"Is it Snowing in Space?!" “Is it snowing in space?!” Asks a disgruntled Bill Murray in the film Groundhog Day when he is told that he cannot call out from the snowbound town of Punxsutawney, Pennsylvania. If there is a remake, Bill might not have to worry: signal dead zones may soon be a thing of the past due to recent advancements in satellite technology. Whereas the old picture of satellite communications was a scientist in the wilderness with a big clunky antenna, these days the technological payload is all in space. Recent advancements such as Low Earth Orbit (LEO) satellites, advanced beamforming, and the use of mobile spectrum bands means that any phone supporting 4G LTE can potentially receive satellite data directly. This integration of satellite and terrestrial networks is set to reshape the mobile industry, creating both opportunities and challenges for traditional mobile network operators (MNOs) and mobile virtual network operators (MVNOs). In this article we give an overview of the technological advancements, the major players in the market, and then consider the effects this will have on traditional wholesale mobile market structures; concluding with the emerging opportunities for new revenue and growth. The Evolution of Satellite Connectivity Historically, satellite communications operated independently from terrestrial networks, serving specialised markets with limited scalability and high entry barriers. However, recent advancements, particularly in Low Earth Orbit (LEO) satellite technology, have dramatically altered this scenario. The most well-known example is obviously SpaceX, which has played a pivotal role in democratising space: reducing barriers to entry and making satellite connectivity more scalable, performant, and accessible. SpaceX and other companies have found innovative ways to dramatically reduce costs. Since Sputnik 1 in 1957, launching payloads into space has been prohibitively expensive, with costs exceeding $100,000 per kilogram in the 1960s and averaging $16,000/kg for heavy payloads from 1970 to 2010. SpaceX’s innovations have brought these costs down through reusable rockets, vertical integration, economies of scale, and advancements in materials and manufacturing processes: leading to price points as low as $100 per kilogram in recent years. However, cost is just one of the barriers. The real gambit has been provided by Low Earth Orbit (LEO) satellites, which typically orbit at altitudes ranging from approximately 160 to 2,000 km and offer low-latency, high-speed connectivity — making them ideal for real-time applications and direct-to-device communications. The latest generation of technologies now enable LTE mobile phones to connect directly to satellites without specialised hardware, marking a significant milestone in mobile communications. The Major Satellite-to-Cell Players While SpaceX's Starlink has garnered the most attention, several other major companies are actively developing satellite-to-cell technologies and forming strategic partnerships with terrestrial mobile operators. As of April 2024, Starlink had established 15 partnerships with mobile carriers globally — including T-Mobile in the US. T-Mobile has structured its beta program to begin with text messaging capabilities, gradually expanding to include picture messages, data connectivity, and eventually voice calls. As of February 2025, it is reported that 7,086 Starlink satellites are in orbit, with 7,052 being operational. AST SpaceMobile has emerged as a significant innovator, achieving a historic milestone in April 2023 with the first-ever two-way voice call directly with an unmodified smartphone, via their BlueWalker 3 satellite. AST SpaceMobile launched its first five commercial satellites, the BlueBird 1-5 mission, on September 12, 2024, aboard a SpaceX Falcon 9 rocket. Lynk Global represents another significant player. In a recent expense report, it revealed that each satellite costs around $400,000 to build and up to $815,000 to launch into space. They hope to have up to 1000 satellites (for full continuous broadband coverage) in orbit by 2025 and 32 mobile network operator (MNO) partnerships by the end of 2025. The company has successfully demonstrated text messaging capabilities from satellites to standard cellular devices and continues to expand its constellation and service offerings. Huawei has partnered with China Telecom to demonstrate satellite-to-phone messaging capabilities, while Apple has worked with Globalstar to implement emergency satellite messaging features in recent iPhone models. Implications for Traditional Wholesale Mobile Market Structures Traditionally, the wholesale mobile market has been structured