Flapping Airplanes was founded by Aidan Smith and brothers Asher and Ben Spector. It raised a $180 million seed round and, in October 2026, a $1 billion Series A co-led by Index and Lux. See our report.

What the company does

Flapping Airplanes is an AI research lab whose stated aim is to train large models with far less data than today’s systems consume. Its founders describe the goal as building intelligent systems “without ingesting half the internet,” according to TechCrunch. The company has not published a model or benchmark scores in the coverage we reviewed, so its data-efficiency claims remain an aspiration rather than a measured result.

Funding and backers

TechCrunch reports that the $1 billion Series A, announced on October 21, 2026, was co-led by Index and Lux at a reported $6 billion valuation, four times the $1.5 billion valuation of its earlier $180 million seed round. Participants named in the report include Sequoia, GV, Kleiner Perkins, Valor, Atreides, A* and Nvidia. The valuation is described as reported, not confirmed by the company.

Technical approach

The founders say their software work centers on what they call “the world’s most complete megakernel framework.” A kernel is a program that runs on a GPU, and a megakernel bundles many tasks into one program instead of launching many small ones. The company claims this lets it overlap memory-bound inference with compute-bound training so the chip is rarely idle. These are the company’s claims as relayed by TechCrunch, and we have not seen independent measurements.

Why it matters

Most frontier labs compete on scale. A lab that needs far less data and compute per capability would change who can afford to build advanced models, which is why investors are funding it before any public product. The counterpoint is that data efficiency has been a research goal for years without replacing large-scale pretraining at the frontier.

Our full report, Flapping Airplanes raises $1 billion, covers the round and the team in more detail. For how such rounds work, see how AI startup funding works.