AST SpaceMobile decoupled from recent launch disappointments by scheduling the orbital deployment of its next three satellites on a SpaceX Falcon 9 rocket.

The space-based mobile network company hopes to blast its BlueBird 8, 9 and 10 satellites into low Earth orbit (LEO) on 17 June. As ever, launches are dependent on various environmental and other factors, so precise timing is fluid.

AST SpaceMobile expects the latest satellites to deliver almost twice the data rates of its initial BlueBird models, which it noted recently hit 98.9Mb/s in the downlink.

Company president Scott Wisniewski said the significance of the satellites goes beyond expanding its constellation and coverage: they represent the culmination of an in-house manufacturing drive and bolster claims to having birds with the largest phase-arrayed antennas at LEO heights.

AST SpaceMobile stated the trio of satellites are already stacked using a proprietary architecture and ready to be integrated with the SpaceX rocket.

The scheduled launch is something of a firing back by AST SpaceMobile at commentators who questioned whether a recent failure of a Blue Origin New Glenn rocket during a test would impact a plan to conduct regular launches throughout 2026.

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Interview: AT&T completed a controlled introduction phase of its cloud RAN deployment, with roughly 25 sites running live traffic on Intel’s Sapphire Rapids processors as it plans to aggressively scale deployment when Intel’s next-generation Granite platform arrives over the coming months.

The Sapphire deployment is currently handling the TDD layers of the network, which represent the largest share of traffic, but not yet the full stack.

Rob Soni (pictured), VP of the operator’s RAN architecture, told Mobile World Live (MWL) Granite, which is already in AT&T’s labs, will enable a full stack covering FDD, TDD, NR and LTE from a single server design.

“This is all coming in phased pieces through the fall and early next year,” he said. “We plan to scale more aggressively on Granite than we did on Sapphire.”

He said AT&T expects to move from a few hundred Sapphire sites to thousands on Granite through 2026 and into 2028.

Performance on the Sapphire sites is matching traditional RAN on call drop rates and throughput, Soni said, and the team is beginning to utilise the platform’s promise of faster feature delivery.

The leading example is AI-driven link adaptation, developed with Ericsson, which replaces rules-based scheduling algorithms with a deep neural network.

Trials are showing roughly 10% gains in spectrum efficiency and 15% improvements in individual user throughput, with further benefits expected as AT&T tunes the global Ericsson model to its own network morphology.

“We’ve done a lot of trailing with the kind of global model of Ericsson,” Soni explained. “We’re now in the process of tuning the model to the AT&T morphology, the AT&T usage. That will change the nature, and we expect there to be more gain.”

Halfway point

In cellular networks, Soni stated a base station must determine on every transmission frame which users to serve, what modulation and coding scheme to use and how to balance competing demands across the spectrum.

It is a computationally intense optimisation problem, and the traditional approach has been to encode engineering judgment into static rule sets. The AI model Ericsson developed learns from network behaviour and adapts more fluidly to changing conditions.

Link adaptation is a critical algorithm for determining the overall multiple user performance in a cellular network,” he stated.

Rival T-Mobile US stated in May 2026 it is also trialling Ericsson’s AI-native scheduler with link adaptation on live 5G-Advanced traffic, but Soni noted AT&T has been trialling it since December 2025.

Soni told MWL AT&T is just past the halfway point for switching out Nokia’s RAN gear for Ericsson’s as part of a five year plan to transition 70% of its network traffic to run on open platforms by end of year.

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The Linux Foundation launched the open-source Agentic AI Foundation (AAIF) six months ago to ensure protocols are standardised across enterprises, hyperscalers, and telecommunications companies.

The December launch spanned 49 companies, including co-founders Anthropic, Block, and OpenAI, with additional support from Google, Microsoft, AWS, Cloudflare and Bloomberg.

As of 3 June, it now has more than 200 member companies and is growing at twice the pace of the Linux Foundations CNCF Kubernetes project, AAIF executive director Mazin Gilbert told Mobile World Live.

“I think what is new that I have not seen before is that in every foundation I’ve been part of before, we used to go and ask, convince companies to join,” Gilbert said. “The phenomenon we’re seeing here is the opposite.

“Companies are coming on their own accord,” he added. “No outreach. They all want to have a say in this ecosystem.”

Being open source, all the members of AAIF benefit from the development of the tools and interfaces.

As the industry moves beyond chatbots and LLMs, Gilbert explained stakeholders need to agree on standard protocols and interfaces to deliver on agentic AI’s value.

Gilbert, whose career includes 22 years at AT&T and over four at Google, said there are roughly two million open-source models currently available, with open variants now only four months behind closed ones.

