The Compute Corridor When Blackwell Density Rewrites FSI

The Compute Corridor

When Blackwell Density Rewrites FSI

By Arindam Bose
Curious observer of where silicon density, sovereign policy, and Indian real estate economics collide

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Every Tuesday, I Try to Write About Something Safe

Every Tuesday, when I sit down to write about construction and technology, I make myself a promise:

"This week, Arindam… keep it simple. Something solid. Something that doesn't spiral."

And every Tuesday, without fail, that promise collapses.

Last week it was nuclear reactors powering data centers. Before that, walls that store cooling like batteries. Before that, buildings that program themselves to respond to monsoons.

This week, I thought I'd finally picked something grounded.

Office buildings.

Just real estate. Floor plates. Lobbies. FSI calculations.

How complicated could office buildings be?

But within minutes, I was staring at something that shouldn't exist:

Buildings where the most valuable square foot isn't near the food court or the Metro station.

It's in a basement.

Nine and a half meters underground.

Where NVIDIA Blackwell GPUs generate more heat per rack than an entire floor of knowledge workers ever did.

Not metaphorically.
Actually.

Because in 2026, office real estate in India stopped being about people and started being about compute.

The IT Park — that air-conditioned human warehouse we built for three decades — is dying.

And rising in its place is something entirely new: The High-Performance Work Zone (HPWZ).

Not an office.
Not a data center in the old sense.

A machine capital corridor where sovereign intelligence is manufactured, cooled, and defended on Indian soil.

This is the story of how NVIDIA Blackwell — a GPU architecture — became the new determinant of Floor Space Index.

And why the most valuable real estate in India today isn't in Worli penthouses.

It's in rack halls in Visakhapatnam and Navi Mumbai, where data stays local, power stays sovereign, and intelligence is no longer rented from Seattle or Singapore.

The Death of the IT Park: When "Human Warehouse" Became Obsolete

The Old Model: Built for Bodies, Not Blackwells

For three decades, the Indian IT Park followed a simple formula:

3.5-meter slab-to-slab heights (enough for humans + HVAC)
Raised floors for cable management
Cafeterias, atriums, breakout zones
Proximity to Metro, airports, malls

The value proposition was density of talent × cost arbitrage × time zone overlap with Western clients.

Buildings were optimized for headcount, not heat dissipation.

HVAC was designed to keep people comfortable.
Power was designed to run laptops and monitors.
Structural loading was designed for desks and meeting rooms.

That model worked — until AI happened.

The Bhashini Watershed: February 9, 2026

On February 9, 2026, something shifted.

India's National Language Platform — Bhashini — completed its migration from global hyperscalers (Google Cloud, AWS) to Yotta's sovereign Shakti Cloud, powered entirely by domestic NVIDIA H100 GPUs.

The results were not incremental. They were structural.

Performance Metrics (Global Hyperscalers → Yotta Shakti Cloud):

Metric	On AWS/Google	On Shakti Cloud	Improvement
System Performance	Baseline (100%)	+40% throughput	40% boost
Operational Cost	Baseline (100%)	70% of prior cost	30% reduction
Uptime	N/A	99.99%	Zero data loss across 200+ TiB
Daily Inferences	N/A	~15 million requests	Population-scale proven

This wasn't just a technical win.

It was a sovereignty signal.

If the Indian government could save 30% on its "Intelligence Bill" by keeping workloads on domestic infrastructure — while simultaneously improving performance by 40% — then every GCC, every hyperscaler, every AI startup in India would follow.

The lesson was blunt:

Sovereign silicon outperforms rented intelligence.

And buildings that cannot house that silicon are now stranded assets.

Why the IT Park Cannot Adapt

The problem isn't aesthetic. It's thermodynamic.

A traditional enterprise server rack draws 5–10 kW.
An AI training rack with NVIDIA Blackwell GPUs draws 50–100 kW.

That's not a 2× jump.
That's a 10× jump in heat density per square meter.

And here's what that means for the building:

What the IT Park Lacks:

Infrastructure Layer	IT Park (2015)	HPWZ (2026)	Gap
Floor-to-Ceiling Height	3.5m	9–10m (for immersion tanks, overhead manifolds)	Structural incompatibility
Cooling Architecture	Air-based CRAC/CRAH	Liquid cooling (immersion + direct-to-chip)	Mechanical obsolescence
Power Density	50–100 W/sq ft	200–400 W/sq ft	Electrical undersizing
Structural Loading	250–350 kg/m²	500–800 kg/m² (liquid tanks, transformers)	Foundation inadequacy
FSI Treatment	All built-up area counted	DG stacks, cooling plants exempt in DCEZ zones	Regulatory mismatch

You cannot retrofit a 3.5-meter slab building to host liquid immersion cooling tanks.

