Core Viewpoint - Normal Computing has successfully developed the world's first thermodynamic computing chip, CN101, designed for AI and HPC data centers, achieving unprecedented computational efficiency compared to traditional silicon methods [2][4]. Group 1: Chip Technology and Efficiency - The CN101 chip utilizes thermodynamics and other physical principles, diverging from traditional silicon computing, and is closer to quantum and probabilistic computing [2][4]. - The chip can achieve up to 1000 times energy efficiency in AI training tasks, significantly enhancing performance within existing energy budgets [4][5]. - Normal Computing's approach leverages randomness and noise, which are typically detrimental in standard electronics, to solve problems, thus expanding the algorithmic space for applications ranging from scientific computing to AI [2][4]. Group 2: Applications and Future Roadmap - CN101 is specifically designed for linear algebra and matrix operations, crucial for engineering, scientific computing, and optimization tasks [4][5]. - The roadmap includes the release of CN201 in 2026 for high-resolution diffusion models and CN301 in late 2027 or early 2028 for advanced video propagation models [6][7]. - The successful tape-out of CN101 marks a historic moment for thermodynamic computing, paving the way for future developments in AI workloads [6][7].