Category Archives: Technology

Integrated Power Services (IPS) Acquires Bold Renewables 

Blink-powered glasses could keep an eye on health

October 12, 2026

New smart glasses harvest mechanical energy from facial movements to power sensors

EVANSTON, Ill. — From blinking and smiling to jaw clenching and eyebrow raising, faces are constantly in motion — and generating tiny amounts of energy along the way.

Now, Northwestern University engineers are putting that energy to work.

In a new study, the team developed a wholly new type of smart glasses equipped with tiny sensors that harvest mechanical energy from facial movements and convert it into electrical power. Even a quick blink or an artery’s faint pulsing provides enough mechanical energy to activate the highly sensitive sensors.

To put their battery-free device to the test, researchers used the glasses to detect jaw clenching, teeth tapping, blinking and eyebrow raising. Not only did the glasses distinguish these movements from everyday activities like talking and eating, but it also recognized teeth tapping with 99% accuracy and jaw clenching with 96% accuracy. 

The advance could pave the way for common glasses to seamlessly monitor cardiovascular health, bruxism (inadvertent jaw clenching and teeth grinding), fatigue, eating behaviors and other activities throughout the day — without bulky batteries or regular charging.

The researchers will present this work, called GlassTENG, at 4 p.m. China Standard Time (4 a.m. EDT) on Thursday, Oct. 15 at UbiComp/ISWC 2026, a premier conference for ubiquitous, pervasive and wearable computing. “GlassTENG: Self-powered triboelectric nanogenerator based sensing of pulse, jaw and upper facial activity from everyday glasses,” is a part of the session “Eyewear Computing.” The paper is available in the Proceedings of the 2026 ACM International Symposium on Wearable Computers.

“The human face is a goldmine for health data, making everyday glasses the perfect wearable,” said Northwestern’s Nivedita Arora, who led the work. “Generally, wearables track health data, like heart rate, through the wrist. But people have to remember to wear those trackers and take them off to recharge. Our idea is based on the fact that half the population already wears glasses. We can turn those glasses into wearables without asking people to change their habits and behaviors.”

An expert in self-powered electronics, Arora is the Breed Chair Assistant Professor of Electrical and Computer Engineering and Computer Science at Northwestern’s McCormick School of Engineering, where she leads the Vasudhaiva Kutumbakam (VAK) Embodied Systems Lab. Raj Dave, Jovanis Prodanich and Yung-ching Lai — all master’s students in the VAK Embodied Systems Lab — are the study’s co-first authors.

A little static goes a long way

At the heart of the new glasses are three paper-thin devices called triboelectric nanogenerators (TENGs). Although the name sounds complicated, the phenomenon behind them is familiar: static electricity.

Anyone who has rubbed a balloon against their hair or pet a cat’s fur on a dry winter day has experienced the triboelectric effect. When two different materials come into contact and then separate, electrons can transfer from one material to the other, generating a brief electrical charge.

GlassTENG takes advantage of that same basic phenomenon. Each flexible sensor contains layers of materials that repeatedly press together and separate in response to facial movements. A blink, for example, pushes against one sensor. A clenched jaw activates another. Even the subtle pressure produced by blood pumping through an artery can push the sensors. 

“As the layers touch and separate, they generate a tiny voltage,” Arora said. “That means the very movement being measured supplies the mechanical energy needed to power its detection. In other words, a blink helps power the sensor that detects the blink.”

Three sensors, many signals

To capture as much information as possible, Arora and her team positioned three sensors at strategic locations around the glasses frame. One sits at the bridge of the nose, near the angular artery and muscles surrounding the eyes. There, it can pick up the pulse as well as blinking and eyebrow movements. Another sensor sits near the temple, where it detects the superficial temporal artery along with jaw movements. A third sensor sits closer to the ear, where it detects movements from chewing and clenching.

Together, the three sensors give the glasses different vantage points from which to “feel” the face’s movements. And the sensors are sensitive to a range of forces. An arterial pulse — the lightest force the researchers tested — generated electrical signals of about 50 to 100 millivolts. Blinks and eyebrow raises produced roughly 200 to 500 millivolts. Stronger jaw movements, including chewing and clenching, generated signals as high as 1.5 volts.

“These differences give various facial activities their own recognizable electrical signatures,” Arora said.

While wearing GlassTENG, 20 participants performed six activities: blinking, raising their eyebrows, clenching their teeth, tapping their teeth, eating and talking. The research team then used machine-learning algorithms to analyze patterns in the electrical signals and determine which activity each participant performed. Across the six activities, the system achieved 93.8% accuracy.

“One of the most exciting possibilities is using this technology to turn unconscious behaviors into opportunities for meaningful behavior,” said study coauthor Nabil Alshurafa, an associate professor of preventive medicine, computer science and electrical and computer engineering at Northwestern, where he has appointments at Northwestern University Feinberg School of Medicine and McCormick. “Imagine glasses that recognize when someone is clenching their jaw and gently prompt them to relax or detect eating and encourage mindful awareness of their habits. By combining cardiovascular and behavioral sensing within the same ultra-low-power platform, GlassTENG opens the door to studying how physiological states and everyday behaviors interact and to delivering personalized interventions at the moments they may be most helpful.”