You cannot rewire a building designed for 50 W/sq ft to handle 400 W/sq ft AI racks.

You cannot jack up transformer capacity when the grid connection itself was sized for knowledge workers, not silicon.

The IT Park is dying because it lacks the mechanical muscle to house Blackwell-density racks.

And in 2026, if you can't house Blackwell, you're not AI-ready real estate.

You're legacy stock.

The Physical Chakra: How Buildings Became Thermodynamic Machines

The HPWZ Archetype: Designed from the Cooling Plant Up

The High-Performance Work Zone doesn't start with lobbies or floor plans.

It starts with heat rejection.

Because in AI-dense campuses, cooling is no longer a utility. It's the primary design constraint.

Here's what that means architecturally:

1. The 9.5-Meter Hall: Why Ceilings Went Vertical

In traditional office buildings, 3.5 meters is standard.

In HPWZs, 9–10 meters is becoming the default for lower levels.

Why?

Because liquid immersion cooling — the only technology that can handle 100 kW racks — requires:

Immersion tanks (2–3 meters tall, housing entire racks submerged in dielectric fluid)
Overhead distribution manifolds (piping that circulates coolant across hundreds of racks)
Service gantries (for maintenance access without shutting down operations)
Pump rooms and heat exchangers (rejecting waste heat to cooling towers or district loops)

You cannot fit this into a 3.5-meter slab.

The HPWZ is drawn from the cooling plant up, not the lobby down.

2. Liquid Is the New Air: The 27% CAGR Revolution

Here's the market reality:

India Data Center Cooling Market (2026–2031):

Cooling Type	CAGR (2026–2031)	Adoption Drivers
Overall Cooling Market	25.47%	AI workload growth, densification, sustainability mandates
Liquid Cooling (All Methods)	~27%	Fastest-growing segment; GPU density forcing architectural shift
Direct-to-Chip	High-20s% (indicative)	Retrofit ease, hyperscaler AI workloads, lower incremental capex
Immersion	Mid-20s% (indicative)	GPU-dense sovereign campuses (Yotta, Adani-EdgeConneX), 9.5m halls

When any mechanical sub-layer sustains 25%+ CAGR for a decade, it stops being incremental capex.

It becomes a reconstruction program.

In India's data centers, the cooling stack is now in that regime.

Air is a comfort medium. Liquid is the work medium.

And buildings designed around air-based CRAC units are thermodynamically obsolete.

3. The FSI Hack: When Cooling Plants Became "Non-FSI"

This is where policy meets physics.

Under India's emerging Data Centre Economic Zones (DCEZ) framework, certain utility structures are now exempt from FSI calculations:

DG (Diesel Generator) stacks
Cooling towers and chiller plants
Transformer yards and HT panels
Water storage for district cooling loops

Why does this matter?

Because traditionally, every square meter of built-up area — including mechanical rooms — counts toward your FSI cap.

In HPWZs, mechanical infrastructure is being carved out.

This allows developers to go vertical on utilities without burning residential or commercial FAR.

Translation:

A conventional office tower might dedicate 15–20% of its FAR to mechanical + electrical rooms.

An HPWZ can push that to 30–40% — without penalty — by stacking cooling plants, transformers, and DG sets as "non-FSI utility blocks."

This is the invisible differentiator that creates the asset class.

Not zoning.
Not incentives.

Regulatory carve-outs that let cooling infrastructure grow vertically, not horizontally.

The Physical Snapshot: IT Park vs HPWZ

Design Element	IT Park (Legacy)	HPWZ (2026)
Floor Height	3.5m	9–10m (lower levels for liquid cooling)
Cooling Medium	Air (CRAC/CRAH)	Liquid (immersion + direct-to-chip)
Power Density	50–100 W/sq ft	200–400 W/sq ft
FSI Treatment	All built-up area counted	DG stacks, cooling plants exempt (DCEZ)
Structural Loading	250–350 kg/m²	500–800 kg/m² (liquid tanks, transformers)
Design Philosophy	Lobby-first (human-centric)	Cooling-plant-first (machine-centric)

The HPWZ isn't optimized for people. It's optimized for silicon.

