Writing
Notes on significant moves in AI, and how to build agents, RAG and evaluations that hold up. Every post opens with a short answer, then shows the evidence.
Writing is seed pods drifting down a thread of light · Stockcake · Stockcake (public domain).
- Between two Samsung lines, the eyes post: the shortage is now a payout storyAI news · 29 Oct 2026
Jukan's wordless 👀👀 post sat between Samsung's 2027 shortage line and its buyback remarks: what repriced that morning was the KRW 55–75 trillion return plan.
- Samsung’s HBM4 sold at “target price” is the memory bill for RubinAI news · 29 Oct 2026
Mid-to-high $4 per gigabit is about $36–40 per GB, or $9,000–10,500 of HBM4 in one 288 GB Rubin GPU. Sold out at target price makes the shortage contractual.
- Powertech’s $400M panel fab is where Broadcom’s ASIC volume goes when CoWoS is fullAI news · 29 Oct 2026
Taiwan cleared Powertech's US$400M Singapore panel-level packaging fab on 28 October: the second queue for AI packages when TSMC CoWoS is full, with Broadcom ASIC volume.
- Samsung’s 60–70% LTA target is a mortgage on 2030 capacityAI news · 29 Oct 2026
Samsung wants 60–70% of memory on long-term agreements through 2030. The contracts lock volume, not price: a demand schedule with deposits that now justifies the capex.
- Samsung’s 2028 line is a lead-time statement, not a demand forecastAI news · 29 Oct 2026
Samsung guides KRW 84.4 trillion of 2026 capex and still calls 2028 tight: money buys cleanrooms and tools on 12–18 month lead times before it buys output.
- What is DataVendor by HUD, and who pays for your data?AI news · 28 Oct 2026
DataVendor is HUD's new marketplace where teams license codebases, RL tasksets and raw data to AI labs. Here is how a sale works, what it costs, and what is still unverified.
- Can you steer sycophancy out of a small model without retraining it?Interpretability · 2 Dec 2025
LLM sycophancy, removed with activation steering: it shows up as a linear direction in a small model's hidden states. Subtracting that direction while the model generates raised accuracy on sycophantic prompts from 12.5% to 53.8% on Qwen3-0.6B, with no fine-tuning.