For institutional investors, this represents a fundamental pivot. The last decade was defined by “growth at all costs.” The next decade will be defined by “resilience at any price.” Deep tech—specifically the convergence of space infrastructure, advanced energy, and industrial robotics—is no longer a speculative frontier. It is the defensive backbone of the modern state and the offensive engine of future industrial productivity.

Space: The invisible infrastructure

Space technology has graduated from scientific curiosity to critical utility. It is a mistake to view space as vertical; it is a horizontal enabler, an “invisible infrastructure” akin to the internet or GPS, upon which terrestrial industries now depend. We are seeing a shift from launch-focused investments to orbital utility.

The most valuable opportunities lie in “Earth-first” applications. Sovereign nations and multinational corporations are demanding independent satellite constellations for secure communications, climate monitoring, and resource management. We are moving toward a real-time, sensor-rich planetary interface. Investors who recognise space assets as the ultimate high-ground real estate—delivering proprietary data and connectivity to agriculture, logistics, and defence—will capture returns that are uncorrelated with traditional consumer market cycles.

Energy security as an asset class

Energy access is now a critical issue of national security. The fragility of global energy grids has exposed a desperate need for decentralised, high-density power sources. This drives our conviction in next-generation nuclear capabilities, such as micro-reactors and radioisotope power systems, alongside breakthroughs in hydrogen and fusion.

The winners in this sector will not just be those who generate power, but those who solve the “storage and mobility” paradox. We are investing in technologies that decouple energy availability from geography. Whether powering a remote data centre for AI training or a lunar outpost, the physics are the same. By backing companies that miniaturise and ruggedise energy systems, we are effectively buying options on industrial continuity in an unstable world.

The era of physical intelligence

While Large Language Models (LLMs) have dominated headlines, the true productivity revolution awaits the arrival of “Physical AI”—intelligence embodied in robotics. The industrial base is suffering from a chronic labour shortage that demographic trends will only worsen. Software cannot change the physical world; robots can.

We are witnessing the transition from rigid automation to adaptive autonomy. Robots are acquiring the ability to perceive, reason, and act in unstructured environments. This is the bridge between the digital brain and the physical hand. For investors, the alpha lies in “vertical robotics”—machines purpose-built for specific, high-value workflows in manufacturing, mining, and construction. This is not about replacing humans; it is about re-industrialising economies with higher margins and anti-fragility.

Deep tech is for those who understand compounding and harbour those who seek generational impact, challenging the investor mindset. It requires an investor mindset that balances the rigours of physics with the realities of finance. As we look toward 2026, the question for Limited Partners is not “is it too risky?” but rather “can we afford to be excluded from the infrastructure that will run the world?” At Beyond Earth Ventures, we believe the future belongs to the builders.

The post Deep tech: The new global backbone appeared first on International Finance.

In the words of Daniel Sokolovsky, the co-founder and CEO of Warp, the start-up is always looking for ways to make shipping more efficient for its customers, which include large businesses like Walmart, Gopuff, and HelloFresh. As artificial intelligence (AI) has become the new norm in the 21st-century world economy, the company now believes there are opportunities through which supply chains can be further automated.

Sokolovsky told TechCrunch that while Warp can’t automate long-haul trucking or short-range delivery aspects of the supply chain, it focuses on what it can change: the workflows inside its warehouses.

Engineering Logistics At Scale

Warp started its journey by installing cameras in its test warehouse in Los Angeles, using computer vision to convert that data into a virtual warehouse for experimentation.

“We effectively made a digital twin, or simulation environment, for our LA facility. \[We] basically started just throwing stuff at the wall. Honestly, a lot of it was, ‘What happens if we do this? What happens if we do that? What happens if we do that other thing?’” Sokolovsky said.

One of the start-up’s first ideas was to train humanoid robots to use traditional pallet jacks, but it didn’t work. Then, Warp started to find success using off-the-shelf robots with additional tech retrofitted onto them.

“We’ve taken really, really complicated logistics problems, divided them into a lot of easily digestible, system-understood, and system-fed components. We are now using, whether it’s AI in the form of voice, text, email, phone calls, or robotics, \[to ensure] that we’re unloading, storing, and reloading freight. We actually think that we can continue this and really reach our goals as quickly as possible, without hiring more people,” Sokolovsky added.

Warp’s co-founder and CRO (Chief Revenue Officer), Troy Lester, said that these robots will help support Warp’s underlying warehouse partners (other than its Los Angeles test facility). The start-up doesn’t outright own the warehouses in its network, a move that helps reduce labour costs.

“They’re complaining to us about staffing issues all the time. The labour that’s doing the work in these facilities isn’t happy either. So, I think there is an opportunity to empower those businesses to have these robotic kits that would not only help make our network better but also improve their business with other companies,” Lester said.

Warp has raised USD 10 million in its latest Series A round, co-led by Up.Partners and Blue Bear Capital. The start-up is testing several different versions of the robots, with the goal of deploying them by the end of 2025.

The start-up has optimised everything from hyperlocal parcel movement to national freight networks. In doing so, Warp uncovered a massive flaw in the LTL (Less Than Truckload) system, finding that it’s not suitable for modern supply chains, as the mechanism is slow, rigid, and most importantly, blind to the precision today’s shippers demand. To address this, Warp has brought its digital hub-and-spoke network into play, aiming to transform the middle mile and move freight the way it should.

Meet The Solutions

Warp’s LTL solutions allow users to share trucks and cross-dock space, cutting costs without compromising the quality. The start-up consolidates freight with others, maximising efficiency and minimising clients’ transportation costs—all while keeping deliveries fast, reliable, and sustainable.

While conventional LTL methods have drawbacks like class-based pricing, reweighs, rebills, and hidden fees, which make invoices unpredictable and drive up costs, there are also issues such as inefficient transit with multiple touchpoints, long dwell times, and inconsistent routing that lead to delays and missed delivery windows.

Additionally, limited tracking and inconsistent scan data leave shippers in the dark about shipment status. Excessive handling at terminals often increases the risk of damaged or lost freight, while limited vehicle types, lack of temperature-controlled solutions, and inflexible scheduling often fail to meet diverse shipping needs.

Addressing these drawbacks, Warp’s LTL solution optimises smaller shipments into fuller loads, cutting costs and eliminating LTL inefficiencies, in addition to offering per-pallet rates that eliminate class-based pricing, reweighs, or rebills. The solution also provides tailored options for scheduled deliveries, on-demand pickups, and temperature-controlled freight to fit customers’ needs.