Ultra-low power, big benefits

Beyond what GlassTENG can do, another big advantage is what it doesn’t need: electricity. Many existing wearables continuously draw power. Constant power consumption leads to bigger energy demands that require bigger batteries, which add weight and bulk. Batteries also need regular recharging, which presents another barrier to truly continuous health monitoring.

GlassTENG’s three sensors consume just 4.1 microwatts of power combined — orders of magnitude less power than many conventional sensing technologies. From there, it uses Bluetooth to stream data straight to a smartphone or tablet.

“In the long-term, we want to do on-device computation,” Arora said. “If it detected a physiological event, it could have on-device intelligence in a battery-free way that could give immediate feedback. For example, if it detected jaw clenching, it could immediately alert the user to relax their jaw. I think it’s only a matter of time until the glasses we wear everyday can monitor our health.”

“The future isn’t just wearables that tell us what we did,” Alshurafa said, “but wearables that help us recognize and change what we’re doing in the moment.”

The study, “GlassTENG: Self-powered triboelectric nanogenerator based sensing of pulse, jaw and upper facial activity from everyday glasses,” was partially supported by the Ansys, Inc.

Vodia Announces Vodia Wallboards

BOSTON: October 13, 2026 – Vodia Networks, Inc., a provider of unified cloud communications solutions to enterprises, contact centers, and managed service providers (MSPs), is pleased to announce Vodia Wallboards, a self-hosted platform for monitoring and displaying Vodia call queue activity.

When call queues build, teams need to see them immediately, not later on in a report. Vodia Wallboards gives supervisors, contact centers, service providers, and operations teams a live view of the queue activity that matters most; it connects one or more Vodia PBX servers, enables monitoring for the relevant tenants, and creates wallboards for a supervisor’s browser, an operations dashboard, or a dedicated TV display.

See Queue Activity as It Changes

Vodia Wallboards provides a live view of calls waiting, ringing, and active; agent availability and status; inbound and outbound call counts; service levels; abandoned calls; and average speed of answer. This is visibility built specifically around call queues. Teams can identify rising wait times, unavailable agents, or deteriorating service levels, all while there’s still time to respond.

Each widget can follow a wallboard’s queue filter or focus on a specific queue, allowing teams to move from a broad operational view to a more detailed queue view when necessary.

Ready-made layouts

Vodia Wallboards includes eight ready-made layouts for common operational needs, including NOC overviews, single-queue views, executive summaries, agent monitoring, multi-queue displays, and service-level trends. The drag-and-drop wallboard builder and library of 15 widget types make it easy to adapt a layout to the information each audience needs to see, including large KPI displays for a shared operations screen, detailed agent views for supervisors, or a focused wallboard for a particular queue. Widgets include queue-status cards, agent grids, active-call lists, service-level gauges, trend charts, alert feeds, and more.

Monitor queues across PBX systems

For service providers and larger deployments, one Vodia Wallboards instance can connect to multiple Vodia PBX servers. This makes it possible to display call queue activity from different customers, offices, or regions in one place, while keeping each tenant’s information appropriately scoped. Wallboards can also be branded per tenant with a logo and accent color, helping service providers present a consistent, customer-specific view.

Turn queue data into clear decisions

Vodia Wallboards helps teams move beyond raw metrics. AI Summary widgets can provide a plain-language assessment of current queue health using OpenAI, Claude, Gemini, or Ollama. Threshold alerts can notify teams by email when conditions such as waiting calls or abandonment rate exceed defined limits. For dedicated displays, TV Mode publishes a wallboard as a login-free URL. The display link provides read-only access to wallboard data without exposing settings or user management.

Secure, self-hosted deployment

Vodia Wallboards is self-hosted, giving organizations control over where the platform runs and how it is managed. Access can be scoped by PBX system, tenant, or individual queue. Administrator accounts use multi-factor authentication, and stored PBX credentials are encrypted at rest using AES-256-GCM. Vodia Wallboards requires Vodia PBX v69 or later with API access enabled.

Documentation is provided on the Vodia documentation website. Vodia reps can be reached via the Vodia website or via telephone at +1 (617) 861-3490.

From Soil to Smart Farming: How Technology Is Reshaping India’s Agricultural Economy

Artificial intelligence, agricultural drones, digital marketplaces and smart irrigation are opening new possibilities for Indian agriculture, helping farmers improve productivity, manage risks and discover fresh sources of income.

India’s agricultural landscape is undergoing a quiet but significant transformation. Across the country’s villages and farming communities, technology is creating new ways to grow crops, manage resources and connect agricultural produce with markets. While traditional knowledge and farmers’ experience remain indispensable, digital tools are increasingly helping them make more informed decisions in a changing economic and climatic environment.

