Keri Keinath

on a mission to solve the world’s most complex scientific problems @atomiqaquantum

[Keri Keinath @kerikeiii]

more data = less qubits

[Atomiqa @atomiqaquantum]

With these executive orders, the @WhiteHouse takes a decisive step to secure quantum leadership, not as an abstract scientific pursuit, but as a strategic foundation for industrial strength, energy systems, and national security.

At @atomiqaquantum, we build the scientific intelligence platform that translate these national investments into scalable outcomes: accelerating materials discovery for next-generation energy and manufacturing, optimizing complex industrial processes, and closing the gap between theoretical breakthroughs and deployable advantage.

Policy creates the runway. Execution determines who leads.

[Atomiqa @atomiqaquantum]

HALEU supply has become a binding constraint on advanced nuclear deployment. Without scaled domestic enrichment, projected demand is unattainable and nuclear progress is throttled.

Atomic-scale materials modeling can unlock critical throughput by optimizing enrichment cascades, fuel fabrication yields, cladding performance, and recycling efficiency, accelerating reliable HALEU supply and enabling the next wave of clean energy systems.

#HALEU #NuclearEnergy

[Atomiqa @atomiqaquantum]

MXenes have the properties to outperform today’s battery materials - higher conductivity, faster ion transport, more active surfaces, yet deployment has been blocked by atomic‑level disorder in their structure and surfaces.

Different metals randomly mixed, messy surface terminations (–O, –OH, –F), uncontrolled defects, and variable layer spacing all reshape electron and ion pathways, so each batch behaves differently and refuses to scale.

By surfacing these atomic‑level insights, we can deliberately engineer charge rate, capacity, and stability, positioning MXenes as a serious foundation for next‑generation energy devices, not just research.

[Keri Keinath @kerikeiii]

Classical data platforms optimize what we already know. Quantum + AI surfaces what the system is trying to hide.

[Prof. Feynman @ProfFeynman]

Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.

[Keri Keinath @kerikeiii]

If you think I use LLMs like a normal person, think again.

[Keri Keinath @kerikeiii]

When you model your DNA using quantum compute + @GoogleDeepMind and uncover an undiagnosed rare autoimmune disease that inevitably leads to osteoporosis and diabetes 🧬

[Atomiqa @atomiqaquantum]

We are excited to share that Atomiqa is a Startup Sponsor at Quantum Tech World 2026, June 25-26 at Encore Boston Harbor in Boston.

Atomiqa's platform is built for engineering teams across advanced materials, aerospace and defense, automotive, energy, pharmaceuticals, and semiconductors who are tackling impossible problems and need faster, more predictable paths from discovery to commercialization.

⚛️ Swing by Booth SU8 to see how Atomiqa's scientific intelligence platform turns complex enterprise data into innovative scientific breakthroughs with AI and quantum.

[Keri Keinath @kerikeiii]

At @awscloud, we operated 1–2 years ahead of the broader tech narrative. Over time, I became a trusted advisor to investors performing diligence on AI and infrastructure opportunities. The speed and execution with which AWS built and shipped infrastructure and developer tooling was unmatched. Whenever an investor sent me a deal, my consistent feedback was that most were not positioned to win.

Over a year ago, I shared my view that AI would become the new horizontal layer across every tech stack. That shift was validated as big tech announced mass layoffs; not primarily to replace humans with AI, but to reallocate capital toward massive data center buildouts and partnerships with @OpenAI.

Many VCs are still hunting for the next @AnthropicAI unicorn, but the core AI infrastructure wave has passed. As Jensen Huang highlighted at GTC, @nvidia and @Microsoft have been jointly developing the next-generation PC for nearly three years. The future of AI is no longer speculative, it is being deployed in real time.

Where big tech doesn’t play is in building enterprise software that truly aligns technology with the mission-critical challenges customers are determined to solve.

The next unicorn will be founded at the intersection of deep enterprise insight and technical foresight: companies that understand exactly how large organizations will adopt today’s technology while deliberately building for the next wave.

[NVIDIA Newsroom @nvidianewsroom]

News at #NVIDIAGTC Taipei:

@NVIDIARTXSpark debuts at GTC Taipei as a new beginning for personal computers.

The 1-petaflop superchip brings the full CUDA and RTX ecosystem, Windows-native agents and NVIDIA AI and graphics technology to slim Windows laptops and compact desktops built for creators, AI developers and gamers.