The Policy Fortress: How India Built a Tax Moat Around Compute

The 2047 Tax Holiday: India's $70–100 Billion Bet

On February 1, 2026, India's Union Budget did something extraordinary.

It created a 21-year tax holiday for foreign cloud providers — the longest corporate tax exemption in India's post-liberalization history.

Here's the structure:

Tax Holiday Framework (Budget 2026–27):

Component	Details
Duration	Until 2047 (21 years)
Eligible Entities	Foreign companies providing cloud services globally via India-based data centers
Condition	Services to Indian customers must route through a local reseller entity (which remains taxable)
Safe Harbour	15% cost-plus margin for related-party data center services (transfer pricing certainty)
Expected Investment	$70–100 billion in data center capex by 2035

What this means in plain language:

If you're Google, AWS, or Microsoft, and you build a data center in India to serve global customers, your profits on those global revenues are tax-free until 2047.

But if you serve Indian customers, you must route through an Indian reseller entity — which pays full corporate tax.

This is a dual-track taxation model:

Global revenues → 0% tax (incentivizing hyperscaler capex)
Domestic revenues → 22–25% tax (protecting Indian operators)

The P&L Reality: Foreign vs Indian Operators

Let's model this cleanly.

Assume both a foreign hyperscaler and an Indian infrastructure operator handle $10 billion in annual revenue.

Scenario Comparison (Annual, in billions USD):

Scenario	Revenue	Op Margin (%)	Op Profit	Tax Rate (%)	Tax	Net Profit
Foreign Hyperscaler (0% tax)	$10B	30%	$3.0B	0%	$0.00B	$3.0B
Indian Infra (with DCEZ subsidies)	$10B	35%	$3.5B	22%	$0.77B	$2.73B
Indian Infra (no subsidies)	$10B	30%	$3.0B	22%	$0.66B	$2.34B

Key Insight:

The gap between foreign (0% tax) and Indian (22% tax) operators is $0.27B per $10B revenue when Indian operators leverage DCEZ incentives (FSI exemptions, power subsidies, duty waivers).

That 30-basis-point margin gap is the price of sovereignty.

Foreign operators get the tax break.
Indian operators get the land, power, and regulatory carve-outs.

And both need each other.

How Indian Operators Compete Without the Tax Holiday

Indian data center operators (Yotta, Adani-EdgeConneX, CtrlS, Hiranandani) don't compete by chasing the same tax break.

They compete on five different levers:

1. They Are the Landlords of the Tax Break

The 2047 tax holiday applies to foreign cloud profits, not to the Indian data center's revenue.

A foreign hyperscaler must still rent or co-develop capacity in India.

That means Indian operators earn colocation, power, land, and services revenue at full margin — regardless of whether the tenant pays 0% or 25% tax on upstream cloud P&L.

Indian DC players monetize the foreign tax holiday as demand, not as competition.

2. Indian Operators Get a Different Stack of Incentives

They don't have the 0% corporate tax, but they do have state and policy levers that foreign clouds don't directly capture:

Maharashtra, Karnataka, Telangana, UP: Additional FSI, 100% stamp duty exemption, electricity duty waivers, capital subsidies, land subsidies, power bill reimbursements
SEZ / DCEZ benefits: Tax breaks on customs duty, service tax, land acquisition speed
Renewable energy mandates: Indian operators can integrate solar/wind PPAs faster due to local execution networks

These flow to the DC owner/developer, not to the foreign cloud brand.

An Indian operator can structurally lower capex per MW and opex per kWh, partially offsetting the lack of a corporate tax holiday.

3. Sovereign and "Sensitive" Workloads Will Not Sit on Foreign Balance Sheets

Even with a 0% tax carrot, there are categories of demand that:

Must stay on Indian soil, and
Are politically/strategically better hosted in Indian-controlled infrastructure

Think:

Defence, critical infrastructure, law enforcement, elections
Citizen-data platforms, PSU workloads
"Sovereign AI" stacks (like Bhashini + Yotta's Shakti Cloud) where governments explicitly want jurisdiction + governance + Indian majority control, not just location

For that class of demand, an Indian player (or an India-heavy JV) is not a poor cousin.

It is the preferred vendor or gatekeeper.

4. Indian Firms Compete as Infra and JV Platforms, Not as Copy-Paste AWS

An Indian DC company is unlikely to win by building a full global cloud like AWS or Azure.