The shift is about more than modernising cultivation. It is about strengthening the entire agricultural value chain—from choosing the right crop and managing water to reducing post-harvest losses, accessing buyers and creating new rural businesses.

Agriculture and allied activities contribute around 18 per cent of India’s Gross Value Added (GVA), making the sector an important pillar of the economy. Foodgrain production reached an estimated 357.73 million tonnes in the 2024–25 crop year, highlighting India’s substantial production capacity and the importance of farming to national food security.

Yet higher production does not automatically translate into higher farm incomes. Unpredictable weather, rising input costs, limited storage and fluctuating market prices continue to challenge farmers. Technology offers practical ways to address some of these pressures while opening new opportunities for rural entrepreneurship and economic growth.

Artificial Intelligence Brings Timely Advice to Farmers

For a farmer, a timely decision can make a considerable difference to the season’s outcome. Knowing when to sow, how to respond to a pest outbreak or when to irrigate can influence both crop quality and cultivation costs.

Artificial intelligence and mobile-based advisory services are making agricultural information more accessible. Farmers can increasingly use digital platforms to obtain weather updates, crop management guidance, pest alerts and information about government support programmes.

Government initiatives such as the Kisan e-Mitra chatbot help farmers access information about agricultural schemes in regional languages. Bharat-VISTAAR, an AI-based agricultural advisory initiative, represents a further step towards bringing agricultural information and digital guidance together in a more accessible format.

The potential is considerable. When reliable agricultural data is combined with local weather information, crop requirements and expert knowledge, digital tools can help farmers make more informed decisions.

However, the success of AI in agriculture will depend on the quality of its recommendations. Advice must reflect local growing conditions and remain understandable to farmers with different levels of digital literacy. Technology works best when it complements farmers’ experience and the guidance of agricultural experts.

Agricultural Drones Turn Innovation into Rural Opportunity

Agricultural drones are introducing greater speed and precision to selected farm operations. They can help monitor crops, identify areas requiring attention and apply agricultural inputs where appropriate.

For farmers, these services can reduce the time and labour required for certain tasks. Their effectiveness, however, depends on crop conditions, equipment quality, operator training and safe application practices.

The financial model is equally important. Many small and marginal farmers may find it difficult to purchase and maintain drones individually. Shared services and affordable rental models can make the technology more accessible without placing a heavy financial burden on individual cultivators.

This creates opportunities for rural entrepreneurs, trained drone operators and women’s self-help groups to provide agricultural services and earn additional income. In this way, a technology designed to support cultivation can also become a source of employment and enterprise in rural communities.

Digital Markets Help Farmers Look Beyond the Local Mandi

Growing a good crop is only half the challenge; selling it at a fair price is equally important.

Farmers have traditionally depended on local mandis and established trading networks. These markets remain essential, but limited price information, transport costs and restricted buyer access can sometimes reduce farmers’ bargaining power.

Digital platforms such as the electronic National Agriculture Market (e-NAM) aim to broaden market access by connecting agricultural markets through online trading and information services.

By March 2026, e-NAM had integrated 1,656 mandis across 23 states and four Union Territories, with more than 1.80 crore farmers registered, according to reported government figures.

For farmers, digital market access can make it easier to compare prices and explore trading opportunities. For agricultural businesses, it can improve connections with producers and support more organised procurement.

Nevertheless, digital access must be backed by physical infrastructure. Transparent grading, accurate weighing, efficient transportation, suitable storage and timely payments remain critical to ensuring that farmers can turn market information into better commercial outcomes.

Smart Irrigation Makes Every Drop Count

Water availability is becoming an increasingly important consideration for agricultural planning. In areas affected by irregular rainfall or water stress, efficient irrigation can help farmers manage one of their most valuable resources.

Drip irrigation delivers water close to plant roots, while soil-moisture sensors help assess when irrigation may be needed. Automated systems can support more precise water management, reducing unnecessary use when properly designed and maintained.

When combined with weather forecasts and crop-specific guidance, these technologies can help farmers plan irrigation more effectively. The benefits vary according to soil conditions, crop type, local climate and the cost of installation.

Making efficient irrigation affordable for smaller farms will be important to expanding adoption. Access to financing, technical support and suitable maintenance services can help farmers use these systems more effectively over time.

Agriculture Is Creating a New Generation of Rural Businesses

Technology’s influence extends well beyond the field. India’s agricultural economy offers opportunities in machinery rentals, drone services, soil testing, food processing, cold storage, packaging and logistics.

Young entrepreneurs can build businesses that solve practical problems for farmers, from arranging equipment during peak cultivation periods to helping transport produce to processing units and buyers.

Food processing is particularly important because it can increase the value of agricultural produce before it reaches consumers. Better storage and cold-chain facilities can also help preserve perishable crops and reduce losses after harvest.

