This story has played out before. Breakthrough innovations that deliver real, tangible value always find a way to get closer to the end user. That place is the Edge of the network. It’s where real people pay for real value, every single day.
We’re at the beginning of that happening with AI right now.
The 5-Layer Cake That Powers AI Today
It took significant compute, latency, and model breakthroughs to deliver AI that’s broadly reliable and useful. As Nvidia recently outlined, today’s AI runs on a powerful “5 layer cake”: Energy, Chips, Infrastructure, Models, and Applications, all operating at the core of the network. Each layer enables the next. Progress in any one layer unlocks capabilities across the entire stack.
But the hard reality comes down to physics. This core infrastructure, meaning the data centers that power everything you use today, needs massive amounts of energy, expensive high-power chips, and fast interconnects to run these models. That’s the classic first phase of innovation: centralized, powerful, and expensive.
Edge devices, the things you wear and hold, suffer directly because of this. Latency issues. Privacy concerns when data travels to and from the core. And in many cases, no connection to the core at all, which means no AI value delivered. Not yet.
We’ve Been Here Before
Two examples from the not-so-distant past are worth paying attention to.
GPS / Location Intelligence
GPS started as a centralized military system in 1993. By 2000 it moved into enterprise navigation. By 2007 it was in the iPhone, and shortly after that, in every fitness wearable you could buy. The key enabler? Low-power chips from companies like SiRF that made GPS viable on small, battery-powered devices.
Video Compression & Streaming
Video compression started in high-end broadcast infrastructure in 2003. By 2007, Netflix was streaming centrally. By 2010, your phone was decoding HD video locally, your TV was streaming directly, and doorbell cameras were compressing and transmitting on their own. Again, the key enabler was low-power chip technology, H.264 chips from companies like Broadcom that made it all possible at the edge.
History is repeating itself with AI. The 5-layer cake is being rebuilt for the edge, and the devices people use every day are about to get dramatically smarter.
femtoAI Is Shipping That Future Today
femtoAI is building the chip and software infrastructure that makes edge AI real. Here’s what that looks like across each layer of the stack:
Energy: 100x less power
femtoAI’s “True Sparsity” AI models and purpose-built chips run at up to 100x lower power and 10x faster, creating AI that finally works at the edge where battery life and responsiveness actually matter.
Chips: 10x smaller
Our Sparse Processing Unit (SPU) architecture mimics how the human brain works, with highly distributed memory and cores. The result: 100x lower power on chips that are 10x smaller, able to fit on devices and cost a fraction of traditional alternatives.
Infrastructure: Drop-in ready
femtoAI chips integrate seamlessly with existing chips and protocols. No changes to existing architectures required. Private by design.
Models: Up to 80% more efficient
Our open developer portal and purpose-built models give developers broad access to highly efficient AI models optimized for the edge. Use ours, build your own, or mix and match.
Applications: A flexible, developer-friendly platform
This is where end users see and pay for the value. Our open platform enables earbuds, hearing aids, smart glasses, digital appliances, speakers, sensors, toys, and more to sound better, adapt to their environment, last longer between charges, and respond naturally to voice.
The Edge Is Next
With chip and technology breakthroughs across all five layers of the stack, end users are about to see incredible new capabilities on the devices they wear, hold, and use every day. Just as GPS found its way into your running watch and video found its way to your pocket, AI is on the same path.
The 5 billion+ edge devices in people’s hands right now are waiting for it. We’re working to make that happen.