Clients can also choose from a range of vehicles, including cargo vans, box trucks with lift gates, drop trailers, and 53-foot temperature-controlled trucks for any load size. Lastly, live updates, scan-in/scan-out tracking, and POD confirmation ensure complete transparency from pickup to delivery.

Launched less than a year ago with 14 core lanes, the LTL network now spans over 500 digitally connected lanes, representing a 3,400%+ increase, as the company aggressively scales its alternative to traditional terminal-based freight.

Next is “Inbound Consolidation,” under which Warp consolidates its clients’ purchase orders and optimises appointment scheduling at the start-up’s digital cross-dock. The integrated process then delivers freight efficiently to the final destination. This solution boosts load efficiency by merging shipments, reducing empty space, while achieving measurable cost savings and speed.

Businesses can optimise their freight flow with consolidated deliveries, cutting administrative tasks while boosting efficiency and transit speed, in addition to cutting transportation costs by uniting shipments into one efficient delivery, lowering freight expenses and fuel consumption. Consolidated shipments reduce hand-offs and errors, ensuring dependable schedules and consistent deliveries.

Through “Pool Distribution,” Warp harnesses shared routes to consolidate similar shipments, reducing costs and transit times while providing real-time visibility and streamlining operations for efficient middle-mile logistics. The start-up’s digital routes optimise delivery speed and precision across all stops, while consolidating shipments via a digital network to reduce costs and improve delivery speed.

Smarter routing also results in fewer trucks on the road, reducing emissions and enhancing efficiency. Finally, smart shipment tracking and data-driven delivery scheduling make the whole solution cutting-edge.

Efficient, Reliable Delivery For Bulky Items

Warp has engineered a home delivery solution for oversized freight that avoids the usual pain points. Since products like saunas, furniture, and treadmills don’t fit into parcel or standard LTL systems, the start-up uses appropriately sized box trucks and cargo vans, routed directly from cross-docks to customers’ homes. This solution is also streamlined, ensuring efficient deliveries with fewer touchpoints and, most importantly, no inflated charges.

By bypassing congested sorting hubs, Warp eliminates bottlenecks and reduces transit times for parcel shipments. Combining real-time tracking, optimised routing, and a versatile fleet, Warp offers a seamless, efficient zone-skipping service for faster and more reliable deliveries.

Also, Warp reportedly helped an apparel retailer save over 27% by using the same trucks and cross-docks for inbound and outbound shipments, cutting costs and ensuring on-time deliveries. Cross-docking and zone-skipping also reduced delivery times by 20%, keeping shelves stocked.

The post Start-up of the Week: Warp streamlines supply chains with AI appeared first on International Finance.

Huang believes that beyond artificial intelligence itself, robotics will be Nvidia’s biggest growth market, with autonomous vehicles as the first major commercial application.

International Finance will examine how Nvidia is leveraging its AI prowess to drive breakthroughs in autonomous driving and robotics, and what it means for the company’s future and the tech industry at large.

From GPU king to AI powerhouse

Nvidia has a very underdog story. It was established in 1993 and was almost set to be named GeForce. The name Nvidia comes from the Latin word ‘invidia’, which means envy (or green with envy). In early 2006, they put everything they had into CUDA (Compute Unified Device Architecture), which began paving the way for AI’s rise. It’s important to note that there would be no ChatGPT without Nvidia.

The company was a household name in the early 2000s, being the top supplier of graphics cards that were necessary to play high-quality video games. Their top competition back then was AMD, which in the 90s had considered acquiring Nvidia. Today, Nvidia dwarfs AMD, as they are single-handedly pioneering AI, robotics, self-driving cars, chip production, and even building supercomputers. The company is considered a major source of inspiration for Silicon Valley enthusiasts. Notably, Nvidia CEO Jensen Huang was once rejected by Apple, yet he went on to become a titan in the industry and has been referred to as the “Steve Jobs of AI Hardware.”

However, the visionary cofounder of Nvidia knows the semiconductor industry can be cyclical, with data centre investment coming in “booms and busts.” To secure Nvidia’s place in the tech stratosphere long term, Huang has been scouting the next big market beyond conventional “Big Tech” pursuits. At Computex 2024, he declared that two “high-volume” products will dominate robotics in the future: self-driving cars first, and eventually humanoid robots.

These technologies are converging thanks to advances in machine learning, and both require human-like perception, split-second decision-making, and immense computing power, precisely what Nvidia specialises in.

In Huang’s words, “Every single car company will have to be autonomous, or you’re not going to be a car company,” a bold prediction underscoring his belief that autonomy is the future of transportation.

Accelerating the self-driving car revolution

Nvidia has methodically embedded itself at every level of the self-driving technology stack. Huang often describes a three-part approach: one computer to train AI models, another to run simulations, and a third inside the vehicle for real-time driving. By providing the chips and software for all three stages, Nvidia aims to be the go-to enabler of autonomous vehicles rather than a consumer-facing automaker.

“Nvidia has strategically embedded itself in all three key steps that could make every car a self-driving car,” notes Business Insider.

While companies like Waymo and Tesla build robotaxis and personal electric vehicles, Nvidia positions itself as the behind-the-scenes supplier powering those efforts.

Nvidia Drive, the company’s end-to-end autonomous driving platform, exemplifies this strategy. It includes powerful automotive systems-on-chip (SoCs), like the current Drive Orin and next-generation Drive Thor, paired with the Drive OS software and toolkits for perception and mapping. At CES 2025, Toyota (the world’s largest automaker) announced it will integrate Nvidia’s Drive AGX Orin “supercomputer” and Drive OS into its upcoming vehicles to enable advanced driver-assistance and automated driving features.

This was a major win for Nvidia, as Toyota has been collaborating with the company since 2017 on AI for self-driving and even uses Nvidia’s cloud GPUs to train its models. The Toyota deal underscores Nvidia’s “cloud-to-car” strategy: first supplying chips for AI training in the data centre, and now supplying chips and software for intelligence inside the car.

Other automakers are also lining up. Mercedes-Benz, China’s BYD, Volvo, Hyundai, Lucid Motors, and many electric vehicle startups have adopted Nvidia’s Orin-based platforms for their next-gen cars. In early 2025, General Motors struck a broad partnership with Nvidia to use its GPUs and AI software across passenger vehicles, robotaxis, and even factory automation.

