No Priors Ep. 93 | With Akash Systems' Felix Ejeckam and Ty Mitchell

No Priors Ep. 93 | With Akash Systems' Felix Ejeckam and Ty Mitchell

No PriorsDec 12, 202442m

Sarah Guo (host), Felix Ejeckam (guest), Ty Mitchell (guest)

Akash Systems’ diamond-based cooling technology and materials-science approachThermal challenges in AI data centers and limitations of current cooling methodsFrom space applications and high-power RF to AI GPUs and serversSystem-level integration, market strategy, and partnerships (e.g., NexGen, Raytheon)U.S. semiconductor manufacturing, CHIPS Act, and national security implicationsSovereign cloud and data localization as an AI infrastructure trendUsing AI to accelerate materials discovery, design, and manufacturing

In this episode of No Priors, featuring Sarah Guo and Felix Ejeckam, No Priors Ep. 93 | With Akash Systems' Felix Ejeckam and Ty Mitchell explores diamond-cooled AI servers promise cooler chips, faster compute, safer grids Akash Systems’ founders Felix Ejeckam and Ty Mitchell explain how lab-grown diamond, the most thermally conductive material, is being integrated directly with semiconductors to cool everything from space radios to AI GPUs. They argue that current data center cooling—fans, liquids, rack-level tricks—only treats symptoms and that physics- and chemistry-driven materials solutions are essential to avoid power crises and performance limits. By bonding synthetic diamond to chips, Akash claims significant temperature drops, better reliability, and headroom to ‘hyper-accelerate Moore’s law’ for AI workloads. The conversation also covers sovereign cloud deployments, U.S. manufacturing and CHIPS Act support, and how AI itself will accelerate materials research and advanced manufacturing.

Diamond-cooled AI servers promise cooler chips, faster compute, safer grids

Akash Systems’ founders Felix Ejeckam and Ty Mitchell explain how lab-grown diamond, the most thermally conductive material, is being integrated directly with semiconductors to cool everything from space radios to AI GPUs. They argue that current data center cooling—fans, liquids, rack-level tricks—only treats symptoms and that physics- and chemistry-driven materials solutions are essential to avoid power crises and performance limits. By bonding synthetic diamond to chips, Akash claims significant temperature drops, better reliability, and headroom to ‘hyper-accelerate Moore’s law’ for AI workloads. The conversation also covers sovereign cloud deployments, U.S. manufacturing and CHIPS Act support, and how AI itself will accelerate materials research and advanced manufacturing.

Key Takeaways

Attack heat at the materials level, not just with more fans and fluid.

Akash’s thesis is that air and liquid cooling mostly operate far away from the heat source; directly integrating ultra-conductive diamond with chips shortens the thermal path, meaning lower temperatures, less throttling, and higher sustained performance.

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Diamond cooling stacks with existing data-center cooling, it doesn’t replace it.

Their servers ship with both NVIDIA’s liquid cooling and diamond cooling, showing that materials-level advances can be layered on top of rack- and facility-level solutions to gain extra thermal and performance margin.

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Thermal constraints are becoming a primary blocker for AI hardware roadmaps.

Mitchell points to delays and heat issues in recent high-end GPUs as an early sign that keeping performance doubling every few years will be limited less by transistor counts than by the ability to remove heat from increasingly dense chips.

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Diamond-enabled cooling could effectively “hyper-accelerate” Moore’s law for AI.

By reducing thermal crosstalk, the company believes transistor density and GPU operating points can rise faster, potentially shrinking timelines for compute-heavy tasks (like generating feature-length films) from days to seconds.

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Sovereign cloud and localized AI infrastructure are major growth vectors.

The NexGen India deal illustrates how countries want AI capacity and data to remain within their borders, creating many regional opportunities for differentiated, high-efficiency infrastructure vendors.

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Rebuilding U.S. manufacturing across the AI stack is a strategic imperative.

They argue that relying on overseas fabs and assembly is risky for both economic resilience and national security, and that CHIPS Act support should foster an end-to-end domestic ecosystem—from materials and chips to racks and data centers.

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AI will dramatically accelerate materials research and manufacturing innovation.

Both founders expect AI models to mine decades of literature, explore chemical space, and run vast design iterations (e. ...

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Notable Quotes

At Akash, as material scientists, we come in at the periodic table level.

Felix Ejeckam

If a physics or chemistry approach to solving the heat problem is not used today, the needs of AI data centers will crash the grid as we know it.

Felix Ejeckam

Everything you mentioned is heat… unless you go to the source of the problem, you’re really just playing whack-a-mole.

Felix Ejeckam

We think that with our diamond technology, we will be able to hyper‑accelerate Moore’s law.

