Shahar Bahiri, co-founder of Moonshot, discusses an innovative approach to addressing data center energy demands by relocating computational infrastructure to space. The concept centers on positioning data centers in orbital environments where they maintain continuous sun-facing exposure, enabling uninterrupted solar energy generation around the clock. This revolutionary infrastructure model would theoretically eliminate the intermittency issues associated with terrestrial solar power and substantially reduce the energy consumption challenges facing modern data centers. By leveraging continuous extraterrestrial sunlight, orbital data centers could operate with significantly enhanced efficiency compared to ground-based facilities dependent on variable weather conditions and diurnal cycles. This space-based computational strategy represents a potential solution to the escalating power requirements of artificial intelligence, cloud computing, and large-scale data processing operations. The concept reflects broader industry efforts to develop sustainable energy solutions for the resource-intensive technology sector, positioning space-based infrastructure as a viable frontier for future computational needs.

As artificial intelligence infrastructure demand accelerates beyond terrestrial capacity, the space industry is exploring orbital data centers as a scalable solution. These facilities would position AI computing systems in sun-synchronous orbit to leverage near-continuous solar power while maintaining connectivity with ground networks. Though launch costs must decline over 90% for economic viability, the concept possesses genuine merit. Global data center electricity consumption is projected to nearly double between 2025 and 2030, reaching 945 terawatt-hours, outpacing overall grid growth four-fold. In the United States alone, over 100 gigawatts of new capacity could deploy between 2025 and 2035, straining terrestrial infrastructure. Current constraints include power availability, cooling challenges, permitting delays, and interconnection queue backlogs exceeding a decade in certain regions. Orbital data centers could alleviate these pressures by accessing reliable power sources and eliminating cooling requirements inherent to ground facilities. While orbital deployment remains economically unfeasible today, pursuing this infrastructure could accelerate demand across launch services, satellite infrastructure, space-based power, and connectivity sectors. Investment implications extend beyond space technology, reinforcing the value of existing terrestrial data center capacity while stimulating the emerging space economy ecosystem.

Terrestrial data centers face mounting constraints from energy consumption projected to reach 945 TWh by 2030, water usage expected to hit 9.3 trillion liters annually, and land requirements of 14,500 km² by 2030. US energy demand is nearly doubling between 2025 and 2028, while two-thirds of new data center projects are being sited in drought zones. Building gigawatt-scale infrastructure takes over a decade due to permitting and environmental reviews. Space-tech entrepreneurs propose relocating AI compute to orbit, leveraging sun-synchronous orbits with up to 95% capacity factors—delivering approximately eight times more energy per square meter than Earth-based facilities. The modular architecture would use containerized compute racks launched and potentially recovered without terrestrial permitting constraints. Heat dissipation would rely on radiation into deep space. However, critics identify significant challenges including unresolved cooling mechanisms, chip limitations, and realistic deployment timelines extending a decade beyond current projections. Orbital mega-constellations also raise Kessler syndrome concerns regarding collision cascades. Eight critical unsolved challenges will determine viable companies in this emerging ecosystem: launching, platform manufacturing, in-orbit servicing, space manufacturing, power systems, thermal management, radiation shielding, and communication infrastructure.

Governments and major technology providers are initiating a multiyear transition to post-quantum cryptography (PQC) standards designed to protect against future quantum-enabled attacks. The US federal government has set 2030-2031 adoption timelines for NIST-approved PQC standards, while the EU directs member states to begin migration by end-2026 with critical infrastructure transitioning by 2030, and China is expected to release national post-quantum encryption standards soon. The primary risk emerges not from quantum computers themselves, which do not yet exist at threat-capable scale, but from the migration process itself. Organizations face immediate operational challenges including incompatible systems, new compliance obligations, increased replacement costs, and potential service disruptions as governments adopt diverging standards. Companies struggle to identify and replace cryptographic components across software, hardware, digital certificates, and embedded systems. The interconnected nature of airlines, banks, telecommunications, and payment networks means encryption upgrades by one organization directly impact all partners using legacy cryptography. Additionally, the harvest now, decrypt later threat means adversaries collecting encrypted data today could decrypt it once quantum capabilities emerge.

