A powerful AI chip is only half the story. Even the most advanced AI hardware needs the right software to reach its full potential. The compiler decides how AI models run on the chip. The runtime manages their execution. Together, they help turn raw computing power into real-world performance. That's why the next generation of AI hardware needs to be designed as a complete system, not just a chip. At ChipForge (SN108), we're taking this challenge to the next level. Our next competition will bring hardware and software together, with engineers competing to build complete AI acceleration systems capable of running modern AI models. Quest 2 is coming soon.

Quest 1 Complete. 1,000× AI inference speedup. In under two weeks, engineers worldwide competed on ChipForge (SN108) to design working AI accelerators. One leading NPU achieved over 1,000× speedup against RISC-V Core in benchmark simulations. This is decentralized chip design in action. Quest 2 is next. And we're aiming higher. #Bittensor #SN108

As advanced LLMs accelerate chip design, the bottleneck is shifting from generating designs to verifying them. The challenge is no longer just how fast we can design, but how confidently we can validate.

Smarter AI needs smarter hardware. Cars that react in milliseconds. Robots that understand their surroundings. Smart devices making decisions in real time. All while keeping data private and power consumption low. That's where NPUs (Neural Processing Units) come in. Specialized chips built to run AI faster and more efficiently, right on the device, without constantly relying on the cloud. At ChipForge (SN108), we're pushing the boundaries of NPU design to power the next generation of Edge AI.

AI is moving into the devices around us. Cameras. Robots. Everyday devices that need small, efficient chips. ChipForge is opening AI chip design to a global network of builders on Bittensor SN108. Decentralized innovation. Intelligence at the edge. ↓

AI is everywhere, but it all runs on chips. McKinsey projects a $2.3T semiconductor market by 2030. Yet chip design remains costly and concentrated. ChipForge, Subnet 108 is bringing silicon design to Bittensor, opening competition to global talent to build practical chips. mckinsey.com/industries/semi…

AI is about to be everywhere. Not just in your phone, but in everything around you. Cars that see and react in milliseconds. Robots that navigate the real world. Cameras that understand what they see. These devices can't always rely on the cloud. They need to make decisions right where they are. AI needs to run right where it's needed. Fast, private, and power-efficient. Making this possible requires a new generation of powerful, energy-efficient AI chips. At ChipForge (SN108), we're changing how those chips are designed.

🚀 The ChipForge NPU Challenge is LIVE on SN108. Quest 001: Design an AI accelerator chip and the software that runs it. Your design will run four real AI models covering voice, vision and sensor tasks. Every answer must match the reference exactly. Then, it’s scored on chip area and speed. The challenge package includes the rules and evaluator, so you can test your design before submitting. Miners compete, validators verify, and the best designs earn rewards. This is our first step from open competition to real hardware. Get started: github.com/TatsuProject/Chip… Follow submissions, scores and the current winner: chipforge.io/leaderboard The challenge is open. Start building.

The ChipForge NPU Challenge goes live tomorrow, October 6, at 9 AM EST AI is no longer limited to the data center. Intelligence is moving into everyday devices: the phones, cameras, sensors and wearables around us. This is edge AI, and it runs on a small, efficient chip called an NPU (neural processing unit). Until now, designing one has taken large teams and large budgets. ChipForge opens this work to everyone. The challenge: design an AI accelerator chip and the software that runs it. How every design is judged: - It runs real AI models from MLPerf Tiny, the industry-standard benchmark for edge AI chips, covering voice, vision and sensor tasks. - Every result is checked bit for bit against the official reference. Only exact answers count. - Performance and chip area are measured with professional chip design tools. Miners compete to build the fastest and most efficient design. Validators run the same open evaluator, so every result can be reproduced. The best designs are rewarded, and each new winner has to clearly beat the last. The result is an open edge AI chip that gets better with every round. It's the first step on our path from open competition to real hardware. Live tomorrow. Start building.