bio

i'm 21. built my first pc at 11. homebrewed my 3ds for pokemon nuzlockes.
hex-edited games to get outside the map.

rules are silly. nothing's impossible till physics proves it.

technion pre-engineering, left after a missile hit campus. economics undergrad at binghamton.

taught myself ml from scratch, december 2025.

spent six months on hardware-enforced alignment.
pivoted, it only served closed labs (safety is not control).

now: building an open source ai efficiency lab.
frontier ai, radically cheaper to train and run.
science shouldn't be this expensive.

looking for a cofounder (email me).

conceptual builder, not traditional coder. i design, my agents work.

founding engineer at duino, now technical advisor.

upstream

projects

• turboadam drop-in adam replacement. 9.845x smaller optimizer state than adamw, 6.50 bits per parameter. +1.224% on tinystories, -0.094% on wikitext-103, matched 500-step gpt-2 124m runs. on pypi.
• dcaf and noosphere interpretability tools. circuit discovery using fine-tuning as a controlled perturbation, and a 3d explorer for embedding spaces.
• arrow field embeddings keeps what a 3d projection throws away, encoded as arrow direction and magnitude. benchmarks in progress.
• easywheels prebuilt cuda wheels, no 30 to 120 minute source builds. retired when uv's team started building the same thing.

research

• for the lab, in development an ffn that skips about 85% of per-token ffn compute, within about 6% of standard in small-scale tests. a low-bit residual master weight at about 89% perplexity parity, 6.75 bits. optimizer infrastructure that generates its own kernels. a ternary training format.
• navier-stokes an enstrophy-weighted directional fisher information regularity criterion. conditional, not a proof of global regularity. many rounds of ai red teaming, no human expert has checked it.
• entropy-attention and r-attention two attention mechanisms i designed and tested. neither beat standard attention across an 8-task battery. published anyway.