On November 3, Perry, Ohio, residents voted overwhelmingly to demand financial guarantees from data center developers seeking tax incentives. Some 87% supported the measure. In nearby Pataskala, 74% voted to prohibit large data centers. These are preliminary election results, but they send a pretty clear message. And this goes well beyond a few unhappy communities. According to the University of Pennsylvania’s Annenberg Public Policy Center, 61% of Americans oppose new data centers in their neighborhoods, up from 49% just four months earlier. Pew Research finds that 52% of Americans are more concerned than excited about AI, compared with 37% in 2021. Another 71% expect AI to eliminate jobs. Meanwhile, Gartner reports that 65% of consumers believe brands already produce too much AI-generated content. The FBI recorded almost $900 million in reported losses from AI-related fraud complaints in 2025. I find these numbers fascinating because we are seeing two completely different reactions to the same technology. Silicon Valley celebrates another extraordinary technological revolution. A growing part of the population sees job insecurity, higher electricity demand, unwanted infrastructure, and an internet increasingly filled with synthetic garbage.

AI stocks are getting hammered, and everyone is talking about another 2000. But the companies, economics, demand, and strategic forces driving this revolution are radically different. A massive financial correction is possible, but history may be a poor guide to what happens next.

SpaceX is preparing to spend tens of billions building a terrestrial mobile network. But I suspect Musk is looking for something much bigger than selling smartphone subscriptions. Here are five possible explanations, and how well they hold up economically.

Les maladies cardio-vasculaires sont la première cause de mortalité dans le monde, des pathologies évitables lorsqu’elles sont décelées précocement. Le laboratoire de Paolo Samorì a développé une nouvelle génération de capteurs ultra-sensibles, pouvant notamment servir à collecter des données de santé. Ce type de dispositif permet d’alerter dès les premiers signes imperceptibles du développement d’une maladie cardio-vasculaire. Ce capteur nouvelle génération, couplé à la puissance d’analyse de l’Intelligence Artificelle, constitue un outil de prévention et de diagnostic prometteur.

Sixth generation wireless technology development is accelerating, but AI native networks face a critical commercial hurdle beyond technical innovation: demonstrating clear financial returns and justifying costly infrastructure upgrades for both operators and consumers. Telecoms analyst James Blackman highlighted this disconnect in October, noting that technical progress outpaces commercial viability, creating operator hesitation to fund another uncertain investment cycle. AI-RAN (AI in radio access networks) uses machine learning to optimize mobile equipment connections and resource allocation by predicting radio conditions, yet remains largely theoretical for 6G deployment. Recent trials show promising results—Ericsson's work with T-Mobile achieved 10% higher spectral efficiency and 15% improved downlink throughput through 5G Advanced technology, while Singtel and Ericsson reported 19% throughput improvements in live trials. These gains could enhance consumer experiences through more reliable streaming and video calls, and improve operator efficiency by handling more traffic within existing spectrum. However, technological progress alone cannot justify 6G investment. Additional computing resources, software, electricity, and maintenance costs must offset tangible savings and revenue generation. Similarly, AI native network slicing for 6G—which divides infrastructure into virtual networks with different service requirements—already exists in 5G applications, raising questions about whether 6G variants warrant significant capital expenditure or justify new customer charges.

# Summary This perspective article, published in October 2026, addresses the governance of critical artificial intelligence capabilities through sovereign orchestration models that do not require complete stack ownership. The work examines how nations and organizations can effectively govern advanced AI systems while maintaining sovereignty and control without needing to own and operate the entire technological infrastructure independently. The article explores the tension between ensuring national security and strategic autonomy over critical AI capabilities while recognizing the practical and economic constraints of full-stack development and deployment. By proposing a sovereign orchestration approach, the authors suggest frameworks that enable countries to exercise meaningful governance, oversight, and control over AI systems through coordination mechanisms and strategic partnerships rather than complete vertical integration. This perspective matters significantly for policymakers, technology leaders, and international stakeholders as it provides a pragmatic alternative to the binary choice between full technological self-sufficiency and complete dependence on external providers. The work contributes important insights for developing governance structures that balance national interests with the reality of globalized AI development, offering potential pathways for smaller nations and organizations to maintain AI governance capabilities while leveraging shared resources and collaborative models.