around MNOs, MVNOs, and wholesale aggregators. Revenue streams have typically included MVNO wholesale pricing, and IoT and machine-to-machine (M2M) solutions. However, the rise of satellite-to-cell technology poses potential threats to this established model. Disintermediation of MNOs and MVNOs Satellite-to-cell connectivity introduces the potential for disintermediation, where control traditionally held by MNOs could become fragmented across multiple parties in the value chain. As satellite providers increasingly offer direct-to-device services, traditional operators risk losing their central role in network management and customer relationships. Pricing Pressure on Wholesale Markets The increased availability and competition from satellite connectivity providers could exert downward pressure on wholesale pricing. As satellite services become more affordable and accessible, traditional wholesale providers may face challenges in maintaining their pricing structures and profitability. Competitive Pressure in IoT and Enterprise Applications Satellite connectivity is particularly well-suited for IoT and enterprise applications, especially in remote or challenging environments. As satellite-to-cell technology matures, traditional wholesale providers may face intensified competition in these segments, necessitating strategic adjustments to remain competitive. Emerging Opportunities in Satellite-to-Cell Connectivity Despite these challenges, the integration of satellite connectivity into mobile networks also presents substantial opportunities for innovation and growth. Forward-thinking operators can leverage satellite-to-cell technology to develop new business models and revenue streams. Hybrid Terrestrial-Satellite Subscription Models Providing Ubiquitous Connectivity Operators can offer hybrid subscription plans that seamlessly integrate terrestrial and satellite connectivity. Such models provide customers with uninterrupted coverage, enhancing user experience and creating differentiated service offerings. Wholesale Satellite Resale for MVNOs Satellite-to-cell technology opens new avenues for MVNOs to expand their service portfolios. By reselling satellite connectivity, MVNOs can offer enhanced coverage and reliability, particularly in underserved or remote regions, thereby attracting new customer segments. IoT and Enterprise-Focused Applications Satellite connectivity is a natural fit for IoT and enterprise applications, such as remote monitoring, asset tracking, and industrial automation. Mobile operators can forge strategic partnerships with satellite providers to deliver specialised solutions for these markets, tapping into new revenue opportunities. Emergency-Only and Disaster Recovery Plans Satellite-to-cell technology can play a crucial role in emergency and disaster recovery scenarios, providing a reliable backup to terrestrial networks when they are unavailable or overwhelmed. Operators can develop emergency-only plans that leverage satellite connectivity to ensure critical communications during crises. Conclusion Satellite-to-cell technology represents a convergence of space and terrestrial communications systems that promises to fundamentally alter global connectivity markets and players. The dramatic reduction in launch costs by a factor of 20 has enabled the deployment of massive satellite constellations that were previously economically unfeasible. The competitive landscape continues to evolve rapidly, with SpaceX, AST SpaceMobile, and Lynk, and traditional telecommunications companies all pursuing various technological approaches and business models. Commercial text messaging services are already becoming available through beta programs, with video calling capabilities demonstrated and voice calls progressing toward wider availability. The integration of 5G standards with satellite networks continues to advance through collaborative industry initiatives, with projections of a $50 billion market by 2032. As this technology continues to mature throughout 2025 and beyond, it promises to eliminate mobile dead zones and create new application possibilities that were previously unimaginable. The future of mobile communications is undoubtably hybrid: blending terrestrial and non-terrestrial networks into seamless connectivity solutions that follow users wherever they go. This has wide reaching implications for connectivity in remote and isolated regions, and offers perhaps the fastest and most cost-efficient route to bridging the digital divide. It will also transform how we respond in disaster zones and hazardous areas — increasing the ability to protect and save lives with faster and safer humanitarian and emergency services.

