AI Bottlenecks research

Research library across AI, Energy, and Robotics

Browse source-led essays and research notes across the physical constraints behind AI infrastructure, energy systems, and robotics.

  1. AI · Annual review · 2026-08-30

    The Bottleneck Moved

    Memory became an allocation calendar, optics received real money, neoclouds became capital structures, and the scarce product moved from a GPU to useful output per active megawatt.

  2. Energy · Annual review · 2026-08-30

    The Megawatt Became the Product

    The power trade moved from grid avoidance to electrical equipment, then from order books to the harder question: which collection of assets can become an energized campus on time?

  3. Robotics · Annual review · 2026-08-30

    Robots Became Operations

    A few humanoids crossed into measured work. The harder story was everything around them: qualified joints, hands, safety, field failures, integration and the economics of deployed labor.

  4. AI · Flagship research · 2026-08-28

    China Can Reshape Memory Without Winning HBM

    China can pressure conventional DRAM prices long before it reaches HBM parity. The result could be a split memory market, faster incumbent migration into custom HBM, and a more violent cycle when supply turns.

  5. Robotics · Flagship research · 2026-08-22

    A motor is not an actuator: inside the joint that makes a robot move

    A robot joint forces motors, gears, sensors, bearings, heat, control and safety to agree inside a small housing. The hard part is not making it move once. It is producing the same controlled force, at the same cost and lifetime, thousands of times.

  6. Energy · Pillar guide · 2026-08-22

    AI's energy bottleneck: the race for delivered power

    A GPU reservation is only a promise. Capacity becomes real when turbine slots, transformers, interconnection studies, switchgear, cooling loops and crews converge at the same site.

  7. AI · Pillar guide · 2026-06-01

    AI's photonics bottleneck: why moving data is now harder than making chips

    AI clusters are running out of room on copper. As back-end fabrics climb from 800G to 1.6T and 3.2T, the constraint stops being how many GPUs you can buy and becomes how cheaply you can move data between them. The case for optics as the next chokepoint, and a map of where it bites first.

  8. AI · Founder letter · 2026-05-01

    The world is built out of a few narrow places

    Why I built AI Bottlenecks, what the AI buildout actually rests on, and why the most interesting story in markets right now is happening five layers below where everyone is looking.