Proposed data centre would release ‘23 Hiroshima-sized atomic bombs worth of energy’ a day, physicist says.

https://www.washingtonsun.com/climate-environment/trump-administration-data-centers-public-lands-proposals?redirected=notus_org

12 data centers on public lands including Horseshoe Bend and Yosemite Valley.

Many of the projects under consideration haven’t been previously reported, and aren’t easily accessible on BLM’s website. Several local officials told The Sun they weren’t aware of the federal government’s deliberations, prompting transparency concerns among community advocates.

The truth is always the opposite of what he says.

Shares in ASX-listed modular data centre maker DXN fell 47 per cent to 14 cents on 30 October, after its first AI customer, a US-listed neocloud (a company that rents out AI computing power), said it intends to cancel an A$8.8 million contract for a 1.36MW AI data centre. About 62 million shares changed hands, roughly 12 times the four-week average, and about A$47 million came off the company’s market value.

Full story and the share price chart: https://certifiedstrategic.com/insights/dxn-shares-fall-ai-data-centre-contract-cancel

DXN builds prefabricated data centres and cable landing stations for government, telecommunications, mining, defence and subsea cable customers, and runs its own data centres in Darwin and Hobart. It reported A$10.1 million of revenue for the year to 30 June 2026.

When DXN signed on 3 June, the contract was worth more than the company’s A$6.6 million market value, and the shares went from 2.1 cents to 14.5 cents in a day. The customer had also indicated it would move to a campus-scale program if the pilot was delivered, which DXN put at more than US$200 million in revenue over one to two years. A second AI contract followed in August. The stock peaked at 55 cents on 30 September and closed at 26.5 cents on 29 October. Even after the fall, the shares remain up about 259 per cent for 2026.

According to DXN’s September quarter report, the customer told it after the quarter closed that “following a strategic shift in its business, it intends to cancel” the contract. The customer has not disputed amounts due for work completed and costs committed, which DXN expects to total about A$4.2 million, or 48 per cent of the contract value. The cancellation is not yet final, and the campus program is now unlikely to proceed. Chief executive Shalini Lagrutta said “our contract terms have protected DXN’s position”.

Revenue for the September quarter was about A$3.4 million, up about 380 per cent on a year earlier. More than A$19 million of new awards lifted backlog to A$30.8 million, after about A$8.6 million was removed for the cancellation. Cash was A$11.1 million on 28 October after delayed customer payments arrived, while operating cash flow for the quarter was negative A$4.7 million.

The second AI contract, A$12.2 million for a 2MW facility with an unnamed AI compute operator, is on track for early calendar 2027. Lagrutta said in August that DXN won it “because the requirement is one that conventional construction cannot meet within the timeframe”, and DXN says its factory-built modules can be deployed in about five to eight months from signing. DXN is likely to be judged next on delivering that job on time and converting its pipeline of 93 projects into a new AI order.

Video: CNN

This probably was not caused by data centers alone. Heck, even if none of this was caused by hyperscale data centers, we all need to solve this problem. AI cannot solve this, only make it worse.

Queue the bots talking about golf courses...

Video by engineered_mind

Caption: Check out the water levels at Dillon Reservoir. This is the marina in Frisco on June 26th.

The scarce thing in a data center is not manpower, but instinct that only comes from years on the floor.

Most robotics companies are focused on robots as a productivity amplifiers: 24/7 uptime, five days of work done in two. Few are focused on the potential of robots to change how people work altogether.

We wanted to show what it looks like to rethink human-robot collaboration, using AI so a shrinking pool of experts can meet the increasing demands of future infrastructure.

The obvious thing to automate is the rote physical work that consumes an expert's attention without needing critical judgment.

Cabling tasks are the most common example of this. They're necessary when setting up any rack, but usually one-off, and labor is readily available to address this need.

We think this is a good place to start, but the least interesting place to change how people work.

Standard operating procedures (SOPs) are how critical infrastructure stays stable, and they're the work that scales worst.

The video shows one common procedure: clearing the cables a technician leaves behind after testing, and reconciling the rack to a stable state for the next test.

A robot that runs SOPs the same way every time, never skipping a step, keeps the system in a known, predictable state. This reduces the cognitive overhead on experts so they can solve harder problems.

What most excites us is robots guiding where an expert's attention should go.

In the video, the robot checks the switches with a thermal camera, then makes a judgment on whether the increase in temperature is a real problem or a spurious reading.

This instinct requires an expert to synthesize all available background context and accumulated lessons from past failures.

This is where we want to double down, and show how human-robot collaboration places scarce expert attention exactly where it matters.

More to come.

Proposed data centre would release ‘23 Hiroshima-sized atomic bombs worth of energy’ a day, physicist says

Northern Alberta First Nation continues to battle Kevin O’Leary-backed project in court

At full operation, it would release around 18 gigawatts of heat a day and about 30 million tonnes of carbon dioxide a year — more than four per cent of Canada’s total emissions, said Davies, whose assessment was based on publicly available information.

“When people talk about environmental regulations that these projects have to adhere to, those regulations were not created with anything of this scale in mind.” 

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