Flapping Airplanes, a startup just a year old, has made waves in Silicon Valley with its remarkable founding team and innovative vision to enhance training for large models using less data. On Wednesday, the company revealed it has successfully secured a $1 billion Series A funding round, co-led by Index and Lux, achieving a valuation of approximately $6 billion.
This funding round follows just nine months after the company’s inception, during which it raised $180 million in seed funding from GV, Sequoia, and Index, marking a significant increase in its valuation from $1.5 billion to a staggering $6 billion.
Notable participants in this latest funding round include previous investors Sequoia, GV, and Kleiner Perkins, along with new backers such as Valor, Atreides, A*, and Nvidia.
Flapping Airplanes was founded by Aidan Smith alongside brothers Asher and Ben Spector. Smith previously co-founded a venture and was a Thiel Fellow, contributing his expertise at Neuralink while studying in college. Asher Spector earned a PhD in statistics from Stanford, and Ben Spector was pursuing a PhD in computer science at Stanford; he also initiated Prod during his time at MIT.
Prod is an exclusive, five-year-old student-led startup accelerator that has garnered recognition as a significant talent incubator in Silicon Valley. Sequoia partner David Cahn, also an investor in Flapping Airplanes, noted in a recent post that the founders are collectively establishing a premier research hub for young innovators focused on artificial general intelligence (AGI).
The founders describe their project as “the world’s most complete megakernel framework,” which is capable of executing complete training runs, processing inference, playing video games, and even handling all these tasks concurrently within a single kernel. A kernel is a program that operates on a GPU, and a megakernel consolidates numerous functions into one program.
Their framework purportedly optimizes the use of GPUs by enabling it to run memory-intensive inference tasks alongside compute-intensive training tasks, ensuring efficient chip usage. The team believes AI technology has immense untapped potential and can develop intelligent systems without relying on vast amounts of data.
Their aim is to create systems that are less costly to train and operate. Asher Spector remarked to TechCrunch shortly after the startup’s launch that a model with a million-fold increase in data efficiency would be much simpler to integrate into the economy.
With the recent $1 billion raised, they are poised to recruit talent and strive to fulfill their ambitious objectives.
