MAROKO133 Eksklusif ai: Scientists put quantum optics on a chip, bringing scalable quantum

📌 MAROKO133 Hot ai: Scientists put quantum optics on a chip, bringing scalable qua

Germany has taken another major step toward realizing scalable quantum computers with the launch of SmaraQ, a collaborative research initiative that integrates quantum optics directly onto a chip. The project, driven by QUDORA Technologies GmbH, AMO GmbH, and Fraunhofer IAF, aims to replace bulky optical assemblies with compact, chip-based systems that promise to make ion-trap quantum computers more efficient and scalable.

Reinventing optical control for ion-trap systems

At the heart of SmaraQ lies a breakthrough in photonic integration. Traditional ion-trap quantum computers rely on intricate arrangements of mirrors and lenses to direct laser beams for qubit control, a setup that becomes increasingly complex as systems grow larger. Each ion, acting as a qubit, must be precisely addressed with laser light for operations like initialization and cooling. Maintaining that precision across hundreds or thousands of qubits has remained a fundamental challenge for scaling up.

SmaraQ addresses this issue by developing ultraviolet (UV) waveguides and photonic components composed of aluminum nitride (AlN) and aluminum oxide (Al₂O₃). These materials are being used to fabricate on-chip waveguides that can channel light directly to the qubits with nanometer-scale precision. The approach eliminates the need for large free-space optics, drastically reducing system size and improving reliability.

“On-chip integration represents the path forward for ion-trap quantum computing,” said Dr. Maik Scheller, Head of Photonics at QUDORA, in a press release. “We are engineering waveguide structures at the nanometer scale, ten thousand times thinner than a human hair, that deliver light with pinpoint precision exactly where our ion qubits demand it.”

This integration not only enhances optical stability but also facilitates the mass production of quantum processors using established semiconductor fabrication methods, a crucial step toward the broader deployment of quantum computing technology.

A collaboration rooted in complementary expertise

SmaraQ brings together three key partners, each contributing distinct technical expertise. QUDORA Technologies, serving as the project coordinator, is responsible for integrating the photonic systems into its trapped-ion quantum computing architecture and driving commercialization beyond the project’s duration. The company’s proprietary NFQC (Next-Generation Field Quantum Computing) technology is known for achieving high qubit coherence and precision control, setting benchmarks in trapped-ion systems.

Fraunhofer IAF contributes its specialization in materials science by developing epitaxial thin-film AlN wafers of exceptional quality, which serve as the foundation for the photonic components. Meanwhile, AMO GmbH applies its advanced nanofabrication capabilities to create and pattern these components onto chips using cutting-edge lithography. Together, these efforts form a Germany-based supply chain for critical quantum computing materials and components, a strategic advantage for maintaining technological independence.

The project’s name, SmaraQ, is inspired by the Smaragdkolibri, also known as the Blue-tailed Emerald Hummingbird, which is renowned for its precision and ability to perceive ultraviolet light. The analogy captures the project’s focus on miniaturization and control at microscopic scales, essential qualities in the world of quantum technology.

Toward sustainable and sovereign quantum technologies

Running from 2025 to 2028, SmaraQ is funded by Germany’s Federal Ministry of Research, Technology, and Space (BMFTR) under a program supporting enabling technologies in quantum research. The initiative is part of a broader national effort to strengthen Europe’s leadership in quantum computing and secure critical supply chains within the continent.

By focusing on scalable, integrated optical technologies, SmaraQ addresses one of the most significant bottlenecks in ion-trap quantum computing. Maintaining precise optical access as qubit numbers increase. If successful, the project could establish a blueprint for industrial-scale quantum processor manufacturing, bridging the gap between laboratory prototypes and commercially viable systems.

🔗 Sumber: interestingengineering.com

📌 MAROKO133 Eksklusif ai: Celosphere 2025: Where enterprise AI moved from experime

Presented by Celonis

After a year of boardroom declarations about “AI transformation,” this was the week where enterprise leaders came together to talk about what actually works. Speaking from the stage at Celosphere in Munich, Celonis co-founder and co-CEO Alexander Rinke set the tone early in his keynote:

“Only 11 % of companies are seeing measurable benefits from AI projects today,” he said. “That’s not an adoption problem. That’s a context problem.”

It’s a sentiment familiar to anyone who’s tried to deploy AI inside a large enterprise. You can’t automate what you don’t understand — and most organizations still lack a unified picture of how work in their companies really gets done.

Celonis’ answer, showcased across three days at the company’s annual event, was less about new tech acronyms and more about connective tissue: how to make AI fit within the messy, living processes that drive business. The company framed it as achieving a real “Return on AI (ROAI)” — measurable impact that comes only when intelligence is grounded in process context.

