Founder & CEO of @servamind · PhD in AI · building the data layer AI runs on: encode once: train, fine-tune & serve for less. Papers + open source this fall.
I've spent my career on the underlying math of AI — and the question of what it actually takes to get to a Data-from-TNG level of intelligence.
Now I'm building @servamind: a model-agnostic data layer for AI. Encode your data once, and the same file works across training, fine-tuning, and inference — less runtime, less power, targeting ~1/10th the cost.
This fall: two research papers and an open-source release, with a repro kit so you don't have to take our word for anything.
Follow along — I'll be posting about the tokenizer tax, why data preparation is AI's most ignored bottleneck, and what we find as we run the benchmarks.
@TheGeorgePu Hey we have the same question! We’re cooking a massively faster 70b for several families. So would love to resurface this or see what ya’ll really want.