The rational plays are:

a) Land + Power + Infra Specialist

Own the campus, the power tie-ins, the renewable PPA, the local approvals, the extra FSI — and sell MWs and white-label infrastructure to any cloud, foreign or domestic.

The foreign firm brings the tax-advantaged cloud layer; the Indian firm captures the hard asset economics.

b) JV / Platform Strategy

Adani-EdgeConneX (Adani + EdgeConneX) is the template:

JV with a global operator, but Indian group controls land, power, local execution, and long-term platform value.

c) Specialized "Sovereign Campuses"

Design for:

Higher floor heights
Fault-tolerant power
Liquid cooling
Campus security
Regulatory carve-outs (DCEZ)

Make yourself the only place where certain AI/GPU loads can run under Indian control, even if a foreign player has a tax edge.

In all three, the foreign tax holiday becomes demand fuel, not a direct competitor margin.

5. The Play for Indian Companies: Where They Actually Win

So why start, and how compete?

Sell shovels in the gold rush.

Let foreign clouds enjoy 0% tax; you own the land, power, and racks they must rent.

Your margin sits in infra, services, and local arbitrage, not in global cloud P&L.

Own the "sovereign" and "regulated" niches.

Position as the default for government, PSU, regulated BFSI, defence, and language/identity stacks where India wants control, not just presence.

Exploit local policy and execution advantages.

States are effectively giving Indian DCs a different "tax holiday" via FSI, stamp duty, electricity duty, capex support, and power subsidies.

Combine that with faster land aggregation, local contractor networks, and green-energy integration — things foreign clouds don't want to do themselves at scale.

Be the Layer-0 to Layer-3 landlord.

Foreign clouds are Layer-7/8 (platform + software).

Indian firms can own:

Layer-0: Land
Layer-1: Power
Layer-2: Network
Layer-3: Racks / shells
Layer-4/5: Managed services, sovereign AI hosting

In other words:

Indian companies compete by not trying to be AWS; they become the indispensable landlord, power utility, and sovereign wrapper around AWS-like tenants.

The 0% tax holiday makes India the cheapest place for foreign clouds to grow; Indian infra players are building the corridors and campuses that convert that into rents, subsidies, and strategic leverage.

The Silicon Inflection: 33,000+ GPUs and the East-West Corridor

The GPU Inventory (2026 Commitments)

Here's the sovereign silicon backbone being built right now:

India GPU Pipeline (2026):

Operator	GPU Model	Units	Timeline	Notes
Yotta Shakti Cloud	NVIDIA B200 (Blackwell)	8,000 units	Dec 2026 – Jan 2027	Confirmed order, sovereign AI workloads
Adani-EdgeConneX (Visakhapatnam)	NVIDIA H100 + B200 (expected mix)	25,000–30,000 units	2026–2030 phased rollout	Backed by $15B JV with Google, gigawatt-scale campus

Aggregate: 33,000–38,000 GPUs committed.

This exceeds the 32,000 GPU threshold that positions India as a sovereign AI manufacturing hub, not just a cloud consumption market.

The Visakhapatnam Gigawatt Campus: Breaking the Duopoly

For decades, Indian data center capacity was concentrated in two corridors:

Mumbai (financial services, hyperscaler landing point)
Chennai (subsea cable terminus, latency to Singapore)

The Adani-Google $15B Visakhapatnam campus breaks that duopoly.

Why Visakhapatnam matters:

Geographic:

East coast, closer to ASEAN and East Asia markets
Subsea cable landing potential (reducing latency to Japan, South Korea, Australia)
Land availability at scale (gigawatt campuses need 100+ acres)

Infrastructure:

Port city (heavy equipment logistics for transformers, chillers, modules)
Renewable energy corridor (Andhra Pradesh solar/wind PPAs)
DCEZ designation (FSI exemptions, duty waivers, fast-track approvals)

Capacity:

Gigawatt-scale (1,000+ MW IT load when fully built)
25,000–30,000 GPUs (largest single-site sovereign GPU deployment in India)
Phased rollout (2026–2030, modular expansion as AI demand scales)

This is the first true "East-West Corridor" for AI infrastructure in India.

Mumbai and Chennai remain hyperscaler hubs.

Visakhapatnam becomes the sovereign AI anchor — where Indian-controlled workloads (Bhashini, defence AI, regulated BFSI models) run on Indian-majority infrastructure with guaranteed power and cooling.

