EDGE AI • HEAT RECOVERY • WATER EFFICIENCY • DISTRIBUTED RESILIENCE • MICRO DATA CENTERS • COMMUNITY INFRASTRUCTURE • DARK-FIBRE SCALE-ACROSS • NVIDIA SPECTRUM-XGS • CHALLENGING MEGA DATA CENTRESEDGE AI • HEAT RECOVERY • WATER EFFICIENCY • DISTRIBUTED RESILIENCE • MICRO DATA CENTERS • COMMUNITY INFRASTRUCTURE • DARK-FIBRE SCALE-ACROSS • NVIDIA SPECTRUM-XGS • CHALLENGING MEGA DATA CENTRES

Young inventors

Artificial Inventor for Kids

The youth-focused experience is designed to encourage creativity, invention and experimentation with age-appropriate safeguards and adult oversight.

Encourage creativity with safeguards.

The concept is a patient, supervised mentor intended to help children explore creativity, invention and experimentation without opening adult purchasing, filing or robot-control actions to them.

Creativity and ideation prompts
Simple science and invention guidance
Age-appropriate explanations
Human-controlled boundaries for consequential actions

Videos

Kids overview

Supporting video.

Kids demonstration

Supporting video.

Central architecture challenge

The goal: prove the mega data centre is no longer necessary.

Cloud Wash Laundry is being designed around a direct technical challenge to the conventional mega-campus model: place compute where useful heat already exists, then connect those heat-sink-sited AI factories with dedicated dark fibre and NVIDIA Spectrum-XGS scale-across networking so the distributed sites can operate as one metropolitan compute fabric.

The dark fibre is the dedicated optical transport; Spectrum-XGS is NVIDIA’s scale-across networking layer. The project’s proposed fibre-spool testbed and multi-site field pilot are intended to determine whether distributed sites can match co-located clusters on workload-level measures such as time-to-result and energy per token.

Latest physical-model findings

Measured next. Modeled now. Heat-sink constrained.

Current design-stage results combine the 120-host Los Angeles heat-sink-siting model with the updated fanless heat-rejection screening figure. They are screening outputs, not field-certified performance. In parallel, the network programme tests whether NVIDIA Spectrum-XGS scale-across networking over dedicated dark fibre can make geographically separated AI factories behave as one compute system. The mega-data-centre conclusion remains an experimental objective, not an already validated result.

Distributed-AI paper PDF Fanless-PVT paper PDF

79.4%IT electricity converted to useful process heat in the optimistic fully temperature-compatible heat-sink bound

77.6%same-supply operational emissions reduction at 43 gCO₂e/kWh in that upper-bound compatibility case

74 m³/yrcentral direct evaporative water in the current Los Angeles screening model

44.2%reduction in wetted states under dispatch in the current fanless heat-rejection screening figure

120 / 67 stateswater-eligible states versus wetted states under dispatch in the current screening summary

3-site dark-fibre pilotplanned workload-level validation of the NVIDIA Spectrum-XGS scale-across architecture against a co-located reference

The 79.4% and 77.6% values use the optimistic fT = 1.00 temperature-compatibility bound; lower compatible heat fractions materially reduce both benefits. The updated fanless heat-rejection figure also summarizes 83 of 144 states as feasible overall and 77 of 144 as feasible by free pathways alone, while array-wide EHD is not preferred because only 3 of 80 tested cases exceed the conservative comparator.