GM will equip future cars with Nvidia’s “AI brain,” including Drive SoCs running the safety-certified Drive OS (based on Nvidia’s latest Blackwell GPU architecture), to enable hands-free driving and autonomy. Notably, GM is also leveraging Nvidia’s Omniverse 3D simulation platform to create virtual assembly lines and train its industrial robots, aiming to boost manufacturing efficiency with AI. This includes the company’s Drive AGX system-on-a-chip (SoC), similar to Tesla’s Full Self-Driving chip or Intel’s Mobileye EyeQ.

The SoC runs the “safety-certified” Drive OS operating system, built on the Blackwell GPU architecture, and capable of delivering 1,000 trillion operations per second (TOPS) of high-performance compute.

This partnership came on the heels of GM’s decision to wind down its Cruise robotaxi unit after safety incidents, signalling that GM now prefers to pivot toward consumer vehicles with advanced autonomy, and it’s tapping Nvidia to help make that happen.

Winning over these automotive giants could translate into huge business for Nvidia. The company projects its automotive division will reach a $5 billion annual run rate by FY2025, a fivefold increase from 2023. That’s still modest next to Nvidia’s booming data centre revenue, but the growth trajectory is clear. Nvidia’s automotive VP Ali Kani remarked that the car business is “still in its infancy,” contributing Nvidia chips to under 1% of cars on the road today, but he calls it a “trillion-dollar opportunity” long term.

Industry analysts have taken note: McKinsey estimates assisted and autonomous driving could be a $400 billion market by 2035. And after a few gloomy years when automakers dialled back self-driving investments (Ford and VW shuttered Argo AI in 2022, GM pulled back on Cruise in 2024), Jensen Huang’s confident CES showcase was seen as a “shot in the arm” for the sector.

“Nvidia has reversed that and just gave autonomous driving an absolute shot in the arm,” said one automotive consultant, noting that hearing a tech leader evangelise self-driving renewed investors’ interest in the space.

Crucially, Nvidia’s advantage is its full-stack approach. Few companies can provide the training-side infrastructure (massive AI supercomputers to train driving models) and the in-car chips to execute those models on the road.

Tesla, for instance, trains its Autopilot AI on Nvidia GPUs in the data centre, even though it builds custom chips for its cars.

This “cloud + edge” synergy makes Nvidia a natural partner for any firm aiming to deploy autonomous vehicles at scale. It’s no surprise Huang says Nvidia is “absolutely positioning [itself] as the leader for autonomous technologies, period.”

Indeed, from passenger cars and long-haul trucks to robotaxis, Nvidia’s silicon and software are increasingly becoming the standard toolkit for autonomy. As Huang put it at CES 2025, self-driving cars are no longer perpetually “coming” — “they’re already here,” citing the commercial progress of Waymo and Tesla as proof.

Building an ecosystem of robots

If self-driving cars are essentially “robots on wheels,” Nvidia’s ambitions don’t stop at transportation. The company is simultaneously assembling an expansive ecosystem for robotics and automation in other domains. Huang believes the world is on the cusp of an era of “physical AI,” intelligent machines performing tasks in the real world, and he wants Nvidia to provide the brains of those robots. At Computex, flanked by virtual humanoid figures, Huang proclaimed, “Robotics is here. Physical AI is here. This is not science fiction.”

So, what is Nvidia’s game plan for robotics? In short, to offer a full technology stack akin to its automotive approach. Simulation is one pillar: the company’s Omniverse platform creates rich virtual worlds where robots can be trained and tested safely. Built atop Omniverse is Isaac, described as a “gym” for robots, which lets developers put virtual robots through their paces to practice tasks or generate synthetic training data.

Then comes the edge hardware: Nvidia’s Jetson line of AI chips (with a forthcoming flagship called Jetson Thor) provides the onboard compute for robots to perceive and act in real time. Finally, tying it together are AI models and software frameworks that give robots their smarts.

In 2023, Nvidia unveiled Project “GR00T,” a “moonshot” effort to develop a foundation AI model for humanoid robots. In 2025, this bore fruit in the form of Isaac GR00T N1, billed as the world’s first open-source generalist model for robot intelligence.

GR00T N1 is essentially a robot “brain” that has been pretrained on vast data, not just text or images, but demonstrations of physical actions. It uses a dual-system architecture inspired by human cognition: a “slow-thinking” module that reasons and plans, and a “fast-thinking” module that executes reflexive actions.

This mimics psychologist Daniel Kahneman’s concept of thinking fast and slow. In practice, GR00T N1 can observe its environment (through sensors and cameras), interpret instructions, plan a sequence of actions, and then control a robot’s limbs to carry out complex tasks. Nvidia pretrained it on both real-world human motion data and millions of synthetic scenarios generated in simulation.

Importantly, GR00T N1 is customisable. Developers can fine-tune it with additional data so a robot learns specialised skills. Huang declared that “the age of generalist robotics is here” as he opened up GR00T N1 to the world’s robot makers.

Complementing GR00T is another key piece called Nvidia Cosmos. Unveiled at CES 2025, Cosmos is a family of foundational models focused on modelling the physical world.

Whereas language models ingest books and websites, Cosmos was trained on 20 million hours of video of humans and objects in motion. It generates highly realistic images, simulations, and 3D scenarios, for example, showing boxes falling off a shelf in a warehouse, which can be used to teach robots what to expect and how to respond in the real world.

“It’s not about generating creative content, but teaching the AI to understand the physical world,” Huang explained.

Companies are already using Cosmos: humanoid robot startups like Agility Robotics and Figure, and self-driving car developers like Waabi and Wayve, are leveraging it to accelerate their training and simulation. In essence, Cosmos gives robots common sense about physics and environments, while GR00T gives them the decision-making and motor skills, together aiming to dramatically lower the barrier to robotics development.

Nvidia’s Jensen Huang envisions a future where advanced AI chips and software power fleets of autonomous vehicles and humanoid robots, a vision already taking shape through partnerships with automakers, electronics manufacturers, and even entertainment companies.

Nvidia is backing up these platforms with real-world pilot projects to showcase what’s possible. One headline-grabbing example is its collaboration with Foxconn, the world’s largest electronics manufacturer.

In 2025, Nvidia and Foxconn announced plans for a “robotic factory” in Houston that will use humanoid robots to assemble Nvidia’s own next-gen AI servers.

This would be the first time Nvidia products are built with the help of humanoid machines, and one of the first such deployments in any electronics factory. Foxconn has been co-developing humanoid robots with Nvidia’s hardware and software, including one bipedal model and one wheeled model, and training them for tasks like picking up components, inserting cables, and performing assembly.