The infrastructure to run them is maturing fast but connecting those models to real applications, such as to self-healing networks, customer care systems and robotic platforms, requires standardised plumbing which nobody has built to date in a neutral, durable way.

“This foundation was created to ensure that the tools, the plumbing, the protocols are standardised,” Gilbert explained.

“I don’t need to know which language model out of the two million I should use,” he added. “I should be able to plug and play into any of them without any additional new code.”

He stated the real breakthrough will come from creating standard interfaces which enable AI agents to connect consistently with networks, databases, applications, microservices, other agents, and development tools.

When the plumbing is standardised, it will unlock a new ecosystem of interoperable agent-based systems, much like common internet protocols enabled the modern internet.

“We call it the internet of agents because now, suddenly, just like the internet, you can start to communicate, you can work with each other,” he said.

agentgateway
With the focus on plumbing, the AAIF welcomed agentgateway as its fourth hosted open-source project.

It is built on the A2A and MCP protocols and functions as what Gilbert calls a traffic light: routing agent-to-LLMa and agent-to-microservice communications, enforcing authentication, tracking token usage, and monitoring inter-agent channels.

For telcos, it offers a concrete path toward agentic network management without rebuilding their existing microservice estates from scratch.

“As far as the agents and the LLMs are concerned,” Gilbert said, “they look at the gateway as the endpoint.”

AI market
Setting aside the user application layer, Gilbert frames agentic AI as a four-layer stack: starting with AI-optimised hardware such as GPUs, TPUs and NPUs: moving up to AI-native infrastructure with Kubernetes, containers, service mech and data bases: then to foundation models, inference and model serving: and finally to the fourth agent applications layer where planning, reasoning and self-healing functions are expected to develop quickly over the coming months.

“We need to start populating what layer four is,” he said. “I expect the key work that we are doing now and over the next six months is to really make sure that we are looking at the agentic AI stack end-to-end.”

The roadmap for the next six months includes scaling 10 to 15 projects, a doubling of the working groups from the current eight, and the first production-scale deployments from member companies.

“We’re already starting to see some companies talking about thousands of agents already in production,” added Gilbert.

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T-Mobile US unveiled an AI-enhanced network optimisation capability aimed at keeping customers connected during high-density events including at packed stadiums, festival grounds and in post-concert taxi queues.

The mobile operator’s Dynamic CX is built on its self-organising network (SON) platform, which is also used to allocate network resources during natural disasters.

Operators have been using centralised self-organising network (C-SON) tools since 2010. In 2015, machine learning algorithms were introduced and blended with SON algorithms, which led to the first iteration of AI-for-RAN.

It is another feature built on the operator’s nationwide 5G-Advanced network which sits on its standalone 5G architecture.

Dynamic CX’s AI-driven automation adapts to network conditions in near real time, marking a meaningful step beyond traditional SON optimisation, which has historically been more reactive in nature.

The AI-enabled network optimisation capability continuously monitors and tunes network performance.

Dynamic CX scans publicly available event information, schedules and online activity to identify upcoming mass gatherings before they happen, allowing the network to begin preparing capacity adjustments in advance rather than scrambling to react once congestion hits.

Once an event is underway, Dynamic CX shifts into continuous monitoring mode, tracking how demand evolves as crowds move, stream and share throughout venues and surrounding areas.

T-Mobile is positioning the launch ahead of the FIFA World Cup, which starts this month and uses 11 US host cities. It is expected to draw millions of international visitors over several weeks.

CTO John Saw framed Dynamic CX as part of a longer arc of event-readiness investment to improve customer experience.

T-Mobile pointed to broader World Cup operational preparations including coordination with public safety agencies, staged deployable network assets and heightened cybersecurity posture across event-related infrastructure.

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Wirtgen Group is actively developing automated road construction vehicles as stepping stones for full autonomy using some of the same technology stack as parent company John Deere.

During a recent demonstration of its roadbuilding machinery at the company’s North American headquarters in the US state of Tennessee, company executives outlined the benefits of its specialised heavy machinery for road building.

Demand for roads and infrastructure keeps rising while contractors juggle labour shortages, climbing material costs, tighter project timelines and shorter paving seasons.

In the US alone, the construction industry is expected to need nearly 700,000 additional workers by 2031 just to keep pace with demand.

About 40% of the four million miles of roadways across the US are currently rated in poor or mediocre condition.

“As we talked with our customers, we learned a few things about some of their business challenges, which is simply to do more with less,” said Craig Lamarque, VP and head of digital products at Wirtgen America. “Every day our customers are responsible to ensure the safety of every person on absolutely every job site”.

“And they have to do that with increasingly less skilled and less experienced personnel.”