Felix Ejeckam

We are limited by our ability to frame the questions… only by our own imagination really.

Ty Mitchell

Questions Answered in This Episode

What technical and manufacturing hurdles remain to scaling diamond–semiconductor integration for all major AI chips, not just select server SKUs?

Akash Systems’ founders Felix Ejeckam and Ty Mitchell explain how lab-grown diamond, the most thermally conductive material, is being integrated directly with semiconductors to cool everything from space radios to AI GPUs. ...

Get the full analysis with uListen AI

How do the economics of diamond cooling (cost per watt saved or performance gained) compare to aggressive liquid cooling or facility-level retrofits?

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What kinds of new AI workloads or model architectures become feasible if GPUs can reliably run much hotter and denser without throttling?

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How should policymakers balance short-term cost pressures with long-term national security when deciding how much AI manufacturing to localize in the U.S.?

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In practice, how can AI tools be embedded into materials R&D workflows to meaningfully shorten the path from novel idea to deployable device?

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Transcript Preview

Sarah Guo

Welcome to No Priors. Today, I'm chatting with Felix Ajekum and Ty Mitchell, the founders of Akash Systems, which makes diamond-based cooling technology for computing platforms, from space satellites to AI data centers. Their innovation uses highly conductive diamond to help computers run cooler and faster while using less energy. Felix and Ty, welcome to No Priors.

Felix Ejeckam

Good to be here.

Ty Mitchell

Thank you, Sarah.

Sarah Guo

I think we should start with just a quick introduction as to what Akash is.

Felix Ejeckam

Sure. Um, again, very good to be here with you, Sarah. Uh, Akash Systems, we are a venture-backed company based in the Bay Area that is starting from the ground up at the material science level, and we are making, using proprietary materials, materials specifically of diamond that we grow in the lab, using it to make electronic systems that are disruptive in the world, by an order of magnitude. Um, it's in contrast, oftentimes when we start companies, even in the hardware space, we tend to, uh, start injecting ourselves in the middle of a supply chain. At Akash, as material scientists, we come in at the periodic table level, uh, and we start there to build up, uh, chips, boards, systems that ultimately change the lives of our society, whether you're in business or as a consumer. Um, and we do that in several ways. Um, we change the structure of a basic material. Uh, the systems that we've chosen to affect, uh, we started off in the space world where we make some of the fastest satellite radios ever made by humans. Uh, and then we go over, as we are doing now, to AI, where we are able to cause compute, uh, a, a GPU to go faster than has ever been done before since the beginning of, of this, this, uh, this new space, uh, or reducing energy consumption in the data center by a significant amount, all because of innovative material science that we've pioneered at the ground floor.

Sarah Guo

So maybe that's a good segue into, uh, how you got started working on this, because you've had this idea for a long time. As you said, you started on, um, uh, space applications earlier. Can you talk a little bit about your background and, you know, the original scientific idea and how you thought it would be applied?

Felix Ejeckam

Sure. Uh, so my background is in material science and electrical engineering. I obtained a PhD in electrical engineering with a minor in material science and device physics from Cornell. Uh, and in my PhD, uh, I focused on bringing together very dissimilar materials, uh, s- in such a way that one plus one equals 10, okay? Uh, and, and, you know, for example, silicon, very well-known, ubiquitous material that's ushered in the current modern era that we have today. Uh, but then there are other materials, plastics, other types of semiconductors, that don't actually do as well as silicon, but they have their own strengths. Um, and so for my PhD, I looked at ways of trying to bring together, say, the optics world with electronics, silicon, and merging them together as such that the overall system is incredibly powerful. That philosophy I've brought, uh, to Akash, uh, when I started Akash with Ty in 2017 to try to do the same thing, um, I've often found personally, uh... And actually it's, I think it's a very good, good metaphor for, for, for humans, how we interact with, together. When you bring different people that have different strengths, the combination can be incredibly powerful in ways that excel and exceed the simple summation of the parts. Uh, and that's exactly what we do at Akash, where we bring, uh, artificial diamonds, well-known as the most thermally conductive material ever grown in nature or ever to occur in nature, and then silicon, or even gallium nitride, and quite frankly, any other semiconductor. When brought together, amazing things happen. Um, very happy and excited about doing that in the, in the world of AI. Uh, we did that in space, uh, where we have now made and launched, uh, s- the fastest radios ever made by, by, by man. Uh, and now with, uh, AI, we're able to, to achieve, uh, performance levels, whether in energy, uh, efficiency levels or, or compute speeds, uh, ever obtained by simply using these, these artificial materials, uh, that we've created in the lab.

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