The goal is to have a small number of these robots operational by Q1 2026 when the Houston plant begins production of Nvidia’s “GB300” AI servers. If successful, this could herald a new era of AI-driven manufacturing.

Observers note it as a prestige project for both firms: Nvidia would solidify its position not only as a chip and server leader but as a platform provider for robotics, while Foxconn would demonstrate high-tech manufacturing innovation on American soil.

Nvidia’s robotics push goes beyond factories. The company is moving into service and entertainment robots, even magic-infused Disney creations.

In March 2025, it emerged that Nvidia, Disney Research, and Google DeepMind are teaming up on a project codenamed “Newton” to create a new generation of interactive robotic characters.

Newton is essentially an open-source physics engine that will help Disney’s robots learn complex movements with precision. Disney Imagineering’s vision is to bring more lifelike robots to its theme parks, for example, free-roaming droids like the Star Wars-inspired “BDX” robots that were previewed during Huang’s keynote.

“This collaboration will allow us to create a new generation of robotic characters that are more expressive and engaging than ever before,” said Disney Imagineering’s senior R&D VP.

In fact, Disney’s first batch of AI-powered BDX droids has already been play-tested on a cruise ship and will soon appear in Walt Disney World and other parks.

For Nvidia, this alliance is a testament to the scope of its robotics prowess, reaching into animatronics and arts, away from factory floors. It also highlights a familiar refrain: Nvidia is not making the robots or cars themselves; rather, it provides the enabler technology that allows industry leaders (be they Toyota, Foxconn, or Disney) to fulfil their AI-fueled dreams.

Towards a deep tech superpower

All these moves point to Nvidia’s evolution from a pure “Big Tech” company into something broader, a deep technology platform spanning hardware, software, and services for the AI-driven future.

“We stopped thinking of ourselves as a chip company long ago,” Jensen Huang recently remarked.

He prefers to describe Nvidia as an “AI infrastructure” and “computing platform” provider, one that now delivers cloud services, simulation software, and development toolkits in addition to silicon.

By weaving itself into the fabric of emerging industries like autonomous vehicles, robotics, and even defence (Nvidia is a partner in a European project led by Nokia to use drones and robots for critical infrastructure protection), Nvidia is staking a claim as a leader in “physical AI,” the application of artificial intelligence in the physical world.

Huang predicts that in the not-so-distant future, there will be “billions of robots, hundreds of millions of autonomous vehicles, and hundreds of thousands of robotic factories” all powered by Nvidia technology. It’s an audacious vision, but one the company is investing heavily to realise.

Financially, these sectors are still ramping up. Nvidia only recently began reporting its automotive and robotics revenues together, and they accounted for roughly $567 million last quarter (about 1% of total sales), albeit growing 72% year-on-year. The company’s present profitability still relies on data centre AI chips, but investors are keenly watching these nascent divisions.

For tech-savvy investors, Nvidia’s foray into self-driving cars and robotics represents the opening of new multi-billion (even trillion) dollar TAMs (Total Addressable Markets) over the coming decade. It pits Nvidia not against the usual FAANG companies, but against (or alongside) players in automotive, manufacturing, healthcare, and aerospace, industries hungry for AI solutions.

The company’s strategy of partnering with incumbents (rather than competing directly) could yield a sprawling customer base without massive capex on its part. As one set of analysts wrote, Nvidia’s strengths in robotics and digital twins could “scale into massive businesses themselves,” potentially driving decades of growth.

Naturally, challenges abound. Robotics, especially humanoid robots, remain harder than web or mobile tech; they involve complex mechanics, safety concerns, and huge data requirements to function reliably in unstructured environments. Sceptics point out that despite Nvidia’s impressive tools, fully autonomous robots are still in the early stages and demand significant R&D.

Even Huang acknowledges that growing the robotics market “isn’t just a matter of time” or inevitability. It will require continued advances in artificial intelligence algorithms, sensors, and perhaps most importantly, cost reduction, to see robots proliferate beyond pilot projects.

Nvidia’s strategy of open-sourcing models like GR00T N1 and collaborating widely is meant to accelerate this progress by seeding an ecosystem (much as OpenAI frameworks spurred the machine learning boom).

Huang believes that by reducing barriers and providing substantial computing power, Nvidia can do for robotics what it accomplished for AI software: make it accessible enough for an explosion of innovation.

Nvidia has gone from selling graphics chips to becoming the linchpin of modern AI, and now it’s charging into autonomous machines on our roads and in our factories. This pivot could fundamentally reshape Nvidia’s identity, no longer simply a supplier to “big tech” companies, but a superpower in deep tech, commanding influence in the next generation of industries built on AI, from smart cars to smart robots.

Huang’s remarks at a recent shareholder meeting put it best: “AI and robotics are the two largest opportunities, representing a multitrillion-dollar growth opportunity.”

If Nvidia succeeds, it won’t just be leading in AI computing; it will be everywhere that advanced computing meets the real world.

In an era when “everything that moves” is poised to become autonomous, Nvidia appears determined to supply the engines of that revolution, thereby laying the basis of its transformation as a force dominating deep tech innovation.

The post Nvidia’s vision: Chips for a robotic world appeared first on International Finance.

Speaking on February 12 at the Private Sector Forum in Riyadh, Amit Midha, CEO of Alat, a company supported by the Public Investment Fund (PIF), emphasised that these machines will transform the production and assembly processes both in the Kingdom and around the world.

Amit Midha disclosed that this historic accomplishment was led by the strategic partnership agreement that Alat and SoftBank Group signed in February 2024 to establish a joint venture to produce industrial robots in Saudi Arabia.

By the end of this decade, the Kingdom hopes to become a global centre of innovation and technology, which is in line with its larger “Vision 2030” economic diversification objective.

Amit Midha said, “By May of this year, we will be exporting robots all over the world, and they will be built in Riyadh. We are investing in a fully automated manufacturing and engineering hub which is dedicated to producing cutting-edge industrial robots.”

“Imagine the robots that can programme themselves. Imagine the robots that have three times to five times the speed of a normal labourer. These robots can really revolutionise how, where and what can be manufactured,” he added.

Amit Midha claims that because these robots will be so affordable, they will “redefine” the conventional manufacturing industry.

“Some of the manufacturing centres developed in the last few decades will get reshaped because now the cost of robots and automation is going to be the same as hiring a person or an operator in a manufacturing facility,” he noted.

