Aikido Technologies Unveils Offshore Datacenter Platform for AI Compute

Mar 6, 2026
Aikido Technologies has introduced the AO60DC, a floating offshore wind platform that combines renewable energy generation with AI-grade datacenter capacity. The company plans to deploy its first commercial unit in the UK by 2028.

Aikido Technologies has launched AO60DC, a floating offshore wind platform designed to host AI-grade datacenters, announced in a press release. The system integrates wind generation, battery storage, and high-density compute infrastructure on a single semi-submersible platform.

Each AO60DC unit can support 10–12 MW of computing power alongside a 15–18 MW wind turbine and integrated battery energy storage. The design targets deployments from 30 MW to more than 1 GW of IT load, enabling nations to install sovereign AI infrastructure close to major coastal data demand centers.

The platform features a modular, prefabricated structure that can be assembled up to ten times faster than conventional offshore units. Its passive cooling system uses seawater to achieve a power usage effectiveness (PUE) below 1.08. The company expects the units to operate within 200 miles of major compute hubs while maintaining sub-10 millisecond latency.

A proof-of-concept unit is under development in Norway, with deployment planned later this year. The first commercial site is expected to be in the UK, with operations targeted for 2028.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.

Also, consider following us on social media:

AI Chips & Datacenters AI Brief AI Brief (X)
Free newsletter

Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.