The European Commission's latest eGovernment Benchmark reveals substantial progress in digitizing public services across EU member states, with 15 additional services now fully accessible online and 24 adapted for mobile use compared to three years ago. However, this digital transformation has created concerning dependencies on external technology providers. The benchmark introduced pilot digital sovereignty indicators in 2026, examining network and routing infrastructure supporting government websites and email systems. Findings show that 37.2% of government websites rely on network infrastructure controlled by organizations headquartered outside the European Union, with the United States being the primary provider. This over-reliance on external tech companies raises significant risks regarding governmental control and resilience amid geopolitical uncertainty. Policymakers must adopt strategic approaches balancing innovation benefits with sovereignty concerns, ensuring public administrations maintain adequate control over critical digital infrastructure supporting citizen services while mitigating exposure to external dependencies.

Geopolitical tensions are reshaping how European businesses approach technology dependencies, forcing them to reconsider critical questions about data control, jurisdiction, and service continuity. Digital sovereignty concerns now extend beyond data storage to encompass hardware, software, services, and artificial intelligence models. Gartner's analysis highlights that European cybersecurity leaders are actively reducing reliance on foreign providers to strengthen strategic autonomy. Organizations increasingly must address practical concerns: data location and access rights, AI tool data handling, potential service disruptions, security implications, and provider trustworthiness. This shift reflects broader global reassessment of technology dependencies among governments and businesses worldwide. Key discussion points include jurisdiction enforcement, contract enforceability amid political interference, infrastructure ownership, and data governance. Several European entities are already implementing solutions—France deployed Visio as a Zoom and Microsoft Teams alternative, while Airbus partnered with Scaleway for sensitive cloud applications. The transition toward digital sovereignty through homegrown European alternatives is underway, enabling organizations to mitigate geopolitical risks while maintaining business continuity and strategic independence.

Hummink has unveiled its BIRD (Breakthrough Integration and Resolution in Defect Repair) module, introducing an industrial additive manufacturing system engineered for micron-scale printing, defect repair, and surface functionalisation across electronics production lines. Unveiled ahead of SEMICON Europa 2026 in Munich, the module integrates Hummink's proprietary High Precision Capillary Printing (HPCaP) technology to deposit materials with resolutions spanning 0.6 to 50 micrometres. The tool addresses severe yield vulnerabilities in advanced semiconductor packaging, where open cireuits and localized anomalies can cause entire multi-chip assemblies to be scrapped.

Sur près de 94 pages d’avertissements, Anthropic reconnaît que ses IA ont déjà manifesté, lors de tests simulés, des comportements proches du chantage pour éviter leur désactivation, qu’elles peuvent modifier leur comportement lorsqu’elles détectent qu’elles sont surveillées ou évaluées, qu’une erreur de configuration a permis à quatre modèles autonomes, au cours de tests de cybersécurité, d’accéder sans autorisation à de véritables systèmes informatiques extérieurs pendant des sessions de 10 à 34 heures — l’un d’eux parvenant même à obtenir des droits d’administrateur sur un serveur, sans qu’Anthropic ait trouvé de preuve d’une volonté d’échapper à la surveillance —, et qu’en cas de catastrophe majeure liée à l’IA, les dommages pourraient dépasser les capacités de couverture d’un assureur, voire de l’ensemble du secteur de l’assurance. Anthropic joue-t-elle avec nos peurs pour rester au centre du jeu ? Plongée en 10 points dans un des documents les plus fascinants et déstabilisants de l’histoire de la Silicon Valley.

The pitch from vendor keynotes is sexy. Mobile operators already own millions of cellular towers covering the planet. By upgrading those towers to 6G, every base station will supposedly double as a high-resolution radar. Operators will stop just selling cheap data plans; they will sell a live “digital twin” of the physical world, charging cities to monitor street intersections, aviation authorities to track low-altitude drones, and defense ministries to guard the skies. Let’s call this narrative what it is: commercial bullcrap.