Lamarque explained customers must complete a greater number of projects on tighter timelines to stay profitable while coping with issues with materials, sustainability pressures, labour shortages, and the need to stay on budget and on schedule.

Wirtgen Group responded by introducing digital tools to help address those challenges.

He said Wirtgen’s digital strategy centres on three pillars: connected support to maximize uptime, job site intelligence to expose inefficiencies and improve decision-making, and smart automation to boost machine performance.

Those capabilities are embedded across its road construction equipment lineup and are supported by hardware and software in collaboration with John Deere.

A legacy built on family names

The Wirtgen Group was a privately held German company before it was acquired by John Deere in 2017.

Earlier in its history, the Wirtgen Group bought asphalt paving company Vogele (in 1996) ahead of purchasing soil and asphalt compaction company Hamm three years later. Vogele was established in 1836, one year prior to John Deere.

Kleemann was acquired in 2006, which expanded Wirtgen’s reach into mineral processing with mobile crushing and screening plants.

The Wirtgen Group bought a 70% stake in Benninghoven in 2014, adding asphalt mixing plants to the ecosystem and enabling Wirtgen to offer the entire cycle of road construction equipment from mixing and paving to milling and recycling.

Wirtgen America was established in 1984 and now includes 300 employees across the Tennessee campus.

“Every one of those names of the brands is a family name, much the same as Deere,” said Wirtgen America president and CEO Jim McEvoy. “From that standpoint, we have a long legacy of being early in these markets, being leaders in these markets and being very innovative in these product spaces.”

Here’s a look at three of the roadbuilding machines and technologies showcased in Tennessee across asphalt milling, paving and compaction.

Wirtgen milling machine
The milling machine removes old asphalt or concrete surfaces while using automation and digital guidance technologies to improve precision, efficiency and performance tracking. It is designed for high-output work on freeways, highways, airports and other major infrastructure projects.

The W210XF is equipped with a 2.5 metre-wide cutter drum which removes asphalt and concrete prior to loading the material into a truck. It uses automation and digital guidance technologies across eight cameras to improve precision, efficiency and machine performance tracking.

“Simple diagnostics, intuitive instructions on the display and backup components built into the machine make it easy to keep going,” Lamarque said.

WPT Milling documents job and machine data for billing and emissions tracking. Smart Level Pro is a fully integrated differential milling system which scans the surface about to be milled.

The process begins with a high-speed survey scan of the existing road surface, either by the customer or a third-party surveyor, without closing the road. The resulting digital model is then georeferenced and logged using GNSS.

After scanning, the road profile is refined to meet specifications, then uploaded to the John Deere Operations Centre and Work Planner, where cutting depths can be checked in advance which saves time compared with milling first and verifying later.

Utilising two John Deere StarFire receivers connected by cellular service, Lamarque said the mill goes to work, “precisely milling the design depth and slope, leaving the best possible surface”.

StarFire GNSS Guidance is Deere’s satellite technology which helps machines maintain highly accurate positioning, alignment and paving guidance throughout the roadbuilding process.

Mill Assist is an automated system on the milling machine that uses real-time machine data to optimise performance, improve efficiency, and reduce fuel consumption and emissions.

Vogele asphalt paver
The asphalt pavers are packed with highly specialised automation, levelling and material handling technologies.

Smart Pave is an advanced digital control and automation system developed by Vogele for its asphalt road pavers. AutoTrac technology helps the paver hold its direction of travel and paving width with precision.  

RoadScan is Vogele’s proprietary, non-contact thermal imaging and temperature measurement system mounted directly to the asphalt paver.

Hamm asphalt roller
The double-drum asphalt roller machine compacts fresh asphalt to the target density required for long term durability, using real-time density monitoring and intelligent compaction technology to hit the mark.

It focuses on preventing over-compaction, maximising operator efficiency and providing proof of compaction quality to contractors, state and federal authorities.

The roller uses a combination of vibration and oscillation to compact material to the desired density. Smart Compact Pro and Track Assist help road crews compact more efficiently, cost-effectively and safely while also meeting intelligent compaction specifications.

Intelligent compaction is data collection of the roller using GPS compact mapping, temperature sensors which map and report asphalt surface temperature and an accelerometer sensor that reports stiffness.

From automation to autonomy
Jason Ambroson, VP and managing director of Wirtgen International, explained running the same technologies, connectivity and data sensors across the various roadbuilding machines enables customers to be more productive using fewer employees and fewer resources.

“We are moving from automation to autonomy,” he said.

That trajectory of connecting machines, data and operators into a single intelligent system was what the Tennessee demonstration was ultimately built to show.

The post Feature: Wirtgen Group paves the way for autonomous road building appeared first on Mobile World Live.

