Anthropic's '2028' essay on US-China AI competition fractures the industry — Nvidia, HuggingFace, and OpenAI each offer incompatible counter-doctrines.
NIST CAISI confirms DeepSeek V4 Pro as top Chinese model, ~8 months behind US leaders — but MIT-licensed, 1M context, and 50–100× cheaper than closed rivals.
Matthew Berman argues DeepSeek confirms US open-source AI has no business model without government subsidy; proposes compute quotas and sovereign procurement as policy fixes.
DeepSeek v4 reignites debate on US open-source AI: Berman argues the business model is broken, leaving Nvidia as the only credible US champion.
DeepSeek V4 drops two open-weight models with 1M-context by default, CSA+HCA hybrid attention, and V4-Pro priced at roughly 1/7 Opus 4.7's output cost.
DeepSeek V4's 10× KV-cache compression restructures AI cost economics globally, exposing a structural threat to US lab pricing and strategic positioning.
A Virginia Tech preprint shows model-native skills extracted via sparse autoencoders outperform human-defined skill files in SFT — and produce 41% gains on math via activation-space data selection.
DeepSeek V4-Pro launches with 1.6T parameters, 1M context, and 10× KV cache reduction over V3.2 — multiplying inference concurrency roughly 10× on the same hardware.
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