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Antimatter Launches as the World’s First Vertically Integrated Neocloud for AI Inference, Plans to Establish Global Headquarters in Hong Kong

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Combining over 1GW of secured power capacity across distributed micro-power sites in the US, Europe and GCC, Antimatter will deploy a global network of 1,000 distributed micro data centers to serve the growing AI inference market  — 5 times faster and 50% cheaper than hyperscalers

HONG KONG, May 4, 2026 /PRNewswire/ — Antimatter, a new category of neocloud purpose-built for the distributed AI economy, today announced its launch through the strategic combination of three companies: Datafactory (US-based energy and power infrastructure), Policloud (modular micro data center network), and Hivenet (distributed cloud provider).

The combined entity creates the industry’s first fully integrated AI infrastructure platform spanning energy sourcing, physical hardware, and cloud software — designed to serve the explosive global demand for AI inference at a fraction of hyperscale cost and dramatically faster time to market.

Antimatter plans to establish its global headquarters in Hong Kong, and is deploying capital at an unprecedented pace to build out the first global neocloud network optimized for AI inference. The company is securing €300 million to fund the deployment of its first 100 Policloud units in 2026, representing 40,000 GPUs and over 3.6 exaFLOPS of active compute capacity.

By the end of 2030, the planned network of 1,000 Policlouds will provide more than 400,000 GPUs and over 36 exaFLOPS of distributed AI inference capacity — the equivalent of five traditional hyperscale data centers, deployed across dozens of countries with 50% lower capital spending and significantly faster time to market.

Antimatter is led by David Gurlé, the serial high-tech entrepreneur who founded Microsoft’s Real-Time Communications business (today’s Microsoft Teams), led Skype’s enterprise division and its sale to Microsoft, and founded Symphony Communication Services.

“In the age of AI, intelligence is not the bottleneck — energy is,” said David Gurlé, Cofounder, Executive Chairman, and CEO of Antimatter. “The infrastructure built for the first era of cloud and AI was designed around centralized scale. But the inference era requires a different model: more distributed, faster to deploy, and sovereign by design. That is the infrastructure Antimatter is building.”

Why AI Inference is Breaking the Cloud Model

The first wave of AI was about training massive models in centralized data centers. But the next phase — inference — is about running those models billions of times per day, across applications like copilots, agents, and real-time decision systems.

That shift changes everything. Inference requires infrastructure that is closer to users, faster to deploy, more energy-efficient, and geographically distributed. Traditional hyperscalers were not built for this. Their model relies on massive, centralized campuses that can take years to build and require enormous upfront capital.

Antimatter’s answer: bring the data center to the energy, not the energy to the data center.

The global data center capacity market is projected to grow from 55GW in 2023 to 220GW by 2030 — a 22% CAGR — yet grid connection queues and infrastructure delays are emerging as the primary bottleneck. In Europe alone, more than 12 TWh of renewable electricity were curtailed in 2023, representing over €4.2 billion in lost value. At the same time, more than 1,000GW of additional renewable capacity remains stuck in permitting and grid-connection queues across Europe and the GCC.

A Full-Stack Neocloud Built for the AI Inference Era

Antimatter is uniquely positioned as the only neocloud that controls the complete value chain:

Energy-first model
More than 1GW of secured power capacity, including over 160MW already operational across Texas and Oregon, USA. Antimatter deploys Policloud units directly at or near existing power assets — including wind, solar, hydro, or biogas sites — converting stranded generation into productive AI infrastructure in a matter of months, rather than waiting years for new transmission capacity.

Decentralized infrastructure layer
A fleet of modular, containerized micro data centers, each housing up to 400 GPUs and deployable in as little as five months, compared with 24+ months for traditional hyperscale builds. Antimatter currently operates 17 units across 8 sites and has a commercial pipeline of more than 500 additional units.

Distributed software layer
A proprietary distributed computing and storage platform providing the orchestration intelligence that connects distributed hardware into a single, sovereign cloud fabric with global default Tier 3 capability — supporting billions of inference requests each day, with sub-10ms latency for edge workloads and full data sovereignty for regulated industries.