The Vastu Layer: When Mechanical, Nuclear, and Thermal Converge

Tying the Threads Together

In my earlier articles, I explored three invisible infrastructures reshaping Indian construction:

"The Sovereign Campus" (Nuclear): How SHANTI-enabled Small Modular Reactors let campuses bring their own baseload, escaping grid queues entirely: The Sovereign Campus Why India's Nuclear Revolution Will Redefine Real Estate
"The Battery in the Wall" (Thermal Storage): How PCM walls and ice tanks shift cooling from 2 PM (peak stress) to 2 AM (off-peak window)The "Battery" in the Wall- Arindam Bose
"4D Printing and Programmed Infrastructure": How buildings learn to respond to monsoons and heat without human intervention4D Printing and the Era of Programmed Infrastructure

The HPWZ is where all three converge.

The Integrated Stack

At the rack level:

Blackwell GPUs push 50–100 kW of heat into liquid cooling loops (immersion tanks, direct-to-chip manifolds).

This is the 27% CAGR mechanical reconstruction we quantified earlier.

At the envelope and basement level:

Thermal storage (PCM walls, ice tanks) turns buildings into silent batteries, shifting that cooling load from 2 PM to 2 AM.

This is the grid-aware cooling layer that prevents AI density from crushing India's substations.

At the boundary fence:

SHANTI-era Small Modular Reactors and long-dated grid contracts decide whether the campus is a tenant of the grid or a sovereign campus that brings its own sun.

This is the energy sovereignty layer that lets AI campuses escape 18–36 month interconnection queues.

The Vastu Metaphor: Agni, Jal, Prithvi, Vayu

In Vastu Shastra, balance comes from five elements:

Agni (Fire): The GPU — 100 kW racks generating heat
Jal (Water): Liquid cooling — immersion tanks, direct-to-chip manifolds
Prithvi (Earth): Sovereign land — DCEZ carve-outs, FSI exemptions, nuclear-ready sites
Vayu (Air): Thermal buffering — ice tanks and PCM walls that breathe with the grid
Aakash (Space): 9.5-meter halls — vertical volume for mechanical infrastructure

The HPWZ isn't a building. It's a coupled thermodynamic machine.

At the rack, Blackwell-class GPUs push heat into liquid loops.

In the envelope and basement, thermal storage turns walls and tanks into silent batteries, shifting cooling from 2 PM to 2 AM.

At the boundary fence, SHANTI-era reactors and long-dated grid contracts decide whether the campus is a tenant of the grid or a sovereign campus that brings its own sun.

In that world, the most valuable square foot in India is not near a food court or Metro station.

It's the square foot that sits inside a hall built for 50–100 kW racks, plumbed for liquid, buffered by thermal storage, and anchored to guaranteed, sovereign power.

The Economics: Why FSI Is Now a Function of Heat, Not Headcount

The 1% Paradox (HPWZ Edition)

Let's be honest:

9.5-meter halls cost more than 3.5-meter slabs.

Liquid cooling systems cost more than air-based CRAC units.

Nuclear-ready land costs more than standard industrial plots.

These are real incremental costs.

But here's what most developers miss:

Translation into Capex %

For large AI-ready campuses, the incremental cost of:

9–10m floor heights (instead of 3.5m)
Liquid cooling infrastructure (instead of air-based)
Thermal storage integration (PCM walls, ice tanks)
Nuclear-ready site selection (seismic + water access)

...is typically <2–3% of total project capex.

But that 2–3% premium unlocks a 100% shift in economics.

Value Unlocked by the Premium

Avoided kVA:

Flattening cooling peaks via thermal storage reduces contracted grid demand by MWs, deferring transformer and HT panel upgrades.

In Noida, Navi Mumbai, Whitefield — where grid queues stretch 18–36 months — this deferral is worth ₹5–10 crore per campus.

Lower diesel usage:

Reduced reliance on gensets during peak or outage scenarios saves millions annually and cuts CO₂.

For hyperscale campuses, diesel OPEX can reach ₹10–15 crore/year.

Thermal storage + liquid cooling cuts diesel runtime by 20–30%.

Green finance eligibility:

Easier IGBC/GRIHA/EDGE credits = eligibility for:

Sustainability-linked loans (10–25 bps interest concession)
H-DREAM-type funds (₹8,400 crore green infra pool)
Additional FAR (5–15% bonus in UP, Haryana, Punjab)

Tenant/AI-client premium:

AI tenants (Google, Microsoft, OpenAI, Anthropic, Indian LLM startups) value resilience and sovereignty.

