🥵💥 Data Centers Are Melting the Grid. Here's What Comes Next.

Happy Monday! This week’s deep dive looks at data center cooling. As power densities increase and chips get hotter, managing heat is becoming a key constraint for AI infrastructure. We explore the technologies aiming to solve it.

In our spotlights, we cover SpiNNcloud’s neuromorphic supercomputer deployment in Leipzig and Kleiner Perkins-backed Ambiq’s small cap IPO debut.

We also highlight key headlines across AI, semiconductors, quantum, neuromorphic, photonics, and data centers, along with curated readings on smarter chips, long-range qubit coupling, and global data center capacity. Funding news was dominated by OpenAI’s $8.3 billion round, alongside several notable Series A to C deals

In our bonus sections (yes, two this time), we take a closer look at Meta’s superintelligence ambitions and Germany’s updated Hightech Agenda, which may be worth a glance for some founders.

Deep Dive: Data Centers Are Melting the Grid. Here's What Comes Next.

As power densities rise and system architectures grow more complex, chips run hotter, making cooling a critical constraint. It already accounts for up to 45% of a data center’s energy use and could reach 5% of global electricity consumption by 2030.

In this deep dive, we break down three dimensions shaping the future of thermal management: 1) Cooling architectures, 2) cooling mechanisms, and 3) an emerging strategy beyond cooling.

Cooling Architectures

Direct-to-Chip Cooling
This is one of the most widely adopted solutions in data centers today. It involves placing a cold plate directly on the chip package. Liquid coolant circulates through the plate, absorbing heat and carrying it away.

• Where it’s used: e.g. AI servers, HPC clusters, and systems where air cooling no longer suffices

• Why it works: Efficient heat transfer with relatively low infrastructure change

• Limitations: Can’t always target specific die hotspots; performance depends on coolant flow rate and material conductivity

On-Chip Cooling
This method tackles heat at the source, directly on or within the silicon. Microchannels, vapor chambers, or embedded cooling structures extract heat from hotspots at the transistor or die level.

• Where it’s used: e.g. ultra high power density chips, 3-D stacked chips, or AI accelerators to cool at the heat source

• Why it works: Targets the most critical thermal zones with high precision

• Limitations: Requires custom chip packaging and is not yet standard in data center hardware

Immersion Cooling
In immersion systems, entire servers are submerged in a non-conductive liquid. Heat dissipates through contact with the fluid, which may remain liquid (single-phase) or evaporate and condense (two-phase).

• Where it’s used: Densely packed compute clusters, edge data centers, and environments where airflow is constrained

• Why it works: Uniform cooling across all components; can reduce energy use and noise

• Limitations: Requires new workflows, server designs, and liquid handling infrastructure

Cooling Mechanisms

Single-Phase Cooling
In single-phase systems, the coolant remains in the same physical state (liquid) throughout the entire heat removal process. Heat is absorbed as the fluid passes over or through hot components, but no evaporation occurs.

• Where it’s used: Most current data centers, especially with direct-to-chip systems

• Why it works: Simpler to control and integrate, avoids managing vapor behavior

• Limitations: Lower heat transfer efficiency than two-phase; larger flow rates may be needed to compensate

Two-Phase Cooling
In two-phase systems, the coolant evaporates as it absorbs heat, turning into vapor. That vapor is then condensed back into liquid elsewhere in the system. The phase change dramatically improves heat transfer.

• Where it’s used: Advanced cooling setups, including some immersion systems and advanced cold plates

• Why it works: Phase change allows more efficient heat removal, especially at high power densities

• Limitations: Requires careful control of bubble dynamics and pressure; harder to standardize and integrate

Beyond Cooling: Reusing Waste Heat

Most cooling systems focus on removing heat, but increasingly, there’s interest in reusing it and thereby turning thermal loss into value. Two-phase and immersion systems are especially promising here, as they output higher temperatures suitable for district heating or industrial use. Adoption, however, remains limited by infrastructure complexity.

If you’re curious how new materials can unlock more efficient heat transfer and make advanced cooling systems viable at scale, read our interview with Apheros co-founder and CEO Julia Carpenter.

Spotlights

🧠 SpiNNcloud to deploy neuromorphic supercomputer at Leipzig University (Data Center Dynamics)

“German neuromorphic supercomputing company SpiNNcloud will deliver a brain-inspired supercomputer to Leipzig University. The system, which will be used to support research into drug discovery, will comprise 656,640 cores and simulate a minimum of 650 million neurons for AI, HPC, and other applications, making it the largest SpiNNcloud Server System to be deployed to-date.”

Keep an eye out for our upcoming interview with SpiNNcloud on the Future of Computing blog!

🦾 Kleiner Perkins–backed Ambiq pops on IPO debut (TechCrunch)

“Ambiq Micro, a 15-year-old manufacturer of energy-efficient chips for wearable and medical devices, closed its first day of trading on Wednesday at $38.53 a share, a 61% increase from the $24 IPO price the company set the previous day.”

