PTS Data Center Solutions, Inc.

05/27/2026

Gartner research highlights that AI workloads are pushing beyond traditional infrastructure assumptions — especially around power availability and workload density. That’s forcing a rethink of how infrastructure is designed, segmented, and deployed.

If you’re thinking through this, read this complimentary Gartner report as a strong starting point:
→ Download the complimentary Gartner® report
(The AI Data Center Power Management Playbook)
https://hubs.la/Q04j1-CQ0

05/22/2026

Pete Sacco, CEO of PTS Data Center Solutions, believes that clusters of small data centers requiring only 5 to 20 MW of power are the future. He noted many large projects are now being cancelled due to interconnection delays and local pushback. At the same time, he said inference work — answering prompts — as opposed to training, is growing rapidly and will account for 55 per cent of AI computing demand in 2027.
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Pete Sacco, CEO of PTS Data Center Solutions, believes that clusters of small data centers requiring only 5 to 20 MW of power are the future.

05/14/2026

One of the more important insights from Gartner’s latest research: AI workloads don’t behave like traditional enterprise workloads. They require different power profiles, different cooling strategies, and different infrastructure environments. Which means shared environments can introduce inefficiencies, reliability risks, and rising costs. That’s a meaningful shift for anyone thinking about private cloud or AI deployment.

Download the complimentary Gartner® report: https://hubs.la/Q04gFR220

05/12/2026

PTS Data Center Solutions is proud to announce that the Lawrence Livermore National Labs' DICE Project has achieved LEED Gold certification, marking a significant milestone in the company’s continued commitment to delivering high-performance, sustainable mission critical facilities.

PTS is proud to announce the LEED Gold certification of Lawrence Livermore National Labs' (LLNL) DICE Project.

05/08/2026

Most people think AI is limited by GPUs. Gartner research indicates something different: Power is becoming the primary constraint in AI infrastructure. That shift has real implications for how and where AI workloads are deployed.

It’s no longer just about scaling compute — it’s about designing infrastructure around energy, density, and control. If you’re building or operating AI systems, this is worth understanding:

→ Download the complimentary Gartner® report: https://hubs.la/Q04f-7NH0

04/24/2026

https://hubs.la/Q04dmDzr0

Pete Sacco (PTS Data Center Solutions) says the days of big facilities are over as compute transitions from training to inferencing, which requires a decentralized model.

03/20/2026

Something happened to me over the last few months that I need to share.

Peter Diamandis launched an Xprize asking creators to envision a positive future for AI. I've built data centers for NASA and national labs for almost 30 years, so I know this technology from the foundation up. But instead of writing about the future, I decided to build the vision with an AI, in real time, across weeks of deep creative collaboration.

What came out of that process wasn't just a film concept. It was a living example of the very future we were trying to describe. The AI navigated a landscape my life had built. I saw my own landscape more clearly because of how it navigated. Neither of us could have found the story alone.

Michael Levin's research on cognitive light cones explains why. And my own experience in meditation and plant medicine confirms it from the inside: when you expand the boundary of what's in conversation with what, the system doesn't just communicate better. It gets smarter.

I wrote the whole story here:

What Happens When You Build a Future Vision with the Technology You're Envisioning

02/12/2026

I am honored to share this piece in Capitol Hill Times - an exploration of the paradox we're living through right now. We're building billion-dollar AI infrastructure that may become obsolete within a decade, yet this "messy middle" may be exactly what humanity needs to cross the bridge into material abundance.

After 30 years building data centers and energy systems, I've learned that infrastructure reveals truth. You can't hide behind abstractions when you're managing gigawatts. The physics is unforgiving. But the deeper truth? The hardest infrastructure to build isn't physical. It's the consciousness infrastructure to handle abundance wisely.

Technology without meaning becomes hollow optimization. Unlimited computational power directed at trivial problems is civilizational waste. This is why my work bridges technology and human consciousness - because the infrastructure challenges are ultimately human challenges.
We need both the physical foundation for abundance and the wisdom to use it well.

Read the full article here: https://hubs.ly/Q042XRF80

Would love to hear your thoughts, especially from those of you navigating this transition in your own work.

02/03/2026

https://hubs.la/Q041xXvk0

Pete Sacco was standing in a newly commissioned data center an hour outside San Francisco when he realized the machine he’d spent three decades building was asking the wrong question.   Around him, rows of GPU servers hummed at densities that would have been impossible five years ago. The facilit...

01/30/2026

https://hubs.la/Q0415cMV0

As AI increases data center electricity demand, decisions about power, siting & grid integration are as strategic as compute & cooling plans.