Key Competitive Advantages

Metric

Antimatter

Traditional Hyperscale

Capex per fully loaded MW

~US$7M

~US$35M

Deployment timeline

5 months

24+ months

Customer pricing

~50% below hyperscalers

Market rate

Edge latency

Sub-10ms

Variable

Carbon reduction

~70% lower;

zero water cooling

Standard

Data sovereignty

Sovereign-by-design;

local jurisdiction

Bolt-on solutions

Strong Commercial Traction

Antimatter enters the market as a cash-flow positive entity with demonstrated commercial momentum:

US$20 million in current annual revenueUS$4 million in EBIT4,500 GPUs deployed with demand for 10,000+100 Policlouds being deployed in 2026, representing 40,000+ GPUs1,000 Policlouds planned by end of 2030, representing 400,000+ GPUsDiversified customer base: Energy sector (35%), Public sector (30%), Agriculture (15%), Corporates (20%)

The company is targeting $250M+ in revenue within the next 18 months and $2.5B+ by the end of 2030.

Investor Perspectives

“AI infrastructure is now a strategic asset class, and the winners will be those who can combine hard assets with software at scale. Antimatter’s vertically integrated model — from megawatts to APIs — is exactly the kind of infrastructure we believe can define the next decade of digital growth.”

— Alex Manson, CEO of SC Ventures, Standard Chartered Bank

“France and Europe need sovereign, energy-efficient infrastructure to compete in AI. What convinced us about Antimatter is not just the technology, but the ability to deploy micro data centers in months, on existing power assets, while meeting the most demanding regulatory constraints.”

— Stéphanie Hospital, Founder and CEO of OneRagtime

“From Dubai, we see first-hand how emerging markets are skipping legacy infrastructure and going straight to AI-native architectures. Antimatter’s model — distributed, capital-efficient and deeply integrated with energy — is built for exactly these markets, and for the next generation of AI companies we back.”

— Noor Sweid, Founder and Managing Partner, Global Ventures

“At Inria, we work every day at the frontier of AI and high-performance computing. Antimatter’s approach is compelling because it reconciles cutting-edge AI workloads with more frugal, sustainable infrastructure — distributed, software-defined, and close to available energy. It is a strong illustration of the deeptech industrial story we want to see emerge in Europe.”

— Bruno Sportisse, Chairman and CEO of Inria

 

About Antimatter
Antimatter is the distributed neocloud for AI inference. By vertically integrating energy, modular infrastructure, and orchestration software, Antimatter deploys enterprise-grade AI compute infrastructure faster, cheaper, and more sustainably than traditional hyperscale providers. Headquartered in Cannes, France, with major operations in the United States, Antimatter serves enterprises, governments, and AI companies worldwide.

www.antimatter.com

About the Founder
David Gurlé is a French entrepreneur, engineer, and Chevalier of the Légion d’Honneur. He has founded seven companies, including Symphony Communication Services ($1.4B valuation), and held senior leadership roles at Microsoft (where he founded the Real-Time Communications business), Thomson Reuters, and Skype (VP & General Manager, Enterprise). He holds an MSc in Computer Science and Telecommunications from EFREI Paris.

Media Enquiries:
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Tel: (852) 2864 4805

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Angela Shen

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Ariane Forgues

Email: aforgues@mantu.com

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Algorized and ZHAW School of Engineering Launch Research on Predicting Human Movement Around Collaborative Robots, funded by InnoSuisse

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A two-year program studies how sensor fusion enhances human presence detection and safe human-machine interaction.

ETOY, Switzerland, Oct. 20, 2026 /PRNewswire/ — Robots working beside people need a reliable estimate of human movement. Their controllers also need to know how far they can trust that estimate. Algorized and ZHAW Zurich University of Applied Sciences Institute of Signal Processing and Wireless Communications ISC have launched a two-year research program to study both questions. The collaboration is funded by InnoSuisse.

The program, “Real-Time Human Perception via Edge-AI Wireless Sensor Fusion for Collaborative Robotics”, runs from September 2026 for two years. It builds on earlier research by Algorized and ISC on ultra-wideband (UWB) radar.

The program aims to combine raw wireless and optical signals in one fusion layer between a robot’s sensors and its controller. Researchers aim to weight each input by confidence and produce a calibrated estimate of a person’s position and predicted path.

