Flapping Airplanes, a year old AI lab building new GPU primitives for more data efficient learning, raises a $1 billion Series A led by Index and Lux
We’ve spent the past year developing new primitives for GPUs. We believe this enables new algorithms to change how machines learn, open new markets, and dramatically reshape AI’s cost structure. We have raised a $1 billion Series A, co-led by Index and Lux.
Context
A billion dollar first round for a lab betting on doing more with less data and compute shows investors backing alternatives to simply scaling up.
Flapping Airplanes is an AI lab whose leaders include Ben and Asher Spector, that aims to train models with far less data. TechCrunch reported the round values it at about $6 billion, up from $1.5 billion at its $180 million seed nine months ago.
Deep dive
On October 21, Flapping Airplanes posted that it has spent the past year developing new primitives for GPUs, which it believes enable new algorithms that change how machines learn, open new markets and dramatically reshape AI's cost structure. It said it raised a $1 billion Series A, co led by Index and Lux.
TechCrunch reported the round values the company at about $6 billion, four times its $1.5 billion valuation at a $180 million seed round from GV, Sequoia and Index nine months earlier. The founders describe their work as a megakernel framework, where a kernel is a program that runs on a GPU and a megakernel bundles many tasks into one, able to run training and inference together so the chip is rarely idle.
Index Ventures wrote that the company has a couple dozen people working in person in San Francisco across the stack, from GPU kernels to pre training, post training and inference. In a talk at a Sequoia event this year, the founders said data scarcity, not just compute, limits where AI can be used, and that their goal is far more data efficient models. They have not described their algorithms, calling them core intellectual property.
The claims about reshaping AI costs are projections; the post gives no benchmarks or products.
What to expect next
Watch for Flapping Airplanes to publish results showing its methods train models with less data or run GPUs more efficiently. Its first model or product will show whether the approach works outside the lab. Also watch whether its GPU tools are released openly, and whether other labs adopt megakernel techniques. How it spends the $1 billion on hiring and compute will show how fast it plans to move.