According to Amit Midha, Saudi Arabia will also export laptops and personal computers to foreign countries by the end of 2025 as a result of Alat’s USD 2 billion deal with Lenovo, a major Chinese tech company.

The post Saudi Arabia to export industrial robots by May 2025: Alat CEO Amit Midha appeared first on International Finance.

With offices in California and Switzerland, the venture, as of April 2024, has raised USD 25 million in venture-backed funding from investors such as Lakestar, Mosaic Ventures, Costanoa Ventures, and Tectonic Ventures, while having a rich clientele including General Electric (GE) Aviation, Quantum Systems, Impossible Aerospace, and the United States Department of Defence.

Unifying A Workforce Of Autonomous Robots

Auterion’s drone software is a different breed altogether, as it streamlines operations, elevates integration, and maximises automation for its clients, all on a single digital platform, while increasing safety, efficiency and sustainability with the operating system for autonomous robots.

Auterion’s cutting-edge operating system for autonomous computing is empowering a diverse range of autonomous robots to perform high-risk to mundane tasks, deliver goods, and aid in life-saving missions. Staying true to its operational versatility, the drone software start-up is powering a range of autonomous vehicles, including multirotors, fixed-wing, VTOLs, and ground vehicles.

A very good example of Auterion’s operational versatility is “Freefly Astro,” which is a connected drone for enterprise workflows. The product is a result of the collaboration between Auterion and its industry peer Freefly. Astro is a ruggedised drone, which enables enterprise workflows through standardised user interfaces, automated data transmission and real-time 4G data connectivity. The lightweight drone is perfect for jobs like image mapping, delivering goods, carrying out infrastructure inspections and search & rescue operations.

Using Auterion’s expertise, a drone manufacturer can accelerate its go-to-market strategy by utilising tried-and-tested software and hardware for faster integration and production scale-up, apart from expanding the capabilities of an enterprise’s robotics fleet. The client venture can also streamline its enterprise-ready solutions like end-to-end workflows, delivering data to the cloud, and connecting with existing apps, all through Auterion’s help.

The start-up is also providing state-of-the-art drone payload tools like MAVLink and the Pixhawk Payload Bus. For its enterprise-grade operations, Auterion also offers a variety of enterprise-grade payload options like a full camera, an app for advanced drone training and mission planning, cloud connection for live video streams, real-time monitoring and over-the-air firmware updates via onboard LTE.

What Are The Key Products?

Let’s start with AuterionOS, which is the only vendor-independent operating system that runs onboard a fleet of interconnected robots. The onboard software platform consists of a flight controller and an operating system running on the mission computer. AuterionOS allows robots to perform advanced operations by enabling specific autonomous actions, ensuring safe mission execution, establishing communication with other software and hardware, and providing LTE connectivity to transfer data in real-time to the user and the cloud.

AuterionOS also allows the installation of apps, enabling features that are relevant to the client enterprise’s purposes, in order to enhance the latter’s operational experience. A very good example here is AuterionOS powering the drone fleet of its industry peer DroneUp which operates in the delivery hubs of Walmart, the largest American retailer, to provide 4 million US households with last-mile delivery.

AuterionOS helps its users to operate a variety of vehicles and payloads with the same experience and workflow, while bringing elements like APIs into the play, to expand the range of drone cameras, radios and payloads. AuterionOS, while running on multiple drone models and supporting different payloads, also enables a unified workforce of autonomous robots with the world’s leading operating system for autonomous computing. Here Auterion Suite comes into the play.

With every mission, data gets automatically transferred into the cloud-based Auterion Suite to provide real-time information captured by the robot while it’s still operating, without any manual intervention. All flight logs get automatically uploaded for every vehicle and every pilot, and log data gets analysed and made available to download as compliance reports.

Auterion Suite enables holistic and scalable fleet management by providing updated information on the vehicle health status, predictive maintenance actions and over-the-air software updates. Robots send operational data and live video automatically to the Suite, while they are still in the air. The Suite also enables end-to-end automated workflow, from the vehicle operating in the field, over the air to the cloud and into third-party applications to process the captured data.

Auterion Suite is a foolproof management solution for a client enterprise’s robotics programme and missions, by handling software updates, tracking vehicles for predictive maintenance and monitoring components to flag operational issues.

Next is Auterion Mission Control, which is the app to plan and execute autonomous missions for any Auterion-powered vehicle. With simple controls and intuitive views, the tool allows a seamless robotics mission planning and execution experience for the client enterprise, especially in terms of standardising operations and reducing training time and resources, apart from scaling up missions and saving execution time by planning from remote locations.

Finally, we have Skynode X, a fully integrated autopilot and mission computer for drones operating under the Auterion software platform. Compared to other drone autopilots, Skynode X transforms robotic vehicles from mere mobile cameras into connected autonomous systems.

Solutions Galore

By collaborating with the start-up, ventures can manage their diverse fleet of robotic vehicles in a single asset management system that handles all software updates, tracks every drone for predictive maintenance, and monitors component health. The business can also download compliance reports per pilot or vehicle data from the cloud, prepare drone missions with pre-flight planning checklists and check real-time traffic information.

From Auterion, drone manufacturers get tried-and-tested software and hardware for faster integration and production scale-up, apart from the ability to offer enterprise-ready robotics fleet with elements like end-to-end workflows, cloud-powered data delivering mechanism, and integration with existing apps, built on industry standards MAVLink and the Pixhawk Payload Bus.

For app developers, AuterionOS comes with payload integrations and on-board applications, so that the professionals become part of an ecosystem that reaches more users and has a bigger impact.

An app developer can integrate his/her services and payloads to work across the whole fleet of Auterion-powered systems. It covers mechanisms like flight controllers, onboard components and the ground station/robotics data workflow in the cloud.

Auterion In News

The start-up, as of April 2024, along with its partners like Freefly, Deltaquad, Lucid Bots, Spleenlab and Sony, is providing its drone software solutions across all the major industry verticals, from cargo and energy to infrastructure and agriculture. Auterion, through its partnerships with drone manufacturers, software developers and payload makers, is shaping the future of both the UAV (Unmanned Aerial Vehicle) industry and the mainstream economy. The domain of robotics is heading towards the software-defined future and Auterion’s products give us a sneak peek of how things will look in the coming years.

