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20:46EN
Matthew Berman· Aug 26, 2026Open-Weight AI Models: Token Share, Spending and Strategic TradeoffsMatthew Berman · Forward FutureMatthew Berman examines a Vercel AI Gateway snapshot and argues that model usage and spending can tell very different stories.
15:37ENMatthew Berman· Aug 4, 2026Matthew Berman on Qwen3.8-Max, AI Costs and Open-Weight CompetitionMatthew Berman · Forward FutureA 2026 review of reported benchmark results and research demonstrations leads to questions about deployment economics and geopolitical dependence.
27:13ENMatthew Berman· Jul 21, 2026Kimi K3 and the Debate Over Open-Weight AIMatthew Berman · Forward FutureMatthew Berman examines model economics, competition and security arguments after Moonshot AI’s Kimi K3 announcement.
19:49ENMatthew Berman· Jun 26, 2026Matthew Berman on Restricted AI Model Releases and the Risk of Concentrated PowerMatthew Berman · Forward FutureA June 2026 commentary argues that limited previews for frontier models could disadvantage startups and independent developers.
17:26ENMatthew Berman· Apr 29, 2026Matthew Berman on Funding US Open-Weight AI in Competition With ChinaMatthew Berman · Forward FutureBerman argues that open models face a financing problem and proposes public support, hardware-backed development and specialized models.
17:21ENMatthew Berman· Apr 25, 2026DeepSeek V4, Model Efficiency and the US–China AI DebateMatthew Berman · Forward FutureMatthew Berman examines DeepSeek’s April 2026 V4 preview and argues that efficient open-weight models raise questions for American AI providers and policymakers.
24:22ENMatthew Berman· Jan 31, 2025Dario Amodei on DeepSeek, AI Costs and Chip Export ControlsMatthew Berman, Jonathan Ross, David Sacks · Forward FutureMatthew Berman examines the Anthropic CEO’s 2025 essay, the limited evidence behind distillation allegations and the economics of model training.
20:34ENMatthew Berman· Jan 28, 2025DeepSeek R1 and the Debate Over AI Costs and ComputeMatthew Berman · Forward FutureMatthew Berman examines 2025 reactions to DeepSeek, from training efficiency and market losses to open weights, privacy and the possibility of a demand rebound.