What Problem do Too Many SaaS Providers Have in Common? Many SaaS security providers have a history of treating important safety and security features as something to upsell. This raises the important question of whether a software vendor has a moral responsibility for the secure operation of their solution. In this article, we explore the implications of treating important security and safety features as an upsell, using Boeing as a test case of where this can go wrong. The Case of Boeing and the Aviation Industry The case against Boeing is emblematic of a more systemic issue across the aviation industry, and many other industries. The public became aware of this issue under tragic circumstances when the Lion Air and Ethiopian Air Boeing 737 Max airliners crashed in 2018 and 2019 respectively. According to the widely quoted New York Times article , the crash could have been avoided if the pilots had access to two safety features that were sold by Boeing as optional extras. According to the incident reports, at the root of the incident were the angle-of-attack sensors. These mechanical sensors operate in a similar fashion to a weathervane to measure whether the aircraft’s nose is pointing above or below the direction of airflow. Being mechanical, they may be prone to malfunction, perhaps jamming after having been installed incorrectly — as was believed to be the case for the Lion Air aircraft . The system that led to the aircraft’s demise, which identifies the risk of the aircraft stalling, only listened to one of the sensors. A difference in the signal being sent by the two sensors was not recognised by the anti-stall system; and the instruments that would have alerted the pilots to the conflicting signals were upsell items. This wasn’t a fancy, nice-to-have bell or whistle that makes the flight more comfortable, efficient, or profitable. It is an underlying safety feature of the aircraft. If there was no safety requirement for the redundancy of two sensors, it is difficult to see why there would ever be more than one. Boeing has now addressed the issue, and the anti-stall system listens to both sensors, responding safely in the event of conflicting signals. It should also be noted that the investigation identified pilot error and deficiencies in the training that contributed to the disasters (and this will be relevant to our points regarding many SaaS product decisions as well). The SaaS Parallels Cloud-delivered Software as a Service (SaaS) has revolutionised the tech industry, and catalysed a phenomenal level of innovation and growth. It has enabled new software capabilities to be brought to market faster than ever before, and facilitated the ability to reach a scale with costs defrayed across multiple customers that would have been unimaginable 30 years ago. However, the benefits of being able to access a service from anywhere, at any time, by anyone also presents significant risks. The ‘anyone’ can be a malicious party operating outside of the reach of law enforcement or extradition. As a result, there are clear commercial responsibilities placed on SaaS providers to secure their infrastructure from attack, and those that do not are unlikely to last long in the marketplace. But just like the aviation industry, there are different flavours of security, and different perceptions of what is considered essential. Taking due care and applying due diligence to ensure that the platform itself is adequately secured from a direct attack is clearly the vendor’s responsibility – but what about those elements of security that relate to risk owned by their customers? One key element of customer risk relates to the security of a user’s password. It is their responsibility to make sure they choose a long and random string drawn from upper case, lower case, numerical, and special characters (if allowed). It is also their responsibility to ensure that they do not ever use the same password for multiple applications or services. But, we know that compromised credentials is a common failure mode. Just because it is the user’s responsibility to mitigate this risk, this doesn’t mean that system developers do not also have some mutual responsibility to make it easier for the user to exercise that responsibility; controls have been developed specifically for that purpose. The most obvious ones are Multi Factor Authentication (MFA, or 2FA), and Single Sign On (SSO). With MFA, we improve the security of the credentials by also verifying that the user is in possession of their trusted device before we trust them at sign in. With SSO, we minimise the number of credentials and accounts to manage by federating with a single corporate account; we can then concentrate our effort to secure that corporate account rather than spreading our resources thinly. Both are relatively easily implemented these days, particularly in the case of SSO where the OAuth protocols are widely offered by Identity Providers. Once implemented, both are essentially free to operate, particularly if MFA uses an Authenticator app rather than SMS text messages. SaaS providers recognise that this security is important, and they will frequently implement MFA and SSO controls into their applications to meet that customer demand. But, too frequently, we see them only offered as part of the more expensive subscription options. This element of security is not enhancing the vendor’s core proposition; it is not making their offering more functional, better looking, or more efficient for their users. It is just making it more secure, and therefore to treat it as an item to upsell comes across as price-gouging rather than the responsible application of good security practice. It is almost as though these vendors have run out of innovative bells and whistles that their clients would value in their core product, so they have had to resort to undermining the security of their cheaper options in order to encourage their customers to pay for their more expensive ones. It is equivalent to a bank only using the CSC code on a card to secure transactions for customers who pay for their premium banking services, because, after all, it is the customer’s responsibility to protect their card details. Conclusion What we have described here is not universal, and probably is not even representative of the majority of SaaS providers. But, when you are reviewing a new service, we urge you to take a closer look at what security your provider is charging extra for. If low cost, high value security controls are being upsold, then you may want to consider what other security good practices are not being considered essential. For more information about our cyber security consulting services and Secure by Design principles in action, please contact Tom Burton, Partner for Cyber Security, using the form below.

Since the origins of the quest for artificial intelligence (AI), there has been a debate about what is unique to human intelligence and behaviour and what can be meaningfully replicated by technology. In this article we discuss these arguments and the ramifications of 'ignorance' as it is expressed by current AI models. To what Extent can Artificial Intelligence Match or Surpass Human Intelligence? This article approaches the question of artificial intelligence by posing philosophical questions about the current limitations in AI capabilities and whether they could have significant consequences if we empower those agents with too much responsibility. Two recent podcast series provide useful and comparative insights into both the current progress towards Artificial General Intelligence (AGI) and the important role of ignorance in our own cognitive abilities. The first is Season 3 of 'Google DeepMind: The Podcast”, presented by Hannah Fry, which describes the current state of art in AI. The second is Season 2 of the BBC's 'The Long History of… Ignorance' presented by Rory Stewart, which explores our own philosophical relationship with ignorance. A Celebration of Ignorance Rory Stuart’s podcast is a fascinating exploration of the value that we gain from ignorance. It is based on the thesis that ignorance is not just the absence of intelligence. It feeds humility and is essential to the most creative endeavours that humans have achieved. To ignore ignorance, is to put complex human systems, such as government and society, into peril. The key question we pose is whether or not current AI appreciates its ignorance. That is, can it recognise that it doesn’t know everything. Can AI embrace, respect and correctly recognise its own ignorance: meaning it doesn’t just learn through hindsight but becomes wiser; and is fundamentally influenced, when it makes decisions and offers conclusions, that it is doing so from a position of ignorance. The Rumsfeldian Trinity of Knowns The late Donald Rumsfeld is most popularly remembered for his theory of knowns. He described that there are the things we know we know; things we known we don’t know; and things we don’t know we don’t know. Stewart makes multiple references to this in his podcast. At the time that Rumsfeld made the statement it was widely reported as a blunder—as a statement of the blindingly obvious. Since then, the trinity of knowns has entered the discourse of a variety of fields and is widely quoted and used in epistemological systems and enquiries. Let us take each in turn, and consider how AI treats or understands these statements. Understanding our 'known knowns' is relatively easy. We would suggest that current AI is better than any of us at knowing what it knows We also put forward that 'known unknowns' should be pretty straightforward for AI. If you ask a human a question, and they don't know the answer, it is easy to report this an an unknown. In fact, young children deal with this task without issue. AI should also be able to handle this concept. Both human and artificial intelligence will sometimes make things up when the facts to support an answer aren’t known, but that should not be an insurmountable problem to solve. As Rumsfeld was trying to convey, it is the final category of 'unknown unknowns' that tends to pose a threat. These are missing facts that you cannot easily deduce as missing. This includes situations where you have no reason to believe that 'something' (in Rumsfeld's case, a threat) might exist. It is an area of huge misunderstandings in human logic and reasoning; such as accepting that the world is flat because nobody has yet considered that it might be spherical. It is expecting Isaac Newton to understand the concept of particle physics and the existence of the Higgs boson when he theorises about gravity. Or following one course of action because there was no reason to believe that there might be another available: all evidence in my known universe points to Plan A, so Plan A must be the only viable option. In experiments with ChatGPT, there is good reason to believe that it can be humble; that it recognises it doesn’t know everything. But the models seem far more focused on coping with 'known unknowns' than recognising the existence of 'unknown unknowns'. When asked how it handles unknown unknowns, it explained that it would ask clarifying questions or acknowledge when something is beyond its knowledge. These appear to be techniques for dealing with known unknowns and not unknown unknowns. The More we Learn, the More we Understand How Much we Don’t Know Through early life, in our progression from childhood to adulthood, we are taught that the more you know and understand, the more successful you will be. Not knowing a fact or principle was not something to be proud of, and should be addressed by learning the missing knowledge and followed by