A living model of how the enterprise works

At the heart of the keynote was what Rinke called a “living digital twin of your operations.” Celonis has been building toward this moment for years — but this was the first time the company made clear how far that concept has evolved.

“We start by freeing the process,” said Rinke. “Freeing it from the restrictions of your current legacy systems.” Data Core, Celonis’ data infrastructure, extracts raw data from source systems. It’s capable of querying billions of records in near real time with sub-minute refresh — extending visibility beyond traditional systems of record.

Built on this foundation, the Process Intelligence Graph sits at the center of the Celonis Platform. It’s a system-agnostic, graph-based model that unifies data across systems, apps, and even devices, including task-mining data that captures clicks, spreadsheets, and browser activity. It combines this data with business context—business rules, KPIs, benchmarks, and exceptions. Every transaction, rule, and process interaction becomes part of a continuously updated replica that reflects how the organization actually operates.

On top of the Graph, the company’s new Build Experience allows organizations to analyze, design, and operate AI-driven, composable processes — integrating AI where it delivers business impact, not just technical demos:

• Analyze where processes stall or repeat

• Design the future state, setting outcomes, guardrails, and AI touchpoints

• Operate with humans, systems, and AI agents working in sync — now orchestrated through a generally available Orchestration Engine that can trigger and monitor every step in one flow

It’s a deliberate shift from discovery-driven AI pilots to outcome-driven AI operations — and a blueprint for orchestrating agentic AI, where human teams, systems, and autonomous agents work together through shared process context rather than in silos.

Real-world proof: Mercedes-Benz, Vinmar, and Uniper

The Celosphere stage offered real proof of theCelonisPlatform in action, through live stories from customers already building on it.

Mercedes-Benz shared how process intelligence became their “connective tissue” during the semiconductor crisis. “We had data everywhere — plants, suppliers, logistics,” recalled Dr. Jörg Burzer, Member of the Board of Management of Mercedes-Benz Group AG. “What we didn’t have was a way to see it together. Celonis helped us connect those dots fast enough to act.”

The partnership has since expanded across eight of the company’s ten most critical processes, from supply chain to quality to after-sales. But what impressed the audience wasn’t just the scale — it was the cultural shift.

“If you show data in context, and let teams visualize processes, you also change the culture,” Burzer said. “It’s not just process transformation — it’s people transformation.”

At Vinmar, CEO Vishal Baid described Celonis as “the foundation of our automation and AI strategy.” His global plastics distribution business has already automated its entire order-to-cash process for a $3 B unit, achieving a 40 % productivity lift. But Baid wasn’t there to just celebrate finished work — he was looking ahead.

“Now we’re tackling the non-algorithmic stuff,” he said. “Matching purchase and sales orders sounds simple until you have thousands of edge cases. We’re building an AI agent that can do that allocation intelligently. That’s the next frontier.”

And in the energy sector, Uniper, with partner Microsoft, demonstrated how process-aware AI copilots are already reshaping operations. Using Celonis and Microsoft’s AI stack, Uniper can predict when hydropower plants will need maintenance — and cluster those jobs to reduce downtime and emissions.

“Each technician, each part, each system plays a role in a living process,” said Hans Berg, Uniper’s CIO. “The human can’t see all of it. But process intelligence can — and it can nudge the system toward the best outcome.”

Agnes Heftberger, CVP & CEO, Microsoft Germany & Austria, who joined Berg on stage, summed it up crisply:

“The hard part isn’t building AI features — it’s scaling them responsibly,” she explained. “You need to marry intelligence with the beating heart of the company: its processes.”

Across the global community, Celonis reports more than $8 billion in realized business valueand over 120 certified value champions — proof that process intelligence is driving measurable impact far beyond pilots. Rinke called it “the early proof points of a true return on AI.”

From closed systems to composable intelligence

Celosphere 2025 marked a shift from architecture to interoperability — from defining enterprise AI to making it work across boundaries.

Rinke’s vision for the future is unapologetically open: “Good things grow from open ecosystems,” he said. That philosophy is taking shape through deeper platform integrations — including Microsoft Fabric, Databricks, and Bloomfilter — with zero-copy, bidirectional lakehouse access that lets customers query process data in place with minimal latency. The company also announced MCP Server support for embedding the Process Intelligence Graph directly into agentic AI platforms like Amazon Bedrock and Microsoft Copilot Studio.

These updates make “composable enterprise AI” tangible — orga…

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🔗 Sumber: venturebeat.com