Farmer-producer organisations and cooperatives can strengthen these opportunities by helping cultivators purchase inputs collectively, share equipment, negotiate with buyers and access services that might otherwise be too expensive for individual farmers.

This broader approach creates the possibility of a more diversified rural economy—one in which livelihoods depend not only on growing crops but also on the businesses and services that support agriculture.

Closing the Gap Between Technology and the Small Farmer

Despite its promise, agricultural technology is not equally accessible everywhere. Small landholdings, limited internet connectivity, affordability concerns and gaps in digital literacy can slow adoption.

Farmers also need confidence that the tools they use are reliable and relevant to their circumstances. AI recommendations require dependable data, drones need trained operators, and digital marketplaces work best when supported by efficient transport and storage.

Addressing these challenges will require collaboration among government institutions, agricultural universities, technology companies, financial institutions and farmer organisations. Regional-language services, practical demonstrations, affordable equipment and accessible financing can help ensure that technological progress reaches small and marginal farmers as well as larger agricultural enterprises.

The objective should not be to replace traditional knowledge with machines, but to combine generations of farming experience with tools that improve decision-making and reduce avoidable risks.

The Future of Farming Lies in Better Returns for Farmers

India’s agricultural transformation will ultimately be judged by its impact on farmers’ livelihoods. Higher production matters, but so do lower costs, reduced crop losses, stronger bargaining power and access to dependable markets.

Artificial intelligence can improve access to information, drones can support efficient farm operations, digital platforms can connect producers with buyers, and smart irrigation can help conserve water. Meanwhile, rural enterprises in processing, storage and logistics can create additional employment and help retain more economic value within farming communities.

The next stage of progress will depend on making these solutions affordable, practical and widely accessible. Technology must serve the farmer’s needs, rather than becoming another expense that is difficult to recover.

The real promise of smart farming is not simply producing more food—it is building an agricultural economy in which farmers make better decisions, rural businesses thrive and a greater share of the value created by every harvest reaches the people who grow it.

Partnership to Scale AI and Multi-Cloud Workloads Across Singapore, Australia and New Zealand

A partnership that enables centralized, observable, and scalable environments for AI and multi-cloud workloads across Singapore, Australia, and New Zealand 

• Orange Business APAC and Aviatrix join forces in the Asia-Pac region to expand the partnership beyond Europe by combining strengths to help enterprises connect, secure, and manage their cloud infrastructure.

• This partnership leverages the connectivity, managed services, and cybersecurity expertise of Orange Business, and the cloud-native networking and security capabilities of Aviatrix. 

Organizations within Asia Pacific namely Singapore, Australia, and New Zealand will soon benefit from the worldwide capabilities offered by Orange Business and Aviatrix following their collaboration in this region. This latest partnership sees the two companies delivering a joint value proposition that combines Orange Business’s global connectivity and managed services with Aviatrix’s cloud-native networking and security expertise, beginning with the three key markets above.  

The expansion further builds on the global partnership that Orange Business and Aviatrix announced earlier this year. Additionally, Aviatrix will also grant Orange Business first right of refusal for opportunities in China, Hong Kong, India, Malaysia, South Korea, and Taiwan. 

Orange Business is a global operator, digital solutions integrator and platform player and the enterprise division of the Orange Group, with more than 20 years of presence across Asia-Pacific. Aviatrix, founded in 2014, delivers the only secure networking architecture built specifically for the cloud, providing centralized security and visibility across every cloud environment from a single platform. 

In an increasingly AI-based landscape where organizations are drawn to innovate faster, scale more efficiently, and deliver new services to customers, AI workloads also expand the attack surface and increase the complexity of cloud networking. AI environments span multiple clouds, regions, containers, Kubernetes clusters, and AI agents. According to a study on 2026 global threat landscape (source: CrowdStrike 2026 Global Threat Report: Evasive Adversary Wields AI), a reported 82% of detections are now malware-free—adversaries use valid credentials and trusted identity flows to move through authorized pathways, bypassing traditional detection entirely. This is why organizations need secure, high-performance connectivity with consistent visibility, centralized governance, and policy enforcement that holds on whether a compromise has been detected.  

Orange Business and Aviatrix address this challenge by providing a secure, scalable foundation for multi-cloud and AI workloads:

• Securing distributed AI environments: Aviatrix secures the network traffic connecting AI data sources, models, and applications across multi-cloud environments. Built-in containment ensures that security policies hold as to whether a breach has been detected, with high-performance encryption at up to 100 Gbps cloud-to-cloud and up to 1 Tbps data-center-to-cloud.

• Simplifying multi-cloud networking: A centralized, software-defined platform for managing, monitoring, and securing cloud connectivity, thereby replacing fragmented, cloud-by-cloud approaches.

• Visibility and enforcement for AI workloads: See how AI applications communicate across clouds, identify risks, and enforce policy on AI-to-AI and AI-to-data connections—without adding architectural complexity.  