Relevant to investors assessing exit opportunities: “The success of the IPO signals strong investor demand in the public market for new small-cap companies benefiting from AI innovation. […] Ambiq closed its first day as a public company with a valuation of $656 million (excluding employee options).”

Headlines

Last week’s headlines span billion-dollar chip deals, progress in quantum control systems, and emerging applications in neuromorphic and photonic tech.

 🤖 AI

Anthropic reportedly nears $170B valuation with potential $5B round (TechCrunch)

🦾 Semiconductors

Nvidia AI Chip Challenger Groq Said to Be Nearing New Fundraising at $6B Valuation (TechCrunch)

Elon Musk confirms Tesla has signed a $16.5 billion chip contract with Samsung Electronics (CNBC)

Infineon Technologies, NXP and STMicroelectronics face rising competition in $132 B automotive semiconductor race (Yole Group)

Nvidia says its chips have no 'backdoors' after China flags H20 security concerns (Reuters)

⚛️ Quantum Computing

Fujitsu starts official development of plus‑10,000 qubit superconducting quantum computer targeting completion in 2030 (Fujitsu)

New quantum state of matter found at interface of exotic materials (Phys.org)

A new open‑source program for quantum physics helps researchers obtain results in record time (Phys.org)

CERN Researchers Demonstrate Antimatter Qubit, but Maybe Don’t Expect That Antimatter Quantum Computer Just Yet (The Quantum Insider)

Newly Patented Cooling Tech Promises Cheaper, Simpler Access to Sub‑Kelvin Temperatures (The Quantum Insider)

Next defense department’s X‑37B mission to carry quantum sensor, laser link experiments (Breaking Defense)

🧠 Neuromorphic Computing

“They’re Watching Us Think”: Panic Erupts as Brain‑Inspired Vision Tech Gives Robots and EVs Human‑Like Perception in Real Time (Caernarfon Herald)

Neuromorphic Computing Chip Market: Demand Analysis Across Key Sectors 2025‑2032 (NewsTrail)

Brain‑inspired AI breakthrough: Machines learn to see smarter (The Brighter Side)

⚡️ Photonic / Optical Computing

Xanadu and HyperLight Unveil Advances in Photonic Chips, Setting New Quantum Computing Benchmarks (The Quantum Insider)

💥 Data Centers

Meta to spend up to $72 B on AI infrastructure in 2025 as compute arms race escalates (TechCrunch)

Green Critical Minerals targets AI data center boom with advanced thermal technology (CruxInvestor)

AI Data Centers Market Size and Forecast 2025 to 2034 (Precedence Research)

Readings

This week’s reading list explores AI-driven semiconductor innovation, new models of quantum connectivity, brain-inspired machine learning, and global data center capacity.

🦾 Semiconductors

The New Chips Designed to Solve AI’s Energy Problem (Wall Street Journal) (6 mins)

How AI Will Impact Chip Design And Designers (Semiconductor Engineering) (11 mins)

New Wave of Research Expands View of What Semiconductors Can Do (All About Circuits) (6 mins)

⚛️ Quantum Computing

Topological Edge States Enable Long-Range Coupling Between Distant Qubits (Quantum Zeitgeist) (7 mins)

🧠 Neuromorphic Computing

From AI to Organoids: How Growing Brain‑Like Structures Are Advancing Machine Learning (Unite.AI) (11 mins)

💥 Data Centers

Data Center Capacity Around the World (Visual Capitalist) (Interactive Map)

Funding News

Last week’s funding activity ranges from early-stage AI and secure computing to major rounds in semiconductors, photonics, and cloud. OpenAI’s $8.3B round leads the list, with several Series B and C deals showing sustained later-stage interest.

PS: While Tzafon is an “agentic AI” startup, we think it still belongs in this list given its focus on building scalable compute infrastructure alongside its core software work.

Bonus 1: Zuckerberg’s Superintelligence Vision

Mark Zuckerberg published a rather abstract and visionary letter on Superintelligence, focusing more on long-term vision than near-term technology or business impact.

The timing coincided with a blockbuster quarterly report, featuring earnings per share up 38% compared to the same period last year. The press responded, reflecting growing investor interest and mixed views on Meta’s AI trajectory.

Meta’s ‘superintelligence’ isn’t here yet. But its AI bets are already paying off (CNN)

Zuckerberg claims ‘superintelligence is now in sight’ as Meta lavishes billions on AI (The Guardian)

Meta's year of bold 'superintelligence' bets unlikely to pump profits (Reuters)

Meta further increases sales and profits, builds on personal superintelligence (Heise)

Bonus 2: Germany’s “Hightech Agenda” — Boring to Some, Relevant to Others

Germany has updated its “Hightech Agenda”, a strategy to boost its role in key technologies. While not too exciting for many, it could be relevant to founders in Germany. We selected the computing-related resources (German only):

Hightech Agenda Deutschland: Quantentechnologie (Bundesministerium für Forschung, Technologie und Raumfahrt)

Hightech Agenda Deutschland: Mikroelektronik (Bundesministerium für Forschung, Technologie und Raumfahrt)

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