Algorized processes raw data with one foundation model to detect human presence and classify whether it is a human or an object. The program tests whether combining raw inputs in sensor fusion, before each sensor makes its own decision, creates a holistic layer for the human-aware machines.

Each sensor type adds different information. UWB radar and Wi-Fi sensing can help detect a person behind a shelf or a machine. Millimeter-wave radar holds its lock through dust, steam, glare and darkness. RGB and time-of-flight cameras add spatial and semantic detail. The program studies how these inputs work together.

The research has four goals. The first three are to sense people in approach to the robot, tell living from non-living objects, and track and predict each person’s path. The fourth is to send the robot controller a graded instruction: continue, slow down, or stop. The inference target is under 100 milliseconds on standard industrial edge hardware. Algorized’s planned safety functions cover presence detection, localization and tracking.

A model of this kind needs its own training data. That data must come from real facilities with people moving through them. Researchers who understand the physics must interpret it. The goal is a core model that transfers across sensor types, vendors and sites without retraining for each deployment.

“Machines enter the physical world,” said Natalya Lopareva, CEO and Founder of Algorized. “For robots to coexist with humans, they need to understand the people around them. We are exploring every sensor and every layer of compute to make shared spaces safe. That takes research, and we are doing it together with the ISC at the ZHAW School of Engineering.”

“The program brings ISC sensing research into real industrial sites. Researchers will combine radar, Wi-Fi, and optical signals to distinguish approaching people from other objects and then estimate the person’s position and movement. The program investigates how the reliability of this estimation can be measured and how to predict where a person will go next,” said Marc Kuhn, Deputy Head of ISC at the ZHAW School of Engineering.

About Algorized

Algorized builds the edge-native nervous system for Physical AI. Its foundation model senses human presence, vital signs, and intent through occlusion – delivering real-time human-aware perception from standard wireless sensors, where cameras and light-based systems go blind. Backed by the Amazon Industrial Innovation Fund and rooted in four years of Swiss sensing research, Algorized partners with silicon manufacturers and industrial OEMs across robotics, automotive, and smart spaces. Learn more at www.algorized.com.

About the ZHAW School of Engineering

The School of Engineering is one of eight schools of the ZHAW Zurich University of Applied Sciences. With 14 institutes and centres, the ZHAW School of Engineering is one of Switzerland’s leading institutions for technical education and research. It provides high-quality degree programmes and continuing education and develops innovative solutions for industry, focusing on the areas of energy, mobility, information and health.

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SOURCE Algorized

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Yoodli Named 2026 Inc. Power Partner for Helping Enterprise Teams Build Skills That Show Up on the Job

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Recognition follows a year in which Yoodli customers including Google and Intuit earned 11 Brandon Hall Group awards for programs built on Yoodli

SEATTLE, Oct. 20, 2026 /PRNewswire/ — Yoodli, the AI Platform for Human Skills, has been named a winner of the 2026 Inc. Power Partner Awards, which recognize the B2B companies that entrepreneurs and businesses rely on to grow.

Inc. selected this year’s honorees for a proven track record of helping companies build and scale, across areas from hiring and compliance to technology, fundraising, and marketing.

“Business owners have no shortage of tools at their disposal, and B2B companies need to make clear why their products and services are worth the investment,” says Bonny Ghosh, editorial director at Inc. “The companies on this year’s Power Partners list have done just that. They don’t just have customers, they have superfans and evangelists. Across industries like marketing, financial services, and technology, they’ve proved their dedication to helping fellow business owners grow and succeed.”

“The best validation we get isn’t an award for Yoodli. It’s watching our customers’ teams get recognized for the work they do with us,” said Varun Puri, co-founder and CEO of Yoodli. “Organizations are under real pressure to get their people ready for an AI-first world, and practice alone doesn’t get them there. Our job is to help skills carry over into the moments that matter, and to show leaders the results.”

“Being a Power Partner means our customers’ results are the scoreboard,” said Mike Rich, head of partnerships at Yoodli. “We work alongside training firms, consultancies, and enablement leaders who build skills programs for their own clients. Together we create immersive training experiences and demonstrate measurable outcomes.”