Additionally, the partnership seeks to benefit organizations in different areas. Firstly, organizations can expect to reduce the total cost of ownership by optimizing network usage and avoiding unnecessary costs. Real-time visibility into cloud resources and consumption supports more accurate financial planning through efficient traffic management and Aviatrix’s cloud-native capabilities that support real-time visibility into cloud resources and consumption.  

Secondly, the joint proposition offers secure connectivity within the cloud and to the cloud. This is achieved through the Orange Business Evolution Platform – a proven, high-performance network infrastructure that can integrate AI workloads with existing offices, data centers, SD-WAN, and security environments. Also, key to note: the Orange Evolution Platform infrastructure hosts Aviatrix in over 40 locations globally that allows Aviatrix to be deployed without additional hardware complexity, and with the flexible advantage of monthly billing option that supports different commercial and operating models, thereby easing an organization’s process in connecting and managing their cloud environments.  

Finally, the partnership also extends traffic visibility and policy enforcement across connected SD-WAN, LAN, and cloud networking environments as a standard managed service – helping organizations see what their workloads are doing, enforce consistent policy, and improve resilience across multi-cloud connectivity. Orange Business and Aviatrix support the full cloud networking lifecycle – from design and deployment through operation and optimization. Organizations can thus choose from self-service, co-managed, or fully managed operating models based on their business needs.

Haiqu Unveils AgenticOS, a System of Agents Solving Some of Physics’ Toughest Problems

R&D Teams Can Build Complete Quantum Projects from the Idea to the Experiment Itself, Verifying AI Results Every Step of the Way; Available Now

NEW YORK — October 9, 2026 — Existing AI models have advanced to the point that they can contribute to real science, but they have their limits. An AI agent can produce convincing math and working code, but it might alter the underlying science while doing so, leaving researchers with results that look right but aren’t. Today, Haiqu is addressing that by unveiling AgenticOS, giving quantum researchers a team of AI agents that are built for scientific exploration, and designed to catch mistakes before they happen.

In complex scientific calculations, general-purpose AI agents can make small changes no one asked for, like shifting a molecular geometry or slipping in an unapproved approximation. The calculation then answers a different question, or returns a result that is simply incorrect. With the Haiqu AgenticOS, researchers can now design an entire quantum project — from the initial question to an experiment that’s ready for quantum hardware — and assign multiple teams of AI agents to validate and confirm the research findings every step of the way. The team overseeing the experiment can then inspect each assumption and conclusion to determine how to proceed.

“Turning a promising research idea into a real experiment demands years of specialized, hands-on expertise in highly technical methods, all of which takes time and resources,” said Mykola Maksymenko, co-founder and CTO of Haiqu. “AgenticOS takes on much of that labor-intensive work, freeing up researchers so they can spend their time working on the right questions, reaching results much faster without sacrificing accuracy.”

AgenticOS builds on the Haiqu platform announced in May. A researcher starts with a question, and the system assigns teams of specialized AI agents to review the literature, work through first-principles mathematical derivations, assess quantum feasibility and check the results. Haiqu’s AgenticOS shows its investigative process as a map of connected research tasks. Results are checked against classical baselines, tests, critic agents and human review, with formal verification. Scientists decide what gets locked, which tasks run on their own and where a human signs off.

During a recent chemistry study accepted at the NeurIPS 2026 workshop in Paris focused on AI for Scientific Discovery, Haiqu demonstrated the need for its platform by giving leading AI agents the same research brief, with and without AgenticOS. On their own, four of 10 agent runs ignored an explicit setup instruction, resulting in widely different answers. Using Haiqu’s AgenticOS, the same models held to the approved protocol from start to finish and produced a simulated quantum result within approximately 3.4% of the exact diagonalization reference.

“Being able to organize, ground and check an AI agent’s work matters as much for scientific research as improving the models themselves,” said Richard Givhan, co-founder and CEO of Haiqu. “Every lab will soon have access to the same powerful AI. The ones that pull ahead will be the ones that can trust what it produces, and that’s exactly what we built AgenticOS to do.”

AgenticOS has already been deployed to work on one of the hardest problems in physics. The Hubbard model describes electrons hopping across a grid and repelling each other when they meet. Haiqu targeted a 2D “doped, frustrated with diagonal hopping” version of the model, which is used to study high-temperature superconductivity in copper-based materials known as cuprates. Starting from a scientist’s idea, AgenticOS built the experiment on a 3-by-3 grid, small enough to cross-check against an exact classical solution, and ran it on an IBM quantum computer. It reduced circuit depth by 75% and proposed a calibration that brought the hardware result in line with what an error-free quantum computer would produce using the same method. That shows a way to apply the same approach to larger simulations that classical computers can’t solve exactly. 

Haiqu’s platform serves enterprise teams testing individual use cases, university research labs and scientists from other fields looking to take their first step into quantum computing. Agents can help users determine if a specific quantum approach is worth pursuing, while mapping out algorithm options, identifying the assumptions and identifying the classical benchmarks needed to judge the result.

