vocabulary
vocabulary at Beyond Market Intelligence is a file of 3 stories. The newest of them: “A small language model that teaches itself column arithmetic.”, “Compact AI runs 400 tokens per second on a laptop CPU with 60 MB”, and “Explore GPT-2's vocabulary through a flyable hyperbolic tree of 32,070 tokens”. This is the kind of result that makes you question what small models actually need. A 250M parameter model that runs at 400 tokens per second on a laptop CPU, no GPU required, is a practical statement about efficiency. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every vocabulary story on Beyond Market Intelligence, newest first.
A small language model that teaches itself column arithmetic.
This is the kind of result that makes you question what small models actually need. A 348M-parameter model, trained on 22.7B tokens, hits 99.4% across nine arithmetic sub-tasks, beating GPT-3's 175B few-shot numbers by a wide margin. The clever part isn't just the accuracy; it's that the model learned place values it was never taught, inventing "millions" and "ten-millions" from zero examples. That's not brute force. That's pattern recognition. We've covered how AI reshapes data ownership, and this feels like a natural extension
Compact AI runs 400 tokens per second on a laptop CPU with 60 MB
A 250M parameter model that runs at 400 tokens per second on a laptop CPU, no GPU required, is a practical statement about efficiency. The 60 MB deployment, achieved through sub-2-bit quantization, and the 1-bit disk cache for long context are the technical details that matter here. The developer trained it on 30B tokens and built a vocabulary from fixed 512-bit codes, which is an unusual choice that shows in the WordSim-353 scores.
Explore GPT-2's vocabulary through a flyable hyperbolic tree of 32,070 tokens
Somewhere in the internet's endless sprawl, a reddit user got tired of flat maps. So they built a better one. This isn't another 2D projection of GPT-2's vocabulary. It's a hyperbolic tree, housing all 32,070 tokens inside a Poincaré ball you can actually fly through. The layout is constructed exactly, with no optimisation or training involved. Trees don't fit well in flat space, but they embed naturally here. Drag, pinch, and tap to explore.