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The Next Platform: In-depth coverage of high end computing

Oak Ridge Starts Weaving Together A Quantum, Classical HPC, And AI System Stack Dell Bulks Up Hardware As AI Infrastructure Shifts To On-Premises Cisco Wins Over AI Customers With Merchant Silicon And Optics With Its IPO Done, Cerebras Can Get Back To Pushing The AI Envelope HPE Throws VM Users A Lifeline, Unifying Containers And VM Management In Cloud Stack OpenAI, Microsoft And Friends Build A Better, More Scalable Ethernet Compute And Memory Price Hikes Drive IT Spending Way Higher Sometimes, Air Is The Only Way For AI Systems To Keep Their Cool Arista Rides AI Scale Out Networks, Moves Into Scale Across, And Awaits Scale Up If You Can Make A Compute Engine, You Can Sell A Compute Engine Cleveland Clinic Simulates Large Proteins With Quantum-Centric Supercomputing Broadcom Helps CPU And XPU Makers Go Vertical With Compute Microsoft Committed To Doubling AI Infrastructure In Two Years Google Is A Full Stack AI Player, And Is Playing Well AWS Will Be An OEM, Just Like Google And Maybe Microsoft New Google Networks Tuned Up For GenAI Inference And Training Microsoft And OpenAI Remain Friends, Are Looking To Hook Up With Others AI-Driven CPU Shortage Saves Intel’s Financial Cookies The GenAI Battle Shifts From Frontier Models To Agentic Platforms With TPU 8, Google Makes GenAI Systems Much Better, Not Just Bigger Cisco Scales Out Quantum Systems With A Quantum Network Switch The Second Time Will Be The IPO Charm For Cerebras Imagine An Army Of AI Minions Handling Incident Response AI Will Soon Drive A Third Of TSMC’s Business Bechtolsheim & Friends Breathe Life Into Pluggable Optics One Last Time How HPC And AI Digital Twins Accelerate Quantum Error Correction The Embrace Of AI In Design Transforms Cadence And Its Customers Nvidia Brings The Power Of Open Source AI Models To Quantum Computing Building The Imperfect Beast For Enterprises, GPUs Need Virtualization As Much As CPUs Ever Did CoreWeave Takes As Much Financial Engineering As It Does Datacenter Design Contemplating Meta’s Homegrown MTIA Compute Engine Roadmap Most Neoclouds, Sovereigns, And Enterprises Will Buy, Not Build, Their AI Stacks Broadcom And Google Benefit Mightily From Anthropic’s Meteoric Growth Rebellions AI Rings Up The Money To Rack Up AI Inference Systems Nvidia Software Pushes MLPerf Inference Benchmarks To New Highs Broadcom Makes Its Pitch To Run Kubernetes On VMware VCF The $2 Billion Nvidia Deal With Marvell Is About A Lot More Than NVLink Fusion Classiq Says Quantum Is On Its Way, But Patience Is Needed Demonstrating The Scientific Usefulness Of Quantum Systems We Need Servers – Lots Of Servers. . . . Arm Comes Full Circle With Homegrown, AI-Tuned Server CPU Riding The Memory Boom And Trying To Avoid The Bust Data Analytics Helps Make The Mighty Lionesses Roar Driving Down The AI System Roadmap With Nvidia The Open Agentic AI World According To Nvidia Nvidia Finally Admits Why It Shelled Out $20 Billion For Groq Nvidia Says OpenClaw Is To Agentic AI What GPT Was To Chattybots IBM Unrolls Blueprint For Quantum-Classical HPC Computing Women Get Data-Driven Health Boost As The FA Tackles Sports Science Four Months Into Its Comeback, Zapata Stakes Its Claim In Quantum Software Eridu Cuts To The AI Networking Chase With High Radix Switch System HPE Works Harder And Smarter To Chase Datacenter Profits We Need A Proper AI Inference Benchmark Test How AI Is Boosting Gender Equality In High Performance Racing Custom Compute Engine Biz Growing More Than Marvell Ever Hoped Broadcom May Become The Biggest Counterbalance To Nvidia Ayar Labs Gets $500 Million To Ramp Photonics Into 2028 AI Systems With Cisco Outshift, Agentic AI Is Teed Up For the Internet Of Cognition Nvidia Sees The Light On Silicon Photonics And Maybe Optical Switching AI Servers Finally Dominate Dell’s Systems Business VAST Data: What Controls The Data Is More Important Than What Stores It So Far, Nobody Turns Tokens Into Money Like Nvidia SambaNova Pits Its Engineering Against Nvidia For Agentic AI Some More Game Theory, This Time On The AMD-Meta Platforms Deal AMD Says “Helios” Racks And MI400 Series GPUs On Track For 2H 2026 CPU-Only Compute Still Matters To A Lot Of HPC Centers Taalas Etches AI Models Onto Transistors To Rocket Boost Inference Some Game Theory On That Nvidia-Meta Platforms Partnership AI Eats The World, And Most Of Its Flash Storage The Current AI Networking Wave Will Be A Tsunami Of Money By 2027 The Memory Crunch Pinches Cisco’s Profits Only A Few AI Platforms Can Survive The Greatest AI Show On Earth Cisco Doubles Up The Switch Bandwidth To Take On AI Scale Out And Eventually Scale Up Datacenter Spending Forecast Revised Upwards – Yet Again The Twin Engine Strategy That Propels AWS Is Working Well With GenAI Turbochargers, Google Is Shifting Its Cloud Into A Higher Gear AMD Finally Makes More Money On GPUs Than CPUs In A Quarter Dassault And Nvidia Bring Industrial World Models To Physical AI TACC Explores Mixed Precision And FP64 Emulation For HPC With Horizon Robotics Will Break AI infrastructure: Here's What Comes Next Oracle’s Financing Primes The OpenAI Pump Gartner Takes Another Stab At Forecasting AI Spending Microsoft Is More Dependent On OpenAI Than The Converse Big Blue Poised To Peddle Lots Of On Premises GenAI Microsoft Takes On Other Clouds With “Braga” Maia 200 AI Compute Engines Nvidia’s $2 Billion Investment In CoreWeave Is A Drop In A $250 Billion Bucket Intel Is Still Struggling In The Datacenter, But It Could Get Better Is Nvidia Assembling The Parts For Its Next Inference Platform? TSMC Has No Choice But To Trust The Sunny AI Forecasts Of Its Customers Cerebras Inks Transformative $10 Billion Inference Deal With OpenAI By Decade’s End, AI Will Drive More Than Half Of All Chip Sales Startup Quantum Elements Brings AI, Digital Twins To Quantum Computing D-Wave Makes Gate-Model Power Move With Quantum Circuits Buy Building The Future Of Software In The AI-Native Era Arista Modular Switches Aim At Scale Across Networks, Hit Scale Out, Too NextSilicon Takes Aim At CPUs And GPUs With “Maverick-2” Dataflow Engine How HPC Is Igniting Discoveries In Dinosaur Locomotion – And Beyond Oracle First In Line For AMD “Altair” MI450 GPUs, “Helios” Racks
Quantum Pulse Does Industrial Light Magic To Deliver Massive Boost In Qubits
Joe Fay · 2026-06-18 · via The Next Platform: In-depth coverage of high end computing

Israeli quantum startup Quantum Pulse Ventures has unwrapped a manufacturing line tweak that it says promises a ten times boost in quantum computer performance. The company unwrapped its QP2.0 platform at a conference in Edinburgh this week, and said its “composite pulse approach improves operational fidelity and robustness against fabrication variability.”

The platform centers on a redesigned universal directional coupler that it claims delivers “an order-of-magnitude improvement in operational fidelity.” The company likens its directional coupler to a “transistor for optical computing, allowing two qubits to interact in a photonic circuit.

Variations and inaccuracies in manufacturing of photonic circuits cause a cascade of problems that make errors more likely. This is one of the reasons that quantum computer designs must allow for a vast number of physical qubits and extensive error correction in order to deliver one logical qubit, meaning quantum computers, for now, are massive both in size and cost.

Quantum Pulse’s design uses composite wave guides, rather than traditional one segment uniform wave guides, to reduce physical errors and noise in the circuits of these gates. The design is also more resistant to fabrication errors, it claims.

The company said this can be used in a broad class of photonic integrated circuits.  And it can be adopted across a range of current silicon photonics, silicon nitride, thin-film lithium niobate, and related integrated photonics manufacturing processes. Here are the components of its stack:

Ofer Shapiro, co-founder and chief executive officer the Israeli company, said the coupler allowed light to jump from one wave guide to another, similar to a transistor in a traditional CMOS circuit.

The wave guides themselves are “very, very small, they are less than one micrometer in size, and the distance between them has to be accurate in a sub-nanometer level for this operation to be accurate.”

This in turn “becomes a huge manufacturing issue, and that's why many of those solutions are just at the cusp of functionality.”

Sticking with the transistor analogy, Shapiro said: “If someone told you I figured out a way to do microelectronics with one tenth of the energy, it would be huge. It's the same thing for photonics.”

The technology is also applicable to matrix multiply units and quantum routers, the company explained, and would deliver a four times speed boost over existing technologies. Here is how you use the tech to make a matrix multiply unit:

And here is how you use it to make an optical router:

Shapiro was at pains to point out that this doesn’t mean extensive rearchitecting of processor designs or fabrication processes.

“We have a recipe for a better transistor that is more accurate and produces better results, and that's not a different manufacturing process. You don't have to change anything in the fab, you just give it a different image to lithograph on to the chip.”

As for how the company will monetize the innovation, Shapiro said: “It's an IP play. If you want to use that IP in order to introduce it into your own chips, you have to pay royalties. It's a very, very simple model, and also very compelling.”

Given that some optical quantum computers are the size of a stadium, with costs to match, this means a lot. One fault tolerant qubit typically requires 10,000 physical qubit averaging to one fault tolerant qubit, so, Shapiro argued, “If they're ten times better, you only need a thousand and this thing means that everything shrinks in proportion.” Or, put another way, “for the same budget you get ten times more.”

This massively improves the ability to produce those elusive fault-tolerant qubits he claimed. “The first person that would have a commercial 100 fault tolerant qubits would win the race for first practical quantum computer. That's considered the threshold where actually starts to make sense.”

Implementing Quantum Pulse’s design is not a big deal, according to Shapiro. “It requires us to work with that partner to get some information about their manufacturing platform of choice, give them the design for this, let's say the coupler or the polarized controller, whatever the component, probably they need both in most cases. Give them the design for that, they drop it in, and it goes.” He said this should take a couple of manufacturing cycles, or six to nine months.

While Shapiro was adamant that the tech can speed the delivery of practicable quantum computers, the uncertainty, as always, is when that will be. “They're certainly telegraphing to the market that they are almost there, right?

“But the question is, what's almost? It's like we were on autonomous driving for a long time. AI was almost there. I think I remember reading about neural networks 30 years ago, maybe more than that, and, you know, it happened when it happened, and of course it changed the world.”

“I think in five to ten years you will have processors that run electrons and processors that run photons.”

Either way, he said, we are getting to the physical limits of “what you could squeeze from electrons.” This is playing out in both memory – which is seeing soaring prices – and in processing.

“People are looking at architecture of the processor rather than a better transistor because they're getting so small in the process that they are limiting, getting close to the physical barriers, right?”

“There's a limit of how much you can get in a single computer, and then you have to scale it, and the way to scale it is by quantum router.”

By contrast, when it comes to quantum computers, there are several options on how to implement the qubit, he said.

“Some of them are using semiconductors, some of them are using trapped ions, some of them are using optics. It may be that for different applications, different technologies win.”

But while there are a variety of technologies or particles to build a qubit, “when you talk about connecting them, there is no replacement for photons. It has to be based on light, right.”

“This like the race to the moon, almost - It just happens in the private sector in most part, and there's no points for second place.” He pauses for a moment, then adds “I think there may be some for second, but I don't know about the third place.”