Evergreen, curated overviews of the forces shaping tech and AI — each grounded in the archive and knowledge graph, and cross-linked to the concepts, coverage and relationships behind it.
16 guides
From chat to autonomous action.
AI agents are systems that plan, use tools, and take actions across software, reshaping workflows while raising reliability, cost, and governance challenges.
The accelerators the whole race is built on.
How GPUs, custom AI chips, inference accelerators and software ecosystems shape competition for AI compute.
The power problem behind the compute problem.
How AI data centers are reshaping electricity demand, grid connections, generation choices, costs, and clean-energy goals.
The physical and financial supply chain behind frontier AI.
AI infrastructure is the physical and financial system of compute, data centers, power, networks, chips, and labor behind frontier AI.
How governments are trying to govern the technology.
How AI regulation is taking shape through the EU AI Act, US federal and state proposals, safety rules, transparency mandates and global competition.
Making increasingly capable systems controllable and aligned.
AI safety and alignment examines how increasingly capable AI systems are evaluated, controlled, interpreted, and governed before and after deployment.
Who owns the data models learn from.
How copyright, consent, licensing, datasets and fair use are reshaping the data used to train generative AI models.
Robotaxis, self-driving, and the long road to autonomy.
Autonomous vehicles: robotaxis, assisted driving, trucking, safety oversight, regulation and the economics of scaling driverless transport.
Export controls, domestic models, and a bifurcating stack.
How China’s AI push is shaped by US chip controls, domestic semiconductor efforts, open-source models, and competition over the AI stack.
The platforms renting out intelligence.
How AWS, Azure, Google Cloud and emerging AI clouds compete for compute, capacity, power, financing and long-term AI workloads.
Where compute meets concrete, power and water.
Data centers are becoming a strategic constraint for AI, linking compute growth to power, water, land, grids, financing and local consent.
From demos to deployment inside real companies.
How enterprises move AI from pilots to production, balancing workflow redesign, data governance, cost, security and measurable returns.
The large models remaking software.
How foundation models evolved from language systems into multimodal infrastructure, and the competition over capability, access, cost and governance.
The falling price of a token and what it unlocks.
How inference costs, token pricing, reasoning workloads and infrastructure shape AI margins, competition and viable products.
Open weights, open models, and who controls the frontier.
Open-source AI explained: open weights, licensing, fine-tuning ecosystems, leading model providers, and the debate with closed frontier labs.
The chips, fabs and supply chains that gate every AI ambition.
How semiconductor design, foundries, packaging, memory, policy and export controls shape global technology supply chains.
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