In March 2024, Kraken Technology Group, a maritime technology leader specialising in the disruptive design and manufacturing of high-performance platforms, and Auterion announced a strategic partnership to exponentially develop autonomous capabilities in the high-performance littoral security boat sector. Auterion will develop and implement modular and low-cost autonomy software and UxV systems for Kraken’s K3 SCOUT and K4 MANTA uncrewed platforms.

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These technological advances have transformed traditional production processes, improving efficiency, precision and productivity while reducing costs and human error. By integrating automation and robotics into manufacturing, companies can streamline operations and supply chains, apart from improving quality control.

In this article, International Finance has examined the various roles that automation and robotics play in manufacturing and highlights their benefits, challenges, and future prospects.

Increased efficiency and productivity

Automation and robotics bring a significant increase in efficiency and productivity in the manufacturing sector. The machines do not tire and do not need breaks. This constant workflow minimizes downtime and optimizes production capacity. Robots can perform repetitive tasks accurately and quickly, resulting in higher output and overall improved efficiency.

Advanced robots can perform complex operations quickly, resulting in shorter turnaround times and higher performance. With automated systems handling tasks like assembly, packaging, and material handling smoothly, human professionals can focus on more important and value-added activities like research, development, and process improvement.

Automated systems can also perform inspections and tests with unprecedented accuracy and consistency. This eliminates the risk of human error and ensures products meet strict quality standards. Robots equipped with vision systems and sensors can identify defects and anomalies in real-time, preventing defective items from entering the market.

In addition, automation allows for continuous monitoring and data collection throughout the manufacturing process. This data can be analyzed to identify patterns, trends and opportunities for improvement. By resolving issues in a timely manner, manufacturers can improve product quality and reduce waste. The ability to maintain consistent quality standards has a significant impact on customer satisfaction and brand reputation.

Automation and robotics are also having a profound impact on the supply chain, streamlining logistics and inventory management. Automated systems can track and manage inventory levels in real-time, ensuring efficient replenishment. They can also facilitate seamless coordination between suppliers, manufacturers and distributors, reducing delays and minimizing disruptions in the supply chain.

In addition, automation enables just-in-time (JIT) manufacturing, where components and materials are delivered exactly when they are needed, eliminating the need for large inventories. This approach reduces inventory costs, minimizes the risk of inventory obsolescence, and improves overall operational efficiency. Robotics and automated guided vehicles (AGVs) can also be used in warehouse operations, enabling efficient material handling and order processing.

Automation and robotics contribute to the safety conditions in the manufacturing environment. By automating dangerous tasks and removing human workers from potentially dangerous situations, the risk of workplace accidents and injuries is significantly reduced. Robots are well suited for tasks that require heavy lifting, exposure to pollutants, or working in extreme temperatures.

No, automation doesn’t lead to unemployment

Contrary to popular belief, the integration of automation and robotics does not necessarily result in job losses. Rather, it often leads to a change in the nature of work. Automation allows human workers to take on more complex, creative, and higher-value roles, such as programming, maintaining, and monitoring automated systems. Collaborative robots, so-called cobots, work together with human workers, thus increasing productivity and efficiency while ensuring a safe working environment.

Automation and robotics also offer manufacturers the opportunity to adapt to changing market demands and production requirements. Traditional manufacturing facilities often involve fixed production lines, which limits flexibility and agility.

However, with automation, manufacturers can quickly reconfigure their processes to accommodate new products or variations without significant downtime.

Robots equipped with advanced programming and sensing capabilities can easily switch between tasks and product variants, enabling efficient changes to the production line. This flexibility allows manufacturers to respond more quickly to customer needs, reduce time to market, and remain competitive in dynamic industries.

Excelling in tasks with precision

Automation and robotics excel at tasks that require precise movement, measurement, and repeatability. Human workers can have inherent limitations in repetitive tasks, leading to variations in quality and consistency. However, robots can always perform tasks with sub-millimetre accuracy and maintain the same level of precision throughout the manufacturing process.

For example, in industries like electronics and automotive manufacturing, automated systems can precisely place components on circuit boards or assemble intricate parts with high accuracy, ensuring consistent quality and reducing the chance of errors.

Automation and robotics generate large amounts of data throughout the manufacturing process. This data can be used to uncover valuable insights and make data-driven decisions that optimize operations and drive continuous improvement. Manufacturers can use machine learning algorithms to analyze the collected data and identify patterns, anomalies and opportunities for improvement.

This approach enables manufacturers to make proactive decisions to increase productivity, reduce waste, and optimize resource allocation. Additionally, predictive maintenance is another valuable application of data analytics in manufacturing.

By monitoring equipment performance and analyzing data from sensors and automation systems, manufacturers can predict potential equipment failures and proactively plan maintenance activities, minimizing unplanned downtime and maximizing production availability.

Industrial robotics’ market trends

The global industrial robotics market size was $37,876.0 million in 2020 and is expected to reach $116,848.7 million by 2030 with a CAGR of 11.7% from 2021 to 2030. Meanwhile, labour costs across the United Kingdom are increasing by over 12% each year, leading to a shortage of labour. To overcome such problems, market players are investing in industrial robotics.

For example, in January 2022, the government invested in robotics to help the British people and economy deal with the inflationary crisis caused by labour shortages. In addition, it is estimated that US labour costs will increase by over 20%. This is therefore leading to an increase in industry initiatives to adopt robots to offset the labour costs and shortages that are driving the industrial robotics market. In addition, according to data from North America Factories and Industries, manufacturers and industrial users ordered more than 25,000 robots in 2021 compared to 2019.

High imports of robots are attributed to their use in the microelectronics industry, where small robots are used to pick and place small components. According to the trends, the global microelectronics industry has grown by more than 10% since 2010. Therefore, the growth in the microelectronics industry, which requires a larger number of robots, is expected to drive the industrial robot market.

Furthermore, during the COVID outbreak, the construction, manufacturing, hotel and tourism industries have been severely affected. Production activities have been discontinued or restricted. Construction and transportation activities as well as supply chains have been hampered on a global scale. This led to a decrease in the manufacture of industrial robots as well as their demand in the market, thereby slowing down the growth of the industrial robotics market.

Conversely, industries are gradually resuming their regular production and service operations. This is expected to bring industrial robotics companies back to full capacity, which will likely help the market recover by the end of 2024.

In January 2022, DHL Supply Chain invested $15 million in robotic solutions for the supply chain network in the warehouses. Robots contribute to a simple supply chain network by reducing long-term costs, increasing productivity, reducing errors and optimizing picking operations. According to industrial robotics market trends, it is estimated that the supply chain market will grow by over 100% by 2026. Hence, with the growing supply chain network, the increasing need for cost savings and efficiency gains is creating new market opportunities.

