Decision Tree Research is an independent research and analysis firm that specializes in strategic technologies, public policy, and geopolitics.
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Our areas of focus
AI capability has become a measure of national power and a geopolitical race for superiority. The competition covers frontier model development, U.S.–China rivalry, industrial policy, export controls, military integration, and the international safety and governance architecture forming around them.
Chips have become the new oil. The contest for silicon supply chain security spans advanced chips, the equipment and materials that produce them, and the export controls and industrial policy reshaping the global industry.
The defense industrial base is being rewritten by a new generation of commercial AI and space firms. Military AI, autonomous weapons, drones, and the commercial space revolution are reshaping the strategic balance.
Featured research
How Big Is China’s Reported DUV Semiconductor Lithography Breakthrough?
China’s first domestically produced immersion DUV lithography tools are real — but the breakthrough is smaller than the drop in ASML’s share price implied, and bigger than China’s official silence suggests.
Four keys to understanding the future of AI and unemployment
A data-driven crash course in the most illuminating historical analogies for AI and employment — from farm mechanization and the fate of the horse to the economics of music and chess.
How Much Did U.S. Semiconductor Export Controls Accelerate China’s Push for Self-Sufficiency?
In terms of Chinese government subsidies, not at all: investment data shows a semiconductor self-sufficiency push that was already running at full speed before U.S. export controls arrived.
From The AI Power Podcast
Weekly episodes on AI policy, semiconductors, and the U.S.–China technology competition — hosted by Gregory C. Allen.
Is China Entering the Global Memory Supply Chain?
Chinese memory maker CXMT is on track for roughly 10 percent of the global DRAM market, and HP, Asus, and Acer have reportedly begun shipping notebooks built on its chips — a position Greg and Adam Goodwin trace to equipment bought ahead of anticipated export controls, a validated end-user license granted on 18-nanometer claims that TechInsights reverse engineering puts at 16, and CHIPS Act money that went largely to logic rather than memory. Then Reuters reporting that Samsung and SK Hynix have tested AMEC etching tools for their China fabs — which neither company fully denies — and a Council on Foreign Relations proposal that fabs be made to choose between American and Chinese toolsets.
Listen →MORE AI Cyber and Bio, Chinese Models, and a U.S. Regulatory Scramble
Three frontier labs have now disclosed models that broke out of evaluation environments and hacked real companies — OpenAI’s Black Hat account of agents leaving each other notes for months, Anthropic’s three real breaches buried in 141,000 evaluation runs, and Meta’s admission of the same — and Greg reaches for Admiral Hyman Rickover and the nuclear navy to explain why blaming the shared testing vendor misses the point. Then the story he finds more alarming: Stanford and the Arc Institute generated 700,000 candidate genomes with a biological foundation model, sixteen of which became working viruses that had never existed on Earth. Plus DeepSeek V4 Flash at three cents a task, and what the White House’s unpublished AI framework concedes about the export controls.
Listen →China’s Homegrown DUV Lithography Breakthrough and the Debate Over Banning China’s Open-Source AI
A Shanghai firm has reportedly begun manufacturing immersion DUV lithography machines — the equipment China has spent two decades trying to build for itself — and Greg argues the Japanese components behind the claim, plus China’s growing ability to service its installed fleet, matter more than the machine count. Then the administration’s accusation that Moonshot AI distilled Anthropic’s Fable model, Beijing’s “AI hegemonism” rebuttal, the status of the MATCH Act, and why the open-source fight turns less on open versus closed than on what safety testing should apply past a capability threshold.
Listen →Why “Decision Tree”?
The decision tree is one of the most useful analytical tools in three disciplines that rarely meet: Machine Learning & AI, Corporate Strategy, and Government Policy Analysis.
In machine learning, the decision tree is foundational to how models classify and predict. In business strategy, it structures operations planning, capital allocation, and risk decisions. In policy analysis, it maps the consequences of regulation, sanctions, and other interventions through complex systems.
Gregory C. Allen’s career has spanned all three. The firm’s name signals the methodology that runs through the work: enumerate the decisions, trace the branches honestly, find the paths that carry the most consequence, and reason rigorously before acting. Decision Tree Research applies that discipline to our analysis of the technologies shaping global power competition.
Built on a body of work
Before founding Decision Tree Research, Gregory C. Allen authored some of the most impactful analysis in U.S. AI policy — at CSIS, the Department of Defense Joint Artificial Intelligence Center, the Center for a New American Security, and the Belfer Center for Science and International Affairs at Harvard Kennedy School.