When a research plan is ready, AgenticOS hands it straight to Haiqu’s quantum software stack. The Haiqu SDK squeezes more out of today’s noisy hardware with data loading, circuit compression and error mitigation. The Haiqu Runtime then manages execution on simulators and quantum processors from IBM, IonQ, IQM, AWS and others, cutting time and cost by up to 1,000x. The same platform that helps a researcher frame the question can take the answer all the way to a quantum computer.

Availability

AgenticOS is included with the Haiqu operating system, and is available now to enterprise R&D teams upon request. Companies can request access and book a demo now.

Academic researchers can apply for free access to the Haiqu platform, including AgenticOS, through the company’s Academic Program. Participating labs get the Haiqu SDK. They can also apply for AWS credits to cover classical and quantum computing workloads.

Airrived Named a Cool Vendor in the 2026 Gartner® Coolest Vendor Innovations in Agentic AI Security

DUBLIN, Calif.–(BUSINESS WIRE)–Airrived, the company behind an enterprise Agentic OS designed to make every business user an AI expert, has been named a Cool Vendor in the Gartner Coolest Vendor Innovations in Agentic AI Security report published on October 2, 2026.

Tetris debuts in North American cars at NY Comic Con 2026 with VW, AirConsole

 Tetris® makes its North American in-car debut at New York Comic Con with AirConsole and Volkswagen

• New York Comic Con visitors can step inside the new 2027 Volkswagen Atlas and experience AirConsole in-car gaming firsthand at the Pop Insider booth, number 1935
• Fans can play multiplayer Tetris® on the vehicle’s infotainment display, using their smartphones as controllers
• The all-new 2027 Atlas becomes part of the game as its ambient lighting reacts to Tetris gameplay in real time
• The activation runs October 8–11 at the Javits Center, giving more than 250,000 expected NYCC visitors the opportunity to experience AirConsole

New York, US – October 8, 2026; AirConsole, the in-car gaming platform by N-Dream, is teaming up with Volkswagen of America and The Tetris Company to showcase their new collaboration at New York Comic Con 2026. At the center of the activation is the all-new 2027 Volkswagen Atlas hosting a Tetris® experience, built around AirConsole’s signature light integration. Giving fans a hands-on look at how AirConsole transforms everyday drives into shared gaming experiences.

“Bringing AirConsole and Tetris to the new Volkswagen Atlas at the New York Comic Con is a perfect match.” said Anthony Cliquot, CEO of N-Dream, the company behind AirConsole. “The event brings together exactly the kind of fans who will love what AirConsole does. It’s a place where people come to celebrate the stories and games that shaped them, while always looking forward to what’s next. Having a timeless and globally recognized title like Tetris here makes it the perfect setting to showcase how we’re bringing entertainment to the car—an environment where people are spending more and more of their time.”

“New York Comic Con brings together communities built around shared passions and experiences,” said Rachael Zaluzec, Chief Marketing Officer, Volkswagen of America. “That makes it the perfect place to showcase how AirConsole can help turn time spent in a vehicle into something social, engaging, and fun. We’re excited to give fans a chance to experience Tetris in the Atlas and see firsthand how Volkswagen is creating new ways for people to connect.”

The showcase builds on AirConsole’s recent expansion with Volkswagen, which introduced AirConsole in-vehicle gaming to select model year 2027 Volkswagen vehicles in the U.S. — including the Atlas, Atlas Cross Sport, Tiguan, Golf GTI, Golf R, and ID. Buzz — making Volkswagen the first volume automotive brand in the U.S. to offer the platform.

TETRIS MULTIPLAYER AND IMMERSIVE

With Tetris, one of the most recognizable video games of all time comes to the car. Players can enjoy the timeless puzzle gameplay across multiple modes with up to 4 players and experience the action with immersive vehicle integration when parked.

Game features include:

• Sprint – Race to clear 40 lines as quickly as possible, either solo or against other players, and compete for the best time.
• Marathon – Enjoy the classic Tetris experience and chase the highest score, now available for both solo and multiplayer play.
• Battle – Go head-to-head with other players, clearing lines to put pressure on your opponents and gain the upper hand.
• Online Battle – Compete against other Tetris car players from around the world or create a private room to battle your friends.
• Immersive ambient lighting – As players clear lines, the vehicle’s ambient lighting responds in real time — syncing to the color of the cleared line for an arcade-like experience that extends beyond the infotainment screen and into the cabin itself.

“Tetris is one of the most recognized and iconic video game brands in the world, and this is the latest step in how it keeps evolving alongside new players and new technology,” said Maya Rogers, CEO of The Tetris Company. “Bringing Tetris into Volkswagen vehicles with AirConsole turns the Atlas into a multiplayer arcade for fans to enjoy. We can’t wait for fans at New York Comic Con to try it for themselves.”

