Reduce the cost
of intelligence.
ATLAS is an independent research project focused on the systems problem behind efficient AI: preserving useful capability while reducing unnecessary memory and computation.
Reducing the computational cost of intelligence without compromising its capabilities.
ATLAS approaches efficiency as a systems problem. Quantization, memory movement, runtime behavior, and execution placement are connected parts of one computation path.
The project stays deliberately independent. It does not present a fictional lab, team, partnership, or institutional affiliation. It documents a direction and leaves room for evidence to refine it.
Make the trade-off
legible.
Systems over slogans
A lower bit-width is not a result by itself. The path, cost, and quality signal all matter.
Evidence over polish
Unverified data stays unverified until the environment and method can be inspected.
Independent by design
ATLAS is a focused project, not a claim of an institution that does not exist.
JUWON KIM
Founder & Independent Researcher
Working on efficient AI systems through research and engineering, with a focus on model compression, memory optimization, and computational efficiency.