The industrial robotics market is segmented by type, industry, function and region. On the basis of type, the market is segmented into joint, card, SCARA, cylinder and other segments. By industry, it is categorized into Automotive, Electrical & Electronics, Chemical, Rubber & Plastics, Machinery, Food & Beverage, and others. By function, it is divided into soldering and welding, material handling, assembly and disassembly, painting and applying, milling, cutting and machining, and others.

Challenges and the future

While automation and robotics offer numerous benefits, their implementation presents certain challenges. The initial investment required to implement automated systems can be significant and discourage smaller manufacturers from adopting these technologies.

Additionally, integrating automation into existing manufacturing processes can require significant reconfiguration and staff training. However, advances in technology and falling costs are making automation more accessible and affordable. Smaller automation solutions are emerging, allowing manufacturers of all sizes to reap the benefits.

The future of automation and robotics in manufacturing holds enormous potential. As technology continues to advance, we can expect further integration of artificial intelligence (AI) and machine learning (ML), and robotics, leading to smarter and more autonomous systems. Collaborative robots or cobots are becoming more common, working hand in hand with human workers in a safe and collaborative environment. These cobots will have advanced sensor capabilities and intuitive interfaces that will enable seamless human-robot interaction and collaboration.

In addition, the concept of “lights-out manufacturing”, in which factories operate completely autonomously without human intervention, is gaining traction. Uninterrupted production can provide significant benefits in terms of cost reduction, production efficiency and 24/7 operation.

However, the implementation of “lights-out manufacturing” requires robust automation systems, AI-driven decision-making algorithms, and advanced security measures. Additionally, the rise of additive manufacturing, commonly known as 3D printing, is poised to revolutionize manufacturing processes. 3D printing enables rapid prototyping, customization and on-demand production, reducing lead times and eliminating complex supply chains. The integration of automation and robotics with 3D printing technologies can open up new possibilities for highly efficient and agile manufacturing.

The manufacturing industry has experienced a significant transformation thanks to automation and robotics. These advancements have improved efficiency, quality control, safety, and collaboration. Further developments will enhance their capabilities, enabling flexibility, data-driven decision-making, and the possibility of lights-out manufacturing. The decreasing costs also make automation more accessible to businesses of all sizes. Companies must adopt these technologies to stay competitive, streamline operations, boost productivity, and meet market demands.

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Created through the Joint Venture of Qatar Airways and Spain-based Ferrovial Group in 2013, , FMM has been managing and operating the facilities management services of Hamad International Airport (HIA) since the latter’s opening in 2014. Being one of the Qatar’s most prestigious landmarks, the award-winning Airport daily welcomes 100,000 passengers. . In 2022, it was voted the ‘World’s Best Airport’ for the second time in a row by Skytrax.

FMM provides facilities management activities at HIA such as daily cleaning of a combined surface of over 600,000 sqm, conducting more than 20,000 maintenance monthly tasks and ensuring the safety and smooth functioning of over 120 km of roads and tunnels throughout the Hamad International Airport network.

“We feel so grateful with what we have achieved so far, as our main client portfolio is based in key landmarks in Qatar,” said FMM CEO Eng. Irene Vidal, while adding, “We manage iconic cultural facilities for Qatar Museum or architectural gems as the Smart City Msheireb Downtown Doha”.

The HIA project turned out to be a crucial one for the FMM, in terms of building its capabilities, and developing a robust platform for staff recruitment, training, and Performance assessment. This ensured a continuous service improvement as FMM keeps on investing in developing their manpower and technology.

“Training is the pillar of our quality services,” stated Patrick Ishac, FMM HR Manager.

“All our staff go through a rigorous induction program followed by several refreshment and specialization sessions that count for approximately 15 days per year. We focus on our procedures, health and safety, as well as customer experience management as we want our operational staff to be able to handle challenges without the constant monitoring of their supervisors,” the official elaborated further.

FMM’s staff training took a turn in May 2022, as the company launched its virtual reality training platform. When asked about this tool, FMM CEO Eng. Irene Vidal responded, “This opportunity came as a solution to a problem that we identified, as our new joiners were idle while waiting for their documents and training to start working at HIA, we decided to create a tool to train them remotely but showing the actual rooms of the facility.”

Hence, the interface of this training platform reproduces our clients’ facilities, and the new recruits are able to see their upcoming working environment and we train them inside much before they obtain their working and access permit to the site. This platform enables us to significantly gain in efficiency as our valued employees join faster than before,” she added further.
Since its inception, FMM has put its emphasis on technology, as the company kept identifying innovations like robotics that could improve its operational performances.

FMM, as of 2023, uses the world’s most advanced cleaning robots in HIA and the state-of-the-art Aisha Bint Hamad Hospital.
According to Ms. Jessica Jung, Custodial Manager of FMM, “With more than 2,000 cleaners working round the clock in our projects, the addition of such high-performing robots naturally boosts our overall cleaning performance and safety records.”

These cleaning robots have the ability to work continuously for six hours, with only two hours of charging time. These devices can also clean all types of corners and edges, something which is considered impossible for conventional machines. Moreover, these robots’ environmental performance manages a monthly saving of over 4,000 liters of water, compared to standard cleaning.

FMM also uses robots in the other daily maintenance activities to gain in time, efficiency, and safety, like cleaning of conduits. The ducting inspection, which is a time intensive activity, due to scaffolding erection and safety risks, is now performed by these robots, which are equipped with cameras and mounted on remotely controlled mobile platforms. These devices inspect ducts in a faster and thorough manner than manual methods.

“The high-resolution images and videos we obtained with these robots were not achievable before with manual cleaning,” said Juanjo Garcia, Senior Manager at HIA, while adding, “We are moreover able to reach areas which were impossible to inspect manually. At the end, it reduces staff downtime and risks while generating savings and better performance.”

FMM employees have also been trained on how to interact, control, assist and maintain these robots. When asked about the next steps of FMM, Eng. Irene Vidal, FMM CEO declared, “We are convinced of the promising future of robotics in Facility Management, and therefore, the team supports the idea that such technology will inevitably get an ad value.”

“Our next major step will be to support the State of Qatar of their vision about sustainability, for this we have brought electric cars into our fleet of vehicles which unavoidably will become standard. Then our long-term goal is to focus in providing upscale FM services to our clients while reinforcing and developing partnership with equipment and material manufacturers to remain competitive and as a pioneer in this industry,” she said further.