HOW IT WORKS

AirConsole is included in Volkswagen’s In-Vehicle Premium plan, a connected services package enabled by an active myVW+ subscription. Three months of In-Vehicle Premium is included with the purchase of select new 2027 models. Here’s how new owners can start playing:

1. Make sure the vehicle has been enrolled in the myVW app and it has an active In-Vehicle Premium plan.

2. Once enrolled, the AirConsole app should be visible in the infotainment system’s app menu. To launch the app, tap the AirConsole icon. (vehicle must be parked, some models may require the parking brake to be engaged).

3. Users will then follow the on-screen prompts and scan QR code with their smartphone to connect it as a controller.

4. Once connected, they can use their smartphone to choose a game and start playing.

This intuitive experience makes AirConsole the easiest way to enjoy quick, social games inside the car—whether it’s with passengers, family, or solo during a charging break.

Scality launches AI Inference Factory to bring enterprise AI on-premises

SAN FRANCISCO, October 8, 2026 – Scality, a global leader in data infrastructure software for AI storage at scale, today announced the availability of Scality AI Inference Factory, an open-code software stack for deploying and operating AI inference on enterprise-owned infrastructure. The solution gives enterprises, government agencies and neo-cloud providers a supported alternative to cloud-based AI services, without having to assemble, integrate and maintain the entire software stack themselves.

As AI moves from experimentation into production, organizations are looking for more predictable costs, greater control over model lifecycles and increased data sovereignty. For most organizations, the answer will be hybrid, with the most critical AI processes running on-premises. Running inference locally can address these requirements while keeping sensitive data within infrastructure that organizations own and operate.

Scality AI Inference Factory brings together validated open-weight models, a disaggregated inference-serving layer, a control plane for authentication, metering, routing and scheduling, and Scality AI Data Infrastructure (ADI), which uses policy-governed autonomous operations to manage massive datasets across the AI lifecycle. Scality validates, ships and maintains the integrated stack.

“With AI moving into mission-critical production environments, organizations need greater control over where inference runs, how their models are managed and what happens to their data,” said Jérôme Lecat, CEO at Scality. “For 15 years, Scality has built data infrastructure that thousands of customers around the globe rely on to operate 24/7. AI Inference Factory brings that experience to on-premises AI, giving organizations the reliability and sovereignty they need to run critical AI workloads on their own terms.”

Cloud AI challenges drive interest in on-premises inference 

Enterprises scaling AI in production are confronting challenges with the cloud-based inference model. With per-token pricing, the more useful an AI workflow becomes, the more it costs, producing bills that are difficult to forecast and impossible to cap. Model versions and quantization can change at the provider’s discretion, affecting the workflows built on them. Organizations with sensitive or regulated data face sovereignty concerns over where their prompts, documents and proprietary code are processed, under which jurisdiction, and who can restrict access to them.

Scality AI Inference Factory is designed for organizations that want to run critical AI workloads on infrastructure they control while retaining flexibility across models, hardware and software. The stack supports specialized chatbots, AI-assisted software development, agentic applications and other inference-intensive workloads.

Scality AI Inference Factory combines:

• Validated open-weight models maintained as part of the supported stack;
• Disaggregated inference serving that separates prefill from decode so each can scale independently;
• A control plane that authenticates and meters requests, routes them to the appropriate GPUs holding the relevant context and schedules workloads against SLA targets; and
• Scality ADI, which provides high-performance object storage for models, enterprise data and inference state.

Scality validates and maintains the complete stack as a supported solution, helping organizations keep pace with rapidly changing models, serving technologies and security requirements without having to integrate and maintain the individual components themselves.

“As AI adoption expands and AI agents become more prevalent, organizations are evaluating which IT environments are best suited to run inference. On-premises deployments are coming into focus for a variety of reasons, including cost optimization, data security and privacy, and regulatory requirements. IDC research shows that running inference on-premises is a credible option for a growing set of enterprise and public sector workloads, provided the infrastructure can hold and serve model state efficiently at scale. Scality is among the vendors addressing that requirement across the inference and storage layers.” — Nataliya Yezhkova, Vice President, Storage and Data Management, Enterprise Infrastructure, IDC

Scality ADI extends AI inference beyond GPU memory constraints

Scality ADI serves as the shared storage layer for AI Inference Factory, extending key-value (KV) cache beyond limited GPU high-bandwidth memory (HBM). This allows inference infrastructure to preserve and retrieve model context instead of requiring GPUs to recompute it, improving GPU utilization and reducing inference costs.

This is particularly important for reasoning models and agentic workloads, where KV cache can quickly exceed available GPU memory. Scality ADI provides a shared, multi-petabyte cache that GPUs read at latency the same order of magnitude as GPU memory, allowing them to retrieve existing context and remain focused on inference.