Orange deepened its push into the travel eSIM market through a global distribution deal with online travel agency Trip.com, offering mobile connectivity at the point of travel booking as demand for roaming services grows.

Orange Travel, an Orange Group subsidiary, stated the partnership will enable Trip.com users to buy Orange Travel eSIM packages directly on the agency platform, allowing customers to arrange connectivity before departure, pay in local currency and activate the eSIM upon arrival.

Trip.com customers will be able to buy packages covering France, Italy, Spain, the UK and Switzerland, with the partners aiming to target key European tourist markets. The pair noted the region accounts for more than 50 per cent of global tourist arrivals, led by France and Spain.

The packages on offer include calls, texts and data across 20GB, 50GB and 100GB options, with validity periods of ranging from a week to 30 days. Prices start at €8.99.

Orange Travel highlighted its eSIM services are supported by the Orange Group’s network reach, including connectivity in more than 200 destinations and 700 roaming agreements worldwide.

Orange Travel CEO Frederic Blehaut said the agreement demonstrates its “commitment to accelerating our growth in Asia and internationally through strategic partnerships”, adding the subsidiary offers “European eSIMs with a recognised quality of service backed by the Orange Group’s know-how”.

Chase Liu, general manager of international attractions and tours business at Trip.com Group, added: “With tailor-made offers and packages easily accessible on our platform, our customers can enjoy enhanced connectivity and greater convenience when they travel in this region.”

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AI player Anthropic confidentially submitted paperwork for its proposed initial public listing ahead of rival OpenAI, while also giving the European Union’s cybersecurity body preliminary access to its Mythos AI tool.

The draft registration statement submitted to the US Securities and Exchange Commission gives the company the option to go public after the agency completes its review.

Anthropic stated the number of shares to be offered and the price have not yet been set.

News of the IPO move came the same day (1 June) Bloomberg reported Anthropic will give ENISA, the European Union’s cybersecurity agency, access to Mythos through Project Glasswing, an initiative which allows organisations to test Mythos’ capabilities before a wider release.

There are growing concerns among governments over the security implications of Mythos, which Anthropic released to some private companies in April.

Anthropic communicated the decision to the European Commission over the weekend.

EC spokesperson Thomas Regnier confirmed the development to Mobile World Live (MWL) followed several weeks of productive discussions.

 “We welcome the latest developments on potential future access,” he said. “This is the result of the Commission’s strong bilateral cooperation and engagement with Anthropic, a leading frontier AI company.”

The EC was careful to frame the moment not as a resolution but as a starting point to work with the US administration, Anthropic and additional AI companies such as OpenAI.

“This is a shared challenge, and we are intensifying our discussions with like-minded partners, including the United States,” Regnier said.

The plan is for ENISA to join Project Glasswing, the coalition Anthropic announced in April which includes Amazon, Apple, AT&T, T-Mobile US, Microsoft, Google, CrowdStrike, Nvidia and Palo Alto Networks, among others.

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Qualcomm CEO Cristiano Amon used his keynote at the annual Computex event in Taiwan to stake the company’s claim in the next phase of AI, arguing the technology will reshape demand for compute across devices, networks and data centres.

Amon described 2026 as the “year of the agent”, stating AI is moving from prompt-based interactions to autonomous systems capable of planning, reasoning and acting across smartphones, PCs, cars, robots and industrial equipment.

“Agents are not coming in the future. They’re already here,” he said, adding the shift is “changing a lot of the compute” and could generate “a lot of demand for new classes of devices and computing”, creating “one of the largest” upgrade cycles the industry has seen.

Amon said the smartphone will no longer sit alone at the nexus of the digital ecosystem. “Agents become the centre of your digital experience,” he stated, adding devices will increasingly become “endpoints for agents”.

Compute continuum
To this end, the executive laid out Qualcomm’s ambition to support the AI infrastructure transition. Amon pointed to the need for CPUs, GPUs, NPUs and connectivity designed to support AI workloads both on devices and in the cloud, stating the company can help scale AI compute from “sub-2 milliwatts” in devices such as earbuds to kilowatt-level systems in data centres.

He also stressed the engineering challenge around battery life and latency, noting devices must be able to support complex planning, reasoning and coordination. “I cannot emphasise enough the importance of power,” he said.

In addition, Amon framed 6G as a key part of the future AI architecture, noting it is the first wireless generation designed as an AI-native network connecting distributed, hybrid intelligence across devices and data centres.

During the event, the chief also unveiled Dragonfly, Qualcomm’s new data centre brand aimed at inference workloads. He said Qualcomm is already working with hyperscalers and global partners on deployments, adding the fresh brand will allow its portfolio to span “every single tier of the compute continuum”.

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