“Every training company says their program works. The hard part is proving it,” said Jeff Bittner, senior director of digital and AI at Braintrust and a member of Yoodli’s Customer Advisory Board. “In two and a half years with Yoodli, we’ve mastered it. Every seller starts with a baseline and a personal record to beat, allowing us to coach the cause instead of the symptom. We’ve seen enterprise clients with hundreds of users adopt at 96%, and others increase their connection level from 22% to 67% in three months. That’s what a real partner does. We make our clients better by providing tools that move the needle.”

Yoodli was recognized for the measurable outcomes its customers have achieved in 2026. Google’s GBOedu Commercial Enablement team won seven awards at the 2026 Brandon Hall Group HCM Excellence Awards (three gold, three silver, one bronze) for scaling AI roleplay practice across its sellers with Yoodli. Intuit’s Global Sales Enablement team earned four Brandon Hall Group awards for programs powered by Yoodli, including gold in Learning & Development Strategy and in Leadership Development.

The company also reached several milestones this year. Yoodli was named to TIME’s Best Inventions of 2026 in the Education category and to LinkedIn’s 2026 Top Startups list for Seattle. It grew past 100 employees and moved into a new headquarters at Pier 70 on the Seattle waterfront. Organizations including Google, Snowflake, Databricks, and Intuit use Yoodli to coach, train, and measure skills across their workforce.

For more information on Inc.’s Power Partner Awards or to view the complete list of honorees, visit inc.com/power-partner-awards.

About Yoodli

Yoodli is the AI Platform for Human Skills. Through AI coaching, learning journey creation, roleplays, personas, and measurement, Yoodli helps people get measurably better in their careers and helps organizations upskill their workforce for an AI-first world. Proven in high-stakes revenue teams and built for company-wide scale, Yoodli is used by organizations including Google, Snowflake, Databricks, and Intuit. Learn more at yoodli.ai.

Media Contact:
Sage Quiamno
press@yoodli.ai
+1 (808) 232-1321

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RBC tops JD Power Retail Banking Satisfaction Study among Big Five banks for third consecutive year

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TORONTO, Oct. 20, 2026 /CNW/ — RBC is pleased to be named Highest in Customer Satisfaction Among the Big Five Retail Banks by JD Power for the third year in a row, and the fourth time in five years. The recognition stems from the JD Power 2026 Canada Retail Banking Satisfaction StudySM, which gathers feedback from thousands of retail banking customers nationwide.

“The trust clients place in us reveals itself in moments big and small, and this study captures that,” said Erica Nielsen, Group Head, Personal Banking, RBC. “We are grateful to our clients who continue to choose RBC, and this award belongs to the employees who show up for them with care and expertise.”

RBC earned an Overall Satisfaction score of 619, finishing nine points ahead of the Big Five average of 610 and holding the number one position among the Big Five across all seven dimensions measured in the study, including Digital Channels and Problem Resolution. The bank’s eight-point improvement outpaced the industry average gain. RBC stands out most in Level of Trust, Account Offerings meeting my needs, and Allowing me to bank how and when I want, where it holds significant leads over the average.

The study also points to continued momentum, with RBC building on its strengths in Digital Channels and Account Offerings, along with improvements in Online Chat, New Account Opening, Product/Fees, and Convenience.

“We keep the client at the centre of everything we do, and that focus is reflected in the areas where we are leading. Whether someone is opening an account online, chatting with us through our digital channels, or sitting down with an advisor, we look across every part of RBC to make sure each experience is built around them. I want to thank our teams across the country for making that commitment felt every day.”

The JD Power 2026 Canada Retail Banking Satisfaction Study drew on responses from 14,038 retail banking customers surveyed in two waves between January and February and between July and August 2026.

About RBC
Royal Bank of Canada is a global financial institution with a purpose-driven, principles-led approach to delivering leading performance. Our success comes from the 105,000+ employees who leverage their imaginations and insights to bring our vision, values and strategy to life so we can help our clients thrive and communities prosper. As Canada’s biggest bank and one of the largest in the world, based on market capitalization, we have a diversified business model with a focus on innovation and providing exceptional experiences to our more than 19 million clients in Canada, the U.S. and 27 other countries. Learn more at rbc.com.‎

We are proud to support a broad range of community initiatives through donations, community investments and employee volunteer activities. See how at rbc.com/peopleandplanet.

For more information, please contact:
Habiba Ahmad, RBC Communications, 437-993-3245

SOURCE RBC Royal Bank

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