Scality testing demonstrated that ADI can reduce GPU consumption while maintaining the same level of performance:

• 1.9-second load time for Gemma-3 27B, almost 10x faster than local NVMe, with the model streamed in parallel across the cluster over RDMA;
• 166 ms warm time-to-first-token on a 14K-token context restore from ADI, only 83 ms behind HBM;
• 14x faster KV cache retrieval than recomputation on a 14K-token context and up to 72x faster on a 439K-token context;
• A KV cache more than 80x larger than a single GPU’s memory, keeping up to 1,000 concurrent sessions resumable without recomputation;
• No measurable impact on token generation, as context is restored before the first token; and
• 97% of network line rate for data transfer between GPUs and storage.

The architecture separates prefill from decode, with ADI acting as the shared cache between GPU pools. This allows available decode GPUs to access existing context without tying it to a specific GPU server. Separating prefill from decode has documented gains: DistServe (OSDI 2024) measured up to 7.4 times more requests served within the same latency targets. Adding a shared KV cache pool on top, Moonshot AI’s Mooncake reported 75 percent more requests on Kimi’s production traffic.

As Giorgio Regni, Scality CTO, puts it: “The KV cache on Scality ADI is fast enough to sit in the serving path. Restoring a context from ADI is the same order of magnitude as GPU memory, and 14 times faster than recomputing it, with the GPUs staying busy the whole time. Storage is no longer the reason to keep the KV cache inside the GPU server.”

Regni continues: “That opens the door to disaggregated serving. One pool of GPUs handles prefill, processing the prompt and writing the KV cache to ADI. A second pool handles decode, reading the cache back and generating tokens. With Scality ADI as the shared cache, any decode GPU can pick up any context, and there is essentially no size limit. Prefill no longer interrupts decode, and both pools run at full load.”

For a technical deep dive into the AI Inference Factory architecture and test results, visit Scality’s companion blog.

Open architecture provides flexibility across models, frameworks and hardware

Scality AI Inference Factory is designed to preserve customer choice across the AI infrastructure stack. It is compatible with open-source harnesses and agentic frameworks such as OpenCode, Hermes, Goose, LangGraph and Pydantic AI, and runs validated open-weight models such as Mistral, Gemma, gpt-oss, Qwen, Kimi, GLM, and DeepSeek. The software deploys on standard servers from Dell, HPE, Lenovo and Supermicro.

Every software component Scality ships is delivered as open code, enabling customers to inspect how inference state is stored and moved, and to submit contributions for Scality review. For organizations running sensitive, regulated or sovereign AI workloads, this provides transparency into the software handling their models and data rather than requiring them to rely on a closed external service. 

Scality ADI integrates with standard AI stacks and deploys at multi-petabyte scale on NVMe, with RDMA access to HDD for virtually unlimited KV cache capacity. A single namespace automatically tiers data across TLC, HDD and, optionally, tape, allowing organizations to align storage performance and economics with different stages of the AI data lifecycle.

Availability

Scality AI Inference Factory is available now as a software license or as a fully managed service. Scality is demonstrating the solution and its reference architecture at Scality Day on October 8 in Paris. To learn more, visit the Scality AI Inference Factory web page and detailed companion blog.

TÜV SÜD on the New Management System Standard for Sustainability Goals

Munich. ISO/UNDP 53001 was published at the end of September. It provides  organizations with a new international framework for integrating the UN Sustainable  Development Goals into their management structures. Developed by the International  Organization for Standardization (ISO) and the United Nations Development Program  (UNDP), the ISO/UNDP 53001 standard is the world’s first management system standard  of its kind. It provides a structured approach for integrating the UN Sustainable  Development Goals (SDGs) into corporate governance, strategy, and operational  processes. TÜV SÜD provides information on the newly published standard. 

Sustainability has become an integral part of corporate strategy in many companies. However,  consistently embedding environmental, social, and economic goals into existing management  structures remains a challenge. ISO/UNDP 53001 addresses this need through a management  system approach that helps companies define responsibilities, set goals, and monitor progress  as part of a continuous improvement process. Since the standard follows the harmonized  structure used in all ISO management system standards, it can be integrated into existing  quality, environmental, or energy management systems. 

“Sustainability can only be effective if it is integrated into a company’s daily decision-making  and management processes,” says Sara Brandimarti, Global Head of Sustainability – Business  Assurance Division at TÜV SÜD. “ISO 53001 provides a structured framework for this. It helps  organizations systematically consider sustainability aspects and derive long-term changes  from them that go beyond individual projects or reporting requirements.” 

Response to Rising Stakeholder Expectations 

The expectations of customers, investors, and regulatory authorities regarding sustainability  continue to rise. Transparent and systematic management of sustainability issues is becoming  increasingly important, particularly for companies operating in complex international supply  chains. With ISO/UNDP 53001 as a certifiable standard, an independent certification body  such as TÜV SÜD can now assess whether an organization’s SDG management system meets the standard’s requirements. Organizations that take this approach demonstrate that  they manage their sustainability-related activities within a structured and transparent  management framework.