The hottest Silicon Substack posts right now

And their main takeaways
Category
Top Technology Topics

Huang's Law

The Chip Letter • 6115 implied HN points • 18 Jun 25
🕹 Technology AI Hardware Computing Silicon Performance
  1. Huang's Law suggests that the performance of AI chips is improving much faster than what we used to call Moore's Law. It claims chips double their performance every year or so, which is a big leap forward.
  2. This new law emphasizes performance improvements related to AI, unlike Moore's Law, which was mostly about the number of transistors. It's all about how quickly these chips can process complex tasks.
  3. However, some experts think Huang's Law might not last as long as Moore's Law. While it's exciting now, it's still uncertain if this rapid improvement can continue in the future.

NVLink Fusion: Embrace, Extend, Extinguish

Mule’s Musings • 417 implied HN points • 27 May 25
🕹 Technology AI Hardware Networking Silicon Computing
  1. Nvidia has a strong edge in the market with its NVLink technology, allowing fast communication between chips. This positions Nvidia favorably against competitors who are still developing their own solutions.
  2. By licensing its C2C technology and selling NVLink chiplets, Nvidia is opening its technology to others while still maintaining a competitive advantage. This strategy helps Nvidia grow its influence and solidify its market position.
  3. The 'embrace, extend, extinguish' strategy means Nvidia is likely to dominate the market by allowing others to use its technology while quickly outpacing them with its own products and innovations.

Every AI Model Needs Its Own Chip, says Taalas

More Than Moore • 4 HN points • 06 Mar 24
🕹 Technology AI Silicon Hardware Startups
  1. Start-ups are focusing on developing silicon dedicated to processing AI workloads which can offer efficiency and cost benefits.
  2. Taalas, a new startup, aims to create architecture and chips that are model-specific, breaking the efficiency barrier in AI silicon.
  3. The future of AI hardware may lie in dedicated, fixed chips designed at the time of deployment to meet specific compute workload needs, potentially revolutionizing machine learning technology.
Get a weekly roundup of the best Substack posts, by hacker news affinity: