An Earth observation satellite has successfully identified targets on its own while in orbit, without requiring human analysts on the ground, marking what is believed to be the first reported use of a vision-language AI model operating in space.

What Happened?

The milestone took place aboard YAM-9, a satellite operated by space infrastructure company Loft Orbital.

Traditionally, Earth observation satellites collect large volumes of imagery and sensor data, which are then transmitted to Earth for analysis by either human operators or machine-learning systems. In this case, however, the analysis happened directly on the satellite itself.

Using software developed by NASA’s Jet Propulsion Laboratory (JPL) and Google’s Gemma 3 vision-language model, the spacecraft was able to interpret natural-language instructions and identify relevant features within the imagery it was collecting. According to reports, researchers asked the system to locate things such as infrastructure around railway hubs and areas where human development meets the natural environment, and the satellite successfully identified them.

The demonstration is believed to be the first publicly reported example of a vision-language model operating autonomously in orbit.

How The Technology Works

The project combined several technologies that have become increasingly important in artificial intelligence.

Vision-language models differ from conventional image-recognition systems because they can understand both images and natural-language instructions. Rather than being trained to identify only specific objects, they can interpret broader requests expressed in everyday language.

On YAM-9, Google’s Gemma 3 model was integrated into a software platform called NAVI-Orbital, developed by NASA JPL. The system ran on an Nvidia Jetson Orin AGX processor carried onboard the satellite.

This allowed the satellite to analyse imagery while still in orbit rather than waiting for instructions from Earth.

Instead of downloading vast quantities of raw data and asking analysts to search through it later, the satellite could determine which information was relevant and prioritise it automatically.

Why This Matters

The development could significantly change the economics and usefulness of Earth observation.

Modern satellites generate enormous amounts of data, much of which may never be examined in detail because analysing it requires time, computing resources, and human expertise. By performing initial analysis onboard, future satellites could reduce the volume of data that needs to be transmitted and processed on the ground.

Paul Lasserre, Loft Orbital’s head of AI, described the wider opportunity by saying: “If you have a VLM, you can have logic, like ‘monitor this border for me, and let me know when something is suspicious,’ and interact back and forth with the satellites.”

That represents a change from satellites acting primarily as remote cameras towards becoming active participants in monitoring and decision-making processes.

The technology could also help reduce delays. For example, rather than waiting for imagery to be downloaded and reviewed, operators could potentially receive alerts about significant events as they occur.

Potential Applications

The possible uses extend across both commercial and public-sector activities.

Loft Orbital already highlights applications including vessel detection, asset monitoring, border security, environmental tracking, wildfire detection, vegetation monitoring, and deforestation analysis. The company’s wider vision involves deploying AI applications directly in orbit rather than relying entirely on ground-based processing.

The company states that its AI-enabled infrastructure allows decision-makers to have “their questions answered in near real-time”.

Future systems could potentially monitor shipping routes, identify unusual activity around critical infrastructure, detect environmental changes, or support emergency response efforts following natural disasters.

Loft is also developing Altair, a planned ten-satellite AI-enabled constellation designed for near real-time monitoring and deployment of space-based AI applications.

Part Of A Bigger Change

The demonstration also points towards a broader trend within the space industry. For decades, satellites have primarily been designed to collect information and transmit it elsewhere for analysis. Increasingly powerful onboard processors are now making it possible for spacecraft to perform far more sophisticated tasks independently.

According to Loft Orbital, “Traditional satellites cannot keep up” with the pace of AI development, which is why the company is investing heavily in on-orbit computing and AI infrastructure.

Researchers involved in the project also see potential applications beyond Earth observation. NASA JPL has previously discussed how similar AI assistants could eventually help astronauts working on the Moon or Mars by providing interactive support without requiring constant communication with Earth.

What Does This Mean For Your Business?

The project really demonstrates how AI is increasingly moving closer to where data is generated rather than relying entirely on centralised data centres and cloud platforms. Similar trends are already emerging in manufacturing, transport, cyber security, healthcare, and industrial monitoring, where AI systems are being deployed directly at the edge rather than waiting for data to be sent elsewhere.

The satellite also highlights a change in how organisations may interact with technology. For example, rather than collecting information and analysing it later, future systems are increasingly being designed to understand objectives, identify relevant information, and proactively highlight what matters.

The result is not simply faster analysis, but it also represents a move towards autonomous systems that can act as intelligent assistants, helping people make decisions from vast amounts of data that would otherwise be impossible to process efficiently. As AI capabilities continue to improve, that model is likely to become increasingly common both in space and here on Earth.

Tesco is migrating approximately 40,000 servers away from VMware while simultaneously pursuing legal action against Broadcom for more than £100 million, in a dispute that highlights growing concerns about software licensing, vendor lock-in, and the risks of relying on critical technology platforms.

What Happened?

The dispute stems from Broadcom’s acquisition of VMware, one of the world’s largest providers of server virtualisation software, by US technology giant Broadcom in late 2023.

Before the takeover, Tesco had purchased perpetual VMware licences in 2021 that included software updates and support until 2026, together with an option to extend support arrangements until 2030. According to Tesco, those agreements formed part of its long-term technology planning for critical systems across the business.

Following the acquisition, however, Broadcom changed VMware’s licensing model and moved customers towards subscription-based offerings.

Tesco alleges that it was prevented from continuing with the support arrangements it expected under its existing agreements and instead faced significantly more expensive bundled subscription packages. The retailer is now pursuing legal action in the UK High Court against Broadcom, VMware entities, and other parties connected to the dispute.

Why Tesco Is Migrating

Perhaps the most striking aspect of the story is that Tesco is not waiting for the court case to conclude.

For example, the retailer has already begun a major programme to replace VMware across its estate and intends to complete the migration by the end of 2027. According to court filings, Tesco began migration efforts in 2025 after concluding that it could no longer depend on the outcome of the legal dispute.

It is worth noting here the sheer scale of this project. For example, migrating 40,000 servers is a complex undertaking that involves replacing core virtualisation infrastructure, retraining staff, testing alternative platforms, maintaining business continuity, and ensuring compatibility with a wide range of existing applications and services.

Tesco’s legal filings seem to suggest the company believes the operational disruption and migration costs are preferable to remaining dependent on its current VMware arrangements.

The Pricing Dispute

At the centre of the disagreement is the question of cost. According to Tesco’s legal filings, Broadcom offered a one-year VMware Cloud Foundation subscription that was substantially more expensive than the pricing Tesco expected under its previous renewal arrangements. The retailer claims some proposals represented increases of approximately 175 per cent compared with earlier pricing structures.

The dispute also extends beyond VMware. Tesco has claimed that software and support arrangements connected to CA Technologies mainframe products, which are also owned by Broadcom, became significantly more expensive following the acquisition.

In court filings, Tesco alleges that it has been forced to incur substantial costs procuring alternative products, hiring external specialists, and diverting internal resources towards accelerated migration projects.

A Wider VMware Backlash

The Tesco dispute has attracted quite a bit of attention because of its size, but it seems the issues at the heart of the case are affecting many VMware customers.

For example, since Broadcom completed the VMware acquisition, many organisations have reported significant changes to licensing, packaging, and purchasing arrangements. The company’s strategy has focused on simplifying VMware’s product portfolio and encouraging customers to adopt broader subscription bundles centred on VMware Cloud Foundation.

Supporters argue that this approach provides a more integrated platform and creates clearer product offerings. Critics, however, have expressed concerns about rising costs and reduced flexibility, particularly for organisations that previously relied on perpetual licences.

The situation has created opportunities for rival vendors. Companies including Nutanix, Microsoft, HPE, and other virtualisation providers have increasingly positioned themselves as alternatives for organisations seeking to reduce dependence on VMware.

The Challenge Of Depending On One Technology Platform

The Tesco dispute highlights a broader challenge facing organisations that depend heavily on a single technology platform.

Many businesses view software licences as long-term assets and build operational plans around assumptions about future support, pricing, and compatibility. Acquisitions can disrupt those assumptions, particularly when new owners adopt different commercial strategies.

The case also demonstrates how difficult it can be to move away from deeply embedded technology. Tesco’s migration involves tens of thousands of servers, third-party support arrangements, infrastructure redesign, application testing, and significant operational risk. Even for one of Britain’s largest retailers, replacing a critical technology platform is neither quick nor inexpensive.

Also, the fact that Tesco has decided to proceed with the migration while litigation continues appears to show the extent to which the relationship has broken down.

What Does This Mean For Your Business?

For businesses, the most important lesson is not whether Broadcom or Tesco ultimately prevails in court. The story really highlights the importance of understanding technology dependencies and having contingency plans for critical platforms. Software vendors can change ownership, licensing models, support arrangements, and commercial priorities far more quickly than organisations can replace core infrastructure.

It also demonstrates the value of regularly reviewing exit strategies. Many businesses carefully assess the benefits of adopting a platform but spend less time considering what would be involved if they needed to leave it.

Most organisations will never face a migration on the scale of Tesco’s 40,000-server project. However, the underlying challenge is familiar to businesses of all sizes. The more critical a technology becomes to daily operations, the more important it is to understand the risks associated with relying on a single supplier.

The Tesco case may ultimately become one of the most closely watched technology disputes of recent years because it raises a question that, when you buy software, how much control do you really retain if the company behind it changes?

New research shows that 43 per cent of MSPs and their customers experienced a cyber incident linked to a supplier or third-party vendor during the last year.

CyberSmart’s 2026 MSP Survey found that MSPs are increasingly being targeted because their access to customer systems can provide a route into multiple organisations. More than half of supply chain incidents involved the MSP as well as the customer.

The survey also found that only 45 per cent of MSPs continuously monitor third-party risk. CyberSmart CEO Jamie Akhtar warned that “a single weak link can have far-reaching consequences for customers, suppliers and partners”.

The findings come as MSPs prepare for the UK’s Cyber Security and Resilience Bill, which will increase scrutiny of supply chain security.

Businesses can reduce their exposure by reviewing supplier security, limiting third-party access, and monitoring supply chain risks on an ongoing basis.

The Trump administration has taken the unusual step of intervening in an environmental lawsuit against Elon Musk’s AI company xAI, arguing that the data centre at the centre of the dispute is so important to national security that it should be protected from legal action seeking to restrict its power supply.

Dilemma

The case highlights a growing sustainability dilemma facing the AI industry. For example, while artificial intelligence is increasingly being positioned as a tool for solving global challenges, its rapidly growing appetite for electricity is creating new environmental pressures, particularly as operators race to build ever-larger data centres.

Why The Government Has Intervened

The dispute in the U.S. centres on xAI’s Colossus AI facility in Mississippi, which relies on dozens of methane gas turbines to help power the infrastructure used to train and operate Grok, the company’s AI model.

The National Association for the Advancement of Colored People (NAACP), one of the oldest and largest civil rights organisations in the United States, filed the lawsuit. In this case, the NAACP’s Mississippi State Conference filed it. The lawsuit alleges that the turbines are operating without the permits required under the Clean Air Act and are contributing to air pollution that could affect nearby communities.

However, in a court filing submitted on behalf of the United States government, the Department of Justice argued that the lawsuit threatens “American national, economic, and energy security by seeking to shut off the power supply for artificial-intelligence innovation that supports the Department of War’s military operations.”

The filing seeks dismissal of the case and represents an unusually direct intervention by the federal government in support of a private technology company.

Why Grok Is Being Treated As A Strategic Asset

A key part of the government’s argument is that Grok has become integrated into sensitive national security operations. For example, according to a declaration submitted by Cameron Stanley, Chief Digital and Artificial Intelligence Officer at the Department of War (previously known as the Department of Defense), xAI’s Grok is “one of only four proprietary state-of-the-art (‘frontier’) AI models currently capable of supporting national security applications”.

The declaration also states that the Department relies on a specialised version known as Grok Gov Model and that it provides capabilities “found in no other frontier AI model”.

The filing claims that if the Mississippi facility were unable to continue operating at its current scale, the development and improvement of future Grok models could be affected, potentially impacting military and intelligence capabilities.

Whether or not the court ultimately accepts those arguments, the case demonstrates how rapidly advanced AI systems are being reclassified from commercial technology platforms into infrastructure that governments increasingly view as strategically important.

The Environmental Cost Of AI Growth

The environmental concerns at the heart of the case are difficult to ignore. For example, the turbines reportedly emit pollutants including nitrogen oxides and particulate matter, both of which have been linked to respiratory and cardiovascular health problems. Environmental groups argue that communities living near the facility should not bear the environmental cost of powering AI systems.

Also, the growth of AI is creating unprecedented demand for electricity. Modern AI models require vast numbers of processors working simultaneously, and those processors need enormous amounts of power.

The result is that many technology companies are now competing for access to electricity on a scale more commonly associated with heavy industry.

This creates an uncomfortable contradiction. Many of the same companies investing heavily in sustainability initiatives and clean technologies are simultaneously searching for whatever energy sources can support their rapidly expanding AI ambitions.

The Search For Cleaner Alternatives

The controversy also highlights why technology companies and investors are increasingly searching for lower-carbon energy sources capable of supporting AI’s growing power demands. One recent example is Critical Energy, a startup founded by a former SpaceX engineer that has raised $22 million to develop modular geothermal turbines for geothermal power plants. The company argues that geothermal energy could provide reliable, round-the-clock electricity for energy-hungry AI infrastructure years before many advanced nuclear projects become commercially available.

Projects such as these are attracting growing attention because geothermal energy can provide continuous power without the intermittency associated with solar or wind generation.

For the AI industry, that matters because data centres require power around the clock, making reliability almost as important as sustainability.

The challenge, however, is that many cleaner energy projects take years to deploy, while AI demand is growing today.

What Does This Mean For Your Organisation?

This case essentially offers an early glimpse of a debate that is likely to become increasingly common over the next decade. Governments want to lead in AI. Businesses want access to more powerful AI tools. At the same time, communities, regulators, and environmental groups are demanding that growth happens responsibly, and the lawsuit against xAI sits directly at the intersection of those competing priorities.

For organisations investing in AI, the wider lesson is that sustainability is becoming an infrastructure issue as much as a software issue. Questions about where AI runs, how it is powered, and what environmental impacts it creates are likely to become increasingly important alongside discussions about capability, productivity, and security.

The case also suggests that some governments are beginning to treat advanced AI infrastructure in much the same way as power stations, telecommunications networks, and defence assets. If that trend continues, future debates about AI may focus as much on energy policy and environmental impact as they do on the technology itself.

The political backdrop is also difficult to overlook in this particular case. Given Elon Musk’s close relationship with the Trump administration, some critics are likely to question whether the government’s intervention reflects purely national security concerns or whether political considerations may also have played a role. The administration maintains that its position is based on the strategic importance of the AI infrastructure involved.

The outcome of this particular lawsuit remains uncertain at this point. What is already clear, however, is that the race to build more powerful AI systems is creating difficult choices between economic growth, national security, environmental protection, and sustainable energy development, choices that governments, businesses, and communities will increasingly be forced to confront.

Microsoft’s new ‘Cowork’ feature in Copilot lets you assign tasks by simply describing the outcome, with Copilot creating a plan, using your Microsoft 365 data, and carrying out tasks across apps in the background while keeping you in control at every step.

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If Gemini AI prompts in Google Docs are getting in the way of your writing, there’s a quick way to turn them off and regain a cleaner, more focused workspace.

Why This Matters

Google has been steadily integrating Gemini into Google Docs, Sheets, Gmail, and other Workspace applications. While many users find the AI features useful, others prefer a cleaner writing environment without AI prompts appearing on screen.

Reducing these prompts can make documents feel less cluttered, help you focus on writing, and give you more control over when and how you use AI tools.

How To Hide The Gemini Bottom Bar In Google Docs

If you see a Gemini prompt box at the bottom of your document, you can hide it:

• Open your Google Doc.
• Click Gemini in the menu bar.
• Select Bottom Bar Preferences.
• Turn off the Gemini bottom bar.

This removes the AI prompt panel from the bottom of the document while allowing you to access Gemini manually if you need it later.

How To Reduce AI Features Across Google Workspace

You can also disable some Workspace smart features that power AI-driven suggestions and personalisation.

• Open Gmail.
• Click the Settings cog.
• Select See All Settings.
• Scroll down to Google Workspace Smart Features.
• Click Manage Workspace Smart Feature Settings.
• Turn off Smart Features in Google Workspace if you no longer want these features enabled.

This setting affects several Google Workspace applications and may reduce some AI-powered suggestions and prompts.

Things To Keep In Mind

Turning off Workspace smart features does not necessarily remove every Gemini capability from your Google account. Some Gemini features may still be available depending on your Google Workspace subscription, administrator settings, and the specific applications you use.

However, these settings can significantly reduce AI prompts and create a cleaner, less distracting workspace for users who prefer to write and work without constant AI assistance.

A Cleaner Way To Work

AI tools can be useful when you need them, but many people don’t want them appearing every time they open a document. Taking a few moments to adjust these settings can help create a simpler, more focused Google Docs experience while still allowing you to use Gemini when you choose to.