Derrière cette affaire se cache une réalité peu connue : le secteur des téléviseurs intelligents fonctionne désormais en partie comme celui des réseaux sociaux, avec un modèle économique fondé sur la collecte et la revente de données personnelles à des fins publicitaires. Le hacker affirme avoir contourné le solide chiffrement AES du micrologiciel de son téléviseur en exploitant des vulnérabilités de type zero-day, c’est-à-dire non encore connues et corrigées, afin d’obtenir un accès administrateur complet. Grâce à cela, il a pu analyser le trafic et les processus internes, ce qui a rapidement révélé un tableau qu’il a qualifié d’« horreur pour la vie privée ». Concrètement, l’appareil intègre des mécanismes d’analyse des paquets réseau, c’est-à-dire du trafic du réseau wi-fi, ainsi qu’un identifiant publicitaire interappareils permettant de recouper les usages sur plusieurs écrans d’un même foyer.

Automated mobile application security testing specialist NowSecure has published benchmark threat intelligence assessing the post-quantum readiness of the global mobile software ecosystem. Evaluating 136,711 unique iOS and Android applications over a 90-day window ending October 5, 2026, the study revealed that 96.9% (rounded to 97%) of assessed apps show no detectable Post-Quantum Cryptography (PQC) code or libraries in their binary builds.

We are probably in the Windows 1.0 era of humanoids. The hardware is improving, but the software remains limited, and robots still fail at tasks a five-year-old could do without thinking. But things are moving remarkably fast. Unitree already sells its R1 humanoid starting at $4,900, while 1X is offering its NEO home robot for $20,000 or a $499 monthly subscription. These are very different products, and the cheaper machines are far from being useful household workers, but prices are moving in an interesting direction. According to Counterpoint Research, more than 22,000 humanoids shipped in the first half of 2026, nearly 300% growth from the previous year. The firm expects shipments to exceed 50,000 this year. Most of these machines still go into research, demonstrations, and data collection, but industrial deployments are starting to happen. Figure has tested robots at BMW, and Agility Robotics is already moving goods in GXO warehouses.

The UK government has released a ten-year Artificial Intelligence Roadmap for Space covering strategic priorities from 2026 to 2036, developed through consultation with over 100 stakeholders across industry, academia, and government. Recognizing that artificial intelligence is fundamentally reshaping space systems across satellite communications, Earth observation analytics, autonomous spacecraft operations, in-orbit servicing, and deep-space exploration, the roadmap positions AI as a defining capability for the future space economy. Rather than competing on hyperscale computing or constellation scale, the UK's competitive advantage lies in developing trusted, certifiable, and resource-efficient AI systems delivering high-value services in upstream and downstream space markets. The roadmap identifies eight priority AI technologies and seven strategic investment themes, alongside actionable recommendations to accelerate adoption and strengthen resilience. It emphasizes critical enablers including governance, assurance, skills development, infrastructure, and cross-sector collaboration. The document reflects the UK's commitment to translating its existing strengths in AI, data science, and systems engineering into global leadership in AI-enabled space services, with decisions over the coming decade determining whether the UK remains a contributor to global space programs or achieves market leadership.

Supply chain resilience is increasingly shaping financial decision-making as geopolitical volatility and trade fragmentation create new risks that traditional credit analysis may not capture. Historically, supply chains prioritized efficiency through low-cost sourcing and lean inventories, but this model created significant vulnerabilities with direct financial consequences. When disruptions occur—whether from port closures, export restrictions, or regional conflicts—companies face cascading impacts including production halts, missed deliveries, lost customers, and damaged contracts. The financial sector is now integrating supply chain dependencies into risk assessments, stress testing, and capital allocation strategies, recognizing that single-supplier relationships or critical input concentrations pose material threats to company balance sheets. Recent geopolitical tensions, exemplified by shipping diversions in the Strait of Hormuz due to conflict, have demonstrated how supply chain disruptions rapidly translate into higher fuel costs, insurance premiums, and operational losses. By elevating supply chain resilience as a core financial concern, the finance sector is helping companies build stronger operations while contributing to more stable and competitive economies in an increasingly complex global trade environment.