[Keri Keinath @kerikeiii]

Beam me up, Scotty 🚀

[zerohedge @zerohedge]

US TO GRANT $2B TO 9 QUANTUM COMPUTING FIRMS, TAKE STAKES: WSJ

Among companies receiving funds:

IBM: $1BN
GFS: $375MM
QBTS: $100MM
RGTI: $100MM
INFQ: $100MM

[Keri Keinath @kerikeiii]

Growing up in the 90’s meant staying up all night just to build an entire theme park on Rollercoaster Tycoon or creating a new world in the Sims. We had the luxury of our parents being naively unaware of the dangers of the internet and the power to roam the virtual world freely. I feel like I’m living in that same world again and it’s bringing out that same childhood curiosity that can’t help but tinker and explore new AI tools launching what feels like every hour. But instead of using software to build an alternate reality, AI is bridging the gap between imagination and our physical world.

[Keri Keinath @kerikeiii]

No one is coming to save you. In fact doctors and standard medical advice substantially contributed to the decline of my health. I am by no means advocating for blind irresponsible experimentation, but like myself, I know many who have been gaslit into thinking nothing is wrong with them. When in reality our body is the only evidence we need to know that something isn’t right. This data tells a bigger story beyond peptides; the current system is broken and people are willing to pay a high premium, where the market is trending in a direction of radical change.

[Peptime @ItsPeptime]

https://t.co/p4qvtJKqRB

[Keri Keinath @kerikeiii]

The extremities of a line are points.

[Keri Keinath @kerikeiii]

@rdominguezibar CLAUDE

[Keri Keinath @kerikeiii]

Leave it to Kathy Hilton to make AI Oprah’s jello diet iconic. #RHOBH

[Keri Keinath @kerikeiii]

The real win for companies? Purpose-built compute that slashes energy use 60+%, delivers up to 40% better price performance, and often requires minimal customer lift.

At AWS I worked with customers on datacenter exits & modernization to adopt Graviton, Trainium & Inferentia chips. Most overlooked $100Ms in cost-savings and the massive impact on achieving carbon-savings. One CTO recognized this early on and we mapped out a plan to adopt more efficient compute that would enable them to meet corporate emissions targets in under 2 years.

Net-zero doesn’t have to be a trade-off. It’s often the smarter business move, but many miss these hidden wins.

[TIME @TIME]

A look at how business and finance are really talking about climate change
https://t.co/eOupwpbco8

[Keri Keinath @kerikeiii]

There is a common misconception that quantum is still years away.

In reality, enterprise companies are already moving beyond experimentation into measurable value.

The divergence between how it’s perceived and how it’s actually being used is where things get interesting.

The question is no longer whether this reshapes industries, but who is positioned early enough to capitalize on it.

https://t.co/c7we23g5Qv

[Keri Keinath @kerikeiii]

The value chain starts at 1. Materials.

Materials innovation is the real barrier to AI scalability. Model sizes and clusters are exploding, but copper interconnects have hit the wall on bandwidth and power. Photonics is the escape hatch, yet it all rests on breakthroughs in substrates, compounds, and optical materials that can be manufactured reliably and at volume.

No material progress = no bigger models, no cheaper inference, no energy-efficient AI at the next scale.

We’re back to atoms: the fundamental physical materials that determine what’s actually possible..

The next decade of AI progress will be decided in the materials lab, the fab, and the supply chain.

[Justin Banks @RealJGBanks]

AI PHOTONICS INFRASTRUCTURE

Here’s the full stack:

1. Materials / Substrates
$AXTI $WOLF $IQE $GLW $LPTH

2. Equipment / Fabrication
$ASML $AMAT $LRCX $KLAC

3. Lasers / Optical Engines
$LITE $COHR $LASR $SMTC $QCLS

4. Foundries / Manufacturing
$TSM $GFS $UMC $INTC

5. Modules + Testing
$AEHR $VIAV $ONTO $AMKR $FN
$AAOI $POET $JBL $LWLG $SIVE

6. Networking / Interconnect
$CRDO $MRVL $AVGO $ANET $CIEN $ALAB

[Keri Keinath @kerikeiii]

@GauravBhogale @Isabelle_D10 @MarwanRefaat @mantisVC Pitch competition, but pitching while gaming 🎮