learning even more to avoid failure in the future. In education we are encouraged to value knowledge more than anything else. But as we get older, we learn with hindsight from the mistakes we have made from ill-informed decisions. In the process, we become more conscious of how little we actually know. If AI in its current form does not appreciate or respect this fundamental concept of ignorance, then we should ask what flaws might exist in its decision-making and reasoning? The Peril of Hubris To feel that we can understand all aspects of a complex system is hubris. Rory Stewart touches on this from his experience in government. It is a fallacy to believe that we should be able to solve really difficult systemic problems just by understanding more detail and storing more facts about the characteristics of society. As Stewart notes, this leads to brittle, deterministic solutions based on the known facts with only a measure of tolerance for the 'known unknowns'. Their vulnerability to the 'law of unintended consequences' is proven repeatedly when the solution is found fundamentally flawed because of facts that were never, and probably could never be, anticipated. These unknown unknowns might be known elsewhere, but remain out of sight to the person making the decision. Some unknown unknowns might be revealed, by speaking to the right experts or with the right lines of enquiry. However, many things are universally unknown at any moment in time. There are laws of physics today that were unknown unknowns to scientists only few decades previously. The Basis of True Creativity Stewart dedicates an entire episode to ignorance’s contribution to creativity, bringing in the views and testaments of great artists of our time, like Antony Gormley. If creativity is more than the incremental improvement of what has existed before, how can it be possible without being mindful of the expanse of everything you don’t know? This is not a new theory. If you search for “the contribution that ignorance makes to human thinking and creativity” you will find numerous sources that discuss it, with references ranging from Buddhism to Charles Dickens. Stewart describes Gormley’s process of trying to empty his mind of everything in order to set the conditions for creativity. Creativity is vital to more than creating works of art. It is an essential part of complex decision-making. We use metaphors like 'brainstorming or blue sky thinking' to describe the state of opening your mind and not being constrained by bias, preconception or past experience. This is useful, not just to come up with new solutions, but also to 'war game' previously unforeseen scenarios that might present hazards to those solutions. What would you Entrust to a Super-Genius? So, if respecting and appreciating our undefined and unbounded ignorance is vital to making good and responsible decisions as humans, where does this leave AI? Is AI currently able to learn from hindsight – not just learn the corrected fact, but learn from the very act of being wrong? In turn, from this learning, can it be more conscious of its shortcomings when considering things with foresight? Or are we creating an arrogant super-genius unscarred by its mistakes of the past and unable to think outside the box? How will this hubris affect the advice it offers and the decisions it takes? What if we lived in a village where the candidates for leader were a wise, humble elder and a know-it-all? The wise elder had experienced many different situations, including war, famine, joy and happiness; they have improvised solutions to problems that they have faced in the past, and have learnt in the process that a closed mind stifles creativity; they knew the mistakes they had made, and therefore knew their eternal limitations. The village 'genius' was young and highly educated, having been to the finest university in the land. They knew everything ever written in a book, and they were not conscious of making a bad decision. Who would you vote for to be your leader? Conclusion The concepts described here are almost certainly being dealt with by teams at Google DeepMind and the other AI companies. They shouldn’t be insurmountable. The current models may have a degree of caution built into them to damp the more extreme enthusiasm. But I’d argue that caution when making decisions based on what you know is not the same as creatively exploring the 'what if' scenarios in the vast expanse of what you don’t know. We should be cautious of the advice we take from these models and what we empower them to do—until we are satisfied that they are wise and creative as well as intelligent. Some tasks don’t require wisdom or creativity, and we can and should exploit the benefits that these technologies bring in this context. But does it take both qualities to decide which ones do? We leave you with that little circular conundrum to ponder.