A 2–3% premium on capex can translate into:

10–15% higher lease rates (vs legacy office stock)
Faster absorption (sovereign + tax-advantaged positioning)
Longer lease terms (10–15 year commitments vs 3–5 year office leases)

Contrast: Commercial Office vs HPWZ

Standard commercial office tenants:

May see 9.5m halls and liquid cooling as "nice-to-have" engineering upgrades.

AI / data center tenants:

That same 2–3% premium is the difference between:

"Grid constraint problem":

Stuck in substation queues
Diesel dependence
Rising OPEX
Uncertain power availability

"Scalable load":

Full IT nameplate capacity
Flatter grid draw
Renewable integration
Premium ESG positioning
Tax-advantaged economics

The FSI Reframe

In the 20th century, FSI was a headcount density metric.

More FSI = more employees = more revenue per square meter.

In the 21st century, FSI is a heat dissipation metric.

More non-FSI utility allowance = more cooling infrastructure = more compute per square meter = more AI revenue per watt.

The HPWZ redefines real estate value:

Not by proximity to transit.
Not by views or amenities.
Not even by fiber connectivity.

By thermodynamic capacity.

Can you house 100 kW racks?
Can you shift cooling load off-peak?
Can you guarantee sovereign power for 10+ years?

If yes, you're an HPWZ.

If no, you're legacy stock.

The Challenge for You — The Reader

If HPWZs truly represent a new asset class — where buildings are valued by thermodynamic capacity rather than headcount density — what breakthrough do you think must happen first for this to scale across India?

Is it:

a) Cost reduction in liquid cooling systems?

Technology is proven, but upfront capex (immersion tanks, manifolds, pumps) still creates friction for Tier-2/Tier-3 developers.

b) Formalization of DCEZ exemptions (9.5m halls, non-FSI utilities) in NBC 2026?

Right now, these are state-level carve-outs and SEZ notifications. Codifying them in the National Building Code would unlock institutional capital at scale.

c) First-mover sovereign AI tenant commitments (10-year leases)?

If Bhashini-scale platforms don't publicly commit to long-term sovereign campus leases, developers won't bet ₹1,000+ crore on speculative HPWZ builds.

d) Grid operators pricing in thermal storage benefits (lower peak charges)?

Without explicit tariff incentives for load-shifting, the economic case for thermal batteries remains invisible to most CFOs.

e) A "gigawatt campus" success story (Vizag operational by 2028)?

If Adani-Google's Visakhapatnam campus comes online on time, on budget, and at full density, the asset class becomes real. If it delays, skepticism persists.

Comment your answer — and let's see where the industry thinks the real bottleneck is.

The Corridor That Rewrote Value

Recast

The HPWZ is not an office building with better HVAC.

It is a machine capital corridor where sovereign intelligence is manufactured, cooled, and defended.

From human warehouse to silicon foundry.
From headcount density to heat dissipation.
From grid tenant to sovereign campus.

The Stakes

The next 100 million square feet India builds will either:

Amplify peak stress → or flatten it
Lock in diesel dependency → or integrate renewables
Wait three years for grid connections → or defer transformer upgrades through thermal storage and sovereign power

The choice is not philosophical.

It is economic.

One Line Summary

If the most valuable square foot in India learns to house 100 kW racks, shift cooling from 2 PM to 2 AM, and anchor to sovereign baseload power, the real estate industry will remember 2026 not as the year office buildings died — but as the year compute corridors quietly rewrote the economics of Floor Space Index.

This was my Technology Tuesday rabbit hole.

Next week?
I'll make myself the same promise:

"Keep it simple, Arindam."

And once again,
I know I'll fail.

Beautifully.

— Arindam Bose

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If buildings can now bring their own sun, store cooling in their walls, and program themselves to breathe — what happens when real estate value is measured in kilowatts per rack instead of rent per square foot?

Welcome to the compute corridor.

→ Read how campuses bring their own power: The Sovereign Campus: Why India's Nuclear Revolution Will Redefine Real Estate The Sovereign Campus Why India's Nuclear Revolution Will Redefine Real Estate
→ Read how walls store cooling: The "Battery" in the Wall: How Thermal Storage Turns Buildings into Silent Grid Assets The "Battery" in the Wall- Arindam Bose
→ Read how buildings learn to respond: 4D Printing and the Era of Programmed Infrastructure 4D Printing and the Era of Programmed Infrastructure