Chain Income Group

Chain Income Group

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Chain Income Infrastructure Partners (CIIP)
We analyze, source , and structure opportunities across the AI infrastructure sectors powering the modern economy.

ENERGY SYSTEMS | AI Compute | EV Network | AUTONOMOUS SYSTEMS | ROBOTICS | WATER UTILITY

22/09/2026

Fuel at A$2.10/L? An average petrol car costs ~A$3,360/yr. An EV? Just A$660 to charge. With solar, only A$240. That's up to A$3,120 saved annually.

Every price spike widens the gap. Once you charge at home, you'll never miss the servo. Your wallet will thank you.

18/09/2026

GPU COMPUTE DAILY SNAPSHOT
09-17-26

$/GPU-hr · 1D · 7D · YTD · 30D ann. vol
>H100 — $2.71 · +0.21% · +0.73% · +44.7% · 8.9%
>H200 — $3.40 · −0.94% · −0.91% · +39.9% · 9.2%
>B200 — $5.07 · +0.62% · +1.64% · +31.0% · 5.7%
>B300 — $6.63 · −3.32% · +0.79% · +56.7% · 20.7%

15/09/2026

Whoever wins the AI race, wins the world. 🔥

15/09/2026

GPU COMPUTE DAILY SNAPSHOT
09-14-26

$/GPU-hr · 1D · 7D · YTD · 30D ann. vol
>H100 — $2.68 · +0.16% · −0.12% · +43.6% · 9.9%
>H200 — $3.41 · +0.27% · +0.44% · +40.4% · 9.0%
>B200 — $5.00 · +0.12% · +0.52% · +29.1% · 5.5%
>B300 — $6.63 · +0.10% · +3.27% · +56.8% · 13.4%

15/09/2026

Daily token usage in China went from 100B to 140T in 14 months.

Beijing's response:
- 100,000 GPUs
- $532B in infrastructure investment
- 9,800 EFLOPS by 2030

The AI race is a compute race. Access to GPUs will define who competes.

Governments and hyperscalers are solving this by building.

Our operator network includes operators running
exactly this kind of compute infrastructure
deployment at scale.

We structure everyday investor access to the cashflow these operators generate operationally.

13/09/2026

Something worth understanding about how AI compute
infrastructure actually works at operator level.

GPU owners who previously mined cryptocurrency are switching to renting hardware to. AI companies instead.

The hardware hasn't changed. The buyer has.

AI inference demand now pays more consistently than crypto mining ever did, and pays in straightforward dollar amounts against contracted agreements.

This is the ground level reality of what compute
infrastructure operators do.

Deploy hardware. Meet AI demand. Generate contractual revenue.

Our operator network includes operators running
exactly this kind of compute infrastructure deployment at scale.

We structure everyday investor access to the cashflow these operators generate operationally.

01/09/2026

The costs of solar and wind energy have fallen, while the costs of nuclear power and fossil fuels keep rising.

Renewable energies are gaining ground not because people realize that climate change costs lives and destroys our environment, but because they are opting for the more cost-effective choice.

01/09/2026

For the past few years, one of the loudest arguments against the AI boom has been its enormous and rapidly growing demand for electricity.

That concern is legitimate.

But look deeper at what that demand is unleashing: a massive accelerant for the renewable energy buildout.

Microsoft has agreements covering up to 40 GW of new renewable energy, including 10.5 GW through Brookfield. Amazon has backed 700+ carbon-free energy projects totalling more than 40 GW, dominated by solar and wind, alongside batteries, geothermal and selected nuclear investments.

Google spent US$4.75 billion acquiring Intersect Power and is developing gigawatt-scale clean-energy parks alongside AI data centres. It's partnering on the world's largest planned 100-hour battery, backed by new wind and solar, and has contracted 1 GW of demand response, allowing data centres themselves to respond to grid conditions.

China requires new data centres across its eight national computing hubs to source at least 80% renewable electricity, alongside enormous investment in batteries and ultra-high-voltage transmission. And now Australia is developing national rules requiring hyperscale data centres to bring forward new, additional renewable generation to meet their enormous new electricity demand, backed by the firming required to make it reliable.

Something much bigger is happening here. AI isn't bringing back the baseload grid. It may actually be accelerating its replacement.

Every hyperscale data centre creates an enormous new load, requiring enormous amounts of new generation, storage and grid infrastructure. Increasingly, the technologies capable of being deployed at the required speed, scale and cost are:

➡️ Solar ➡️ Wind ➡️ Batteries ➡️ Transmission ➡️ Flexible demand

Yes, nuclear, geothermal and other firm clean generation can contribute where their economics and deployment timelines make sense. Gas will continue playing peaking and firming roles in some grids. Hyperscalers need reliable electricity, not ideological purity.

But that's precisely the point. Microsoft, Amazon, Google and other hyperscalers aren't investing billions in SWB because they've suddenly become environmental charities. They're doing it because they need staggering quantities of new electricity, quickly and competitively.

And scale has consequences:

➡️ More deployment strengthens supply chains.
➡️ More batteries firm renewables.
➡️ More transmission unlocks renewables.
➡️ Flexible loads help balance the grid.
➡️ More SWB demand drives costs lower.

That's why I increasingly think AI could become one of the largest accelerants of the energy transition we've ever seen.

The very industry accused of becoming one of the world's great new energy problems may instead become a Trojan Horse for rebuilding the electricity system itself.

And inside this one isn't an army of Greeks. It's an army of SWB.

I'm currently working on a six-part video and blog series, THE GREAT DATA CENTRE DEBATE, digging much deeper into all of this. The public concerns surrounding AI data centres are real and deserve serious answers: electricity and household bills, water, land, jobs, grid infrastructure, emissions and ultimately who pays.

The purpose isn't to dismiss those concerns. It's to put each one through the same test:

➡️ Follow the evidence. Follow the economics. See where it leads.

The irony of the AI boom may ultimately be extraordinary. The technology accused of becoming one of the world's great new energy problems may instead become one of the most powerful forces accelerating the transformation of the electricity system.

The horse is already inside the gates.

The future isn't being built around yesterday's grid. It's being built around speed, flexibility and economics.

31/08/2026

Trump says the only reason to oppose data centers is if communities want to be “backwards and poor.”

29/08/2026

In Australia, under proposed national standards, new data centres must bring their own 100% renewable energy supply, firmed by batteries or gas. Crucially, this means new, additional renewable generation, not simply claiming certificates against generation already on the grid.

And the scale is enormous. AEMO is already tracking 225 data centres in development, with data-centre electricity demand forecast to rise from around 3% of NEM consumption today to 13% by 2036, potentially around 34 TWh a year.

Climate Change & Energy Minister Chris Bowen puts the challenge bluntly: “Data centres are huge consumers of electricity. They are whales.” In 2024, US data centres consumed as much electricity as the entire country of Sweden. Australia wants to get ahead of this.

Australia isn't alone. Similar policy moves are underway in China, Germany and Ireland, but Australia's proposed framework is among the most aggressive: 100% renewable energy, tied to new additional generation and backed by firming, with the new rules intended to begin from 2027.

Instead of allowing this enormous new load to compete with households and businesses for existing generation, Australia wants it to help finance the new supply needed to meet it.

AI growth → electricity demand → renewable PPAs → new solar & wind → more batteries & transmission → stronger grid.

This has always been part of my thesis: AI will become a major new demand engine for Australia's solar, wind and battery buildout, rather than a brake on the energy transition, potentially creating a blueprint the rest of the world can replicate.

AI and renewables don't have to compete. Done right, each can accelerate the other.

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