Speak Not of Data Inefficiency

Humans are really bad at comparing themselves to models. Take, for example, Leopold's preschooler graph: Set aside, for a moment, concerns of scaling and RSI, and meditate: what characteristics does GPT-2 share with a preschooler? Rudimentary control of human language The ability to count the R's in "strawberry" incorrectly ... I can't come up with anything else, because these two entities are almost completely disjoint. Is GPT-2 capable of bipedal locomotion, recognizing its mother's voice, or naming people by face? Does a preschooler learn from eight million scraped web pages sourced from Reddit? What exactly is a preschooler "trained" on? Thousands of hours of "multimodal data". Assuming that a preschooler sees at 720p, and is awake for 12,000 hours by the age of 3 (about 11 hours a day), they have consumed at least 27 terabytes of video data at streaming-quality compression, or about 3.6 petabytes uncompressed, not to mention audio and sensorimotor data. [1] In model-size terms, how large is a preschooler? Trillions of parameters, maybe. Beren Millidge's estimate , which assumes only ~1,000 synapses per neuron, puts the whole brain at an effective 10-30 trillion parameters. So surely GPT-2 is much more "data efficient" than humans, wielding "preschooler"-level control of language with a measly 1.5 billion parameters and 40 gigabytes of text! And what about GPT-3, which, with only 175 billion parameters and about 1 terabyte of text, was capable of prose like : GPT’s behav…