# Chips & LLMs Resources

## Knowledge

### Books
- [**Chip War** — Chris Miller (2022)](https://www.simonandschuster.com/books/Chip-War/Chris-Miller/9781982172015)
  The definitive history of the semiconductor industry: from transistors to geopolitics. Use for: understanding why the value chain fragmented the way it did, the historical formation of today's moats, and US-China tensions. FT Business Book of the Year. Start here.

### Newsletters / Analysis
- [**SemiAnalysis** — Dylan Patel](https://newsletter.semianalysis.com/)
  The highest-signal technical newsletter on semiconductors and AI infrastructure. Covers supply chain bottlenecks (CoWoS, HBM), architecture deep dives, and cost modeling. Requires subscription for full access. Use for: current technical reality behind AI chip demand, NVIDIA economics, foundry dynamics.

- [**The Chip Letter** — Stephen Wass](https://thechipletter.substack.com/)
  Accessible technical explainers on chip history and industry structure. Free. Use for: foundational technical concepts with context.

- [**Stratechery** — Ben Thompson](https://stratechery.com/)
  Strategic analysis of technology companies. Use for: business model analysis, market structure, why certain technical choices compound into competitive advantage.

### Podcasts
- [**Acquired — TSMC (Remastered, 2025)**](https://www.acquired.fm/episodes/tsmc)
  The best single audio resource on TSMC's history, business model, and strategic position. ~4 hours. Use for: understanding why TSMC's moat is so deep and what it would take to replicate it.

- [**Acquired — NVIDIA**](https://www.acquired.fm/search?query=chips)
  Deep history of NVIDIA's pivot from gaming to AI compute. Use for: understanding why NVIDIA's software moat (CUDA) matters as much as its hardware.

### Technical Papers
- [**Chinchilla Scaling Laws** (Hoffmann et al., 2022)](https://arxiv.org/abs/2203.15556)
  The foundational paper on optimal LLM compute allocation. Use for: understanding the relationship between model size, data, and compute — the basis for all hardware demand forecasting.

- [**Attention Is All You Need** (Vaswani et al., 2017)](https://arxiv.org/abs/1706.03762)
  Original transformer paper. Use for: understanding the architecture that every major LLM runs on, and therefore why certain hardware characteristics (memory bandwidth, matrix multiply throughput) dominate.

### Industry Reports
- [**Deloitte 2026 Semiconductor Industry Outlook**](https://www.deloitte.com/us/en/insights/industry/technology/technology-media-telecom-outlooks/semiconductor-industry-outlook.html)
  Annual structured overview. Use for: market sizing, category-level trends, capex cycles.

- [**Quartr — Understanding the Semiconductor Value Chain**](https://quartr.com/insights/company-research/understanding-the-semiconductor-value-chain-key-players-and-dynamics)
  Clean investor-oriented overview of the value chain structure. Use for: quick orientation and financial framing.

## Wisdom (Communities)

- [**r/hardware** and **r/chipdesign** on Reddit](https://reddit.com/r/hardware)
  Practitioner discussions on chip architecture and industry developments. Signal quality varies — check post karma and user history.

- [**SemiWiki**](https://semiwiki.com/)
  Community of semiconductor professionals writing about industry news and technical topics. High trust from practitioners.

- [**HN (Hacker News)**](https://news.ycombinator.com/)
  When SemiAnalysis or major semiconductor news breaks, HN comment threads often contain working engineers and researchers with direct knowledge.

## Gaps
- Need a high-trust resource specifically on AI accelerator architecture (TPU, Trainium, MI300X comparison)
- Need a good resource on advanced packaging (CoWoS, SoIC, FOVEROS) written at a technical but accessible level
- Need a financial modeling resource that translates wafer economics into unit economics for investors