use the term to imagine future hardware-software stacks that blend memory and compute units in a neuromorphic or near-memory paradigm.

Because fatsto lacks formal definition, the term is subject to misinterpretation and is rarely used in formal standards. It is primarily encountered in speculative discussions, blogs, and fringe articles. Related concepts include probabilistic computing, in-memory computing, storage-class memory, and neuromorphic architectures.