The post FMM: Revolutionizing Qatar’s facility management game with robotics appeared first on International Finance.

Despite the incredible potential of ChatGPT, there are apprehensions about what this technology means for the future of human work and people’s livelihoods.

Automation Anxiety

More than ever, advances in both hard and soft forms of technology, such as robots and algorithms, are mimicking the same productivity displayed by human talents. For example, the banking sector is now deploying concepts like AI chatbots and virtual assistants, to cut down operational costs and increase their digital footprints.

The words “artificial intelligence” and “machine learning” allude to what is novel: technology is gaining and honing cognitive and sensory skills previously assumed to be exclusively human, outperforming people at more complex tasks.

On the opposing side, economists are writing off the most recent round of automation worry as unfounded fear-mongering, while pointing out that throughout the history of industrialization, prophecies of robots replacing human labour have appeared in both utopian and dystopian forms.

In the past, futurists claimed that mass automation would either usher in a time when people are liberated from labour or kill everyone to save the privileged few who control or invent the machines.

Yet the economy has often defied such forecasts. Automation has been a significant factor in economic progress and wealth for ages by killing certain occupations and creating others that are often higher paid and less taxing. The history of automation’s effects on the labour market has been chiefly one of “creative destruction.”

The Future Of Work

Technologies automate tasks and lessen the labour-intensive aspects of employment in practice. A farmer and his oxen once ploughed an acre of land daily. The same farmer can now plough 15 acres in the same amount of time with a tractor. Generative artificial intelligence will help knowledge workers to ensure a comparable rate of productivity growth. The solution will also make some equipment/abilities outdated in the process. Increased employment frequently results from such productivity improvements and the accompanying profit. In the US, between 2008 and 2018, employment rates in 11 jobs thought to be at risk from AI rose by an average of 13%.

Specialized AI systems excel in producing behaviours that mirror human patterns on well-known tasks because they rely primarily on human data. They also include prejudices. They struggle with the expectation of a job being carried out correctly every time, robustness, and the capacity to function consistently under varying conditions (including noise that has been purposefully inserted into the data). Today’s specialized AI systems cannot explain how people judge, the explainability issue exacerbates the trust issue.

21st-century businesses still rely on human employees as the capacity to adapt to entirely new conditions is still a massive barrier for artificial intelligence and robots. Humans continue to lead the pack in terms of social connection, incredible athletic prowess, common sense, and general intellect.

Specialized AI systems tend to be task-oriented from the standpoint of work, meaning that they do smaller subsets of jobs rather than the entire collection of activities that make up a profession. For example, one of the many duties performed by radiologists, such as viewing radiographs, is just one of many that are essential to their work. In this situation, artificial intelligence can free up more time for clinicians to focus on other activities like conducting physical examinations or creating individualized treatment regimens. Yet, these systems have grown so adept at automating critical aspects of flying that pilots may lose their manual feel for the controls, which can result in mishaps. Humans have long relied on automated pilots to supplement their manual aircraft control. However, the ability of AI systems in aircraft piloting has not yet been approved.

How Can Humanity Survive In A Future Dominated By Artificial Intelligence?

The solution is to develop your humanity. Workplace value will increase for agency, dedication, empathy, and perseverance. The drawback is that we frequently develop these qualities in our first employment. Because it is practically hard to start as junior staff, I’m still determining where we may get them.

Thoughtfully considering your clients and coworkers, your profession and its role in the world, and learning the finer points of its knowledge base should serve as a general prescription for success. Writing boilerplate code won’t get you very far as a software developer. Start learning about algorithmic complexity, delay, and clear abstractions instead. There will generally be less need to put up with the intelligent but volatile types on the job. Hence, perhaps a little humility and friendship are required for those of us with white-collar occupations.

The generative AI revolution is just getting started, and it will be fantastic.

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In regards to this, she says that she loves robots as sometimes one can find the one which gets stuck so one can help it and the robot replies back ‘Thank You’.

Starship Technologies’ robot delivery service was introduced in Milton Keynes four years ago and has since been slowly growing, with new towns being added just last month.

Amber Case is an expert on how technology affects daily living and the interaction between humans and robots who lives in Oregon. Robots are a common form of technology that is used to attack us in movies. However, we use the delivery robots that are waiting for us.

She believes that instances in which a robot runs into a barrier and needs assistance from bystanders as an essential component of the human-robot connection. If technology requires our help, it can be cute. We appreciate robots that occasionally need our assistance because it fosters a relationship between us.

Strangely, Amber Case criticizes the Starship Technologies delivery robots that litter Milton Keynes’ streets.

They are battery-operated, called and opened by an app, furnished with speakers and pedestrian-detection sensors. This enables a human operator operating from a distance to interact with persons caught on the vehicle’s cameras.

However, she claims that this technological armament is not being used properly. She believes that they are automating the incorrect portion of the process. Humans are very skilled at navigating difficult terrain and locating a specific home.

Despite these concerns, she admits that the Starship Technologies crew approached it correctly, knowing how to make sure it was adorable rather than threatening. They appear to give the design more thought than some robot manufacturers, and a well-designed robot has a higher chance of success.

The public likes the Starship robot’s design element. According to Victoria Butterworth, one of the reasons she moved to Milton Keynes was because of the robots.

Of course, there were many other reasons to relocate here, she continues, but her dachshund’s disc dislocation needs continual attention, which is when the robots started to play a significant role in her life.

She was able to take care of the dog thanks to the robots without having to go shopping. When the dog was sick, they were a true blessing.

She concludes by saying, human-robot relationships which can be seen emerging in Milton Keynes have vanished the stereotype of a menacing robot.

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That said, Facebook does not have a financial stake in NetEquity Networks and will not operate or own fiber networks deployed by the company. 

However, it plans to prove NetEquity with a nonexclusive royalty free licence to deploy this technology. Facebook on its blog said, “This system combines innovations in the fields of robotics and fiber-optic cable design to dramatically lower the cost of deploying fiber by utilising electrical infrastructure. While there have been tremendous improvements in the strength and size of a fiber strand, as well as the amount of data a strand can carry, there has not yet been a widely applicable solution for reducing the cost of fiber construction. Since the cost of deploying fiber comes almost entirely from construction, this was the area we wanted to address. If successful, we believe this technology will allow fiber to effectively and sustainably be deployed within a few hundred meters of much of the world’s population. We expect to see technology trials of this fiber deployment system next year.”

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