Progress
Inference hardware startup Etched has raised $300 million at a $10.3 billion valuation to build specialized chips for large-scale AI models.
Deep dive
- Specialized Silicon: Etched is moving away from GPUs toward hardware engineered specifically for inference workloads to achieve higher token efficiency.
- Funding Context: The massive $10.3B valuation reflects the industry's belief that 'inference' will be the primary computational bottleneck as model adoption scales.
- Operational Scale: The company is establishing 10-megawatt labs for testing and developing full-stack hardware integration, including custom PCBs and cold plates.
Decoder
- ASIC (Application-Specific Integrated Circuit): An integrated circuit customized for a particular use, as opposed to a general-purpose processor like a GPU.
- FLOPs density: The number of floating-point operations a processor can perform per unit of physical space.
Original article
We’ve raised $300M at a $10.3B valuation, led by Sequoia Capital alongside Andreessen Horowitz, Jane Street, Diffusion, Argo, and SK Hynix. We’re grateful for their support on our journey to Gigawatt-scale.
Our mission is to run the world’s inference. We believe the world’s most powerful models require an entirely new form of computing. Frontier models deserve frontier inference clusters: co-designed chips, packages, PCBs, cold plates, interconnects, and more that push the entire pareto curve on the most demanding workloads.
Today, under 1% of the global population has access to the most advanced AI models. Distributing access will require better technology to deliver more tokens / watt and many Gigawatts worth of compute. Our mission has never been more urgent.
We’ve kicked off fabrication of hundreds of millions of dollars worth of inference clusters. We’ve built a new 10-Megawatt lab fifteen minutes from our office to enable continuous deployment of our first-gen hardware and rapid prototyping of future generations. Production is the product.
We’re excited about bringing our first product to life, and we’re even more excited about what’s to come. If you’d like to work on thousand-chip scale-up domains, in-house SMT lines, and new RL environments for recursive kernel generation, you should join us in accelerating inference.
Fresh dev news, AI-digested daily. Never miss a trend at devoured.fyi