# Flapping Airplanes

> Source: https://aiwiki.ai/wiki/flapping_airplanes
> Updated: 2026-10-22
> Categories: AI Companies, AI Research
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> Cite as: AI Wiki. "Flapping Airplanes." aiwiki.ai, 22 Oct 2026. https://aiwiki.ai/wiki/flapping_airplanes
> From AI Wiki (https://aiwiki.ai), the free encyclopedia of artificial intelligence. Reuse freely with attribution.

Flapping Airplanes is a San Francisco AI research company founded in 2025 by brothers Ben and Asher Spector and Aidan Smith. It studies ways to make AI use data and computing resources more efficiently. Its research combines model development with software systems for [graphics processing units](https://aiwiki.ai/wiki/gpu), including a megakernel framework.[1][2]

## Company and funding

Ben Spector is the company's chief executive. He co-founded Prod, a student-run startup incubator. Asher Spector completed a doctorate in statistics at Stanford University, while Smith worked at Neuralink for three years while studying at Georgia Tech.[2][3]

Flapping Airplanes announced its seed financing in January 2026. [Index Ventures](https://aiwiki.ai/wiki/index_ventures), GV and [Sequoia Capital](https://aiwiki.ai/wiki/sequoia_capital) co-led the investment. In October, the company announced a larger Series A co-led by Index and Lux Capital. Index said partner Mark Xu would join the board.[2][3][4]

| Announcement | Financing | Announced amount | Lead investors |
| --- | --- | --- | --- |
| January 28, 2026 | Seed | $180 million | Index Ventures, GV and Sequoia Capital |
| October 21, 2026 | Series A | $1 billion | Index Ventures and Lux Capital |

The amounts are the company's announced financing figures.[4][5] Its website also lists NVIDIA, Jump Trading and XTX Ventures among its backers.[5]

Index described an October 2026 team of roughly two dozen people working together in San Francisco. The investor said the company hired for ability and potential rather than formal credentials. Its account described work spanning GPU kernels, pretraining, post-training and [inference](https://aiwiki.ai/wiki/inference), with each layer developed in conjunction with the others.[2]

## Research approach

The company's initial research agenda centered on data efficiency: learning useful capabilities from fewer examples. In its January investment announcement, Index described the founders' hypothesis that the gap between human learning and the data requirements of current AI models leaves room for different learning methods. This was a rationale for research, rather than an announced result showing a particular improvement.[3]

Sequoia described the company as a laboratory for research over long time horizons, with independence resembling doctoral research. Its investment account framed biological learning as inspiration for more data-efficient models and said the company would explore several possible directions. That description did not identify a single model architecture as the company's settled approach.[6]

By October, Flapping Airplanes described a broader effort to develop models and computing systems together. The company argued that making GPUs more efficient and more flexible could enable learning algorithms that are difficult to express with conventional systems. It identified robotics and scientific discovery as intended applications where improved economics could expand AI use.[5]

## GPU systems work

Flapping Airplanes says it has developed a megakernel framework. Index describes a megakernel as running a whole program on a GPU within one kernel, with the aim of reducing the gaps between separately executed steps.[2] The company says its framework can run a complete training process, serve inference and run video games, including combinations of these activities within a single kernel.[5]

A specific company claim is that the framework can overlap inference limited by memory access with training limited by arithmetic computation. It presents this capability as a way to explore unusual model architectures and optimizers. These are descriptions of the company's internal research system, not independently established measurements of performance or data efficiency. The cited October announcements do not provide a reproducible benchmark comparison or a public release of the described framework.[2][4][5]

## References

1. Sequoia Capital. [Flapping Airplanes](https://sequoiacap.com/companies/flapping-airplanes). Company profile, accessed October 23, 2026.
2. Mark Xu and Shardul Shah. [Toward More Efficient AI: Leading Flapping Airplanes' $1B Series A](https://www.indexventures.com/perspectives/toward-more-efficient-ai-leading-flapping-airplanes-1b-series-a/). Index Ventures, October 21, 2026.
3. Shardul Shah and Mark Xu. [Taking Flight: Our Investment in Flapping Airplanes](https://www.indexventures.com/perspectives/taking-flight-our-investment-in-flapping-airplanes/). Index Ventures, January 28, 2026.
4. Flapping Airplanes. [Series A announcement](https://x.com/flappyairplanes/status/2112955212612919318). X, October 21, 2026.
5. Flapping Airplanes. [Official website](https://flappingairplanes.com/). Research description and funding announcements, accessed October 23, 2026.
6. David Cahn. [Partnering With Flapping Airplanes](https://sequoiacap.com/article/partnering-with-flapping-airplanes). Sequoia Capital, January 28, 2026.