Google announced on Tuesday, the 21st, the completion of the connection of a new transatlantic submarine cable in the city of Sines, Portugal. This new infrastructure establishes another data transmission route between the United States and Europe, during a period of high demand for artificial intelligence (AI) and cloud computing services.
This cable, named Nuvem, referencing the Portuguese word for 'cloud', connects Myrtle Beach, in South Carolina, United States, to Sines, located south of Lisbon. The cable's route crosses the Bermuda Islands and the Azores before reaching Portuguese territory.
According to Google information, the Nuvem system has an approximate length of seven thousand kilometers and is composed of sixteen pairs of optical fibers. Its total projected capacity reaches about 384 terabits per second. Giorgia Abeltino, Head of Government Affairs and Public Policy for Google Cloud in the EMEA region, stated that this project is part of a broader strategy focused on strengthening digital infrastructure.
She added that the cable supports a vision for Portugal and Europe to increase investments in strategic infrastructure, which is essential to sustain the digital economy. It is important to note that submarine cables function as the backbone of the global internet, responsible for transporting over 95% of all worldwide data traffic.
The arrival of this new cable consolidates Portugal's position as a strategic point for intercontinental connections. Currently, the country already has two other high-capacity cables: Equiano, also operated by Google, which connects Portugal to South Africa, and EllaLink, which links Sines directly to Brazil.
During the inauguration ceremony, Gonçalo Matias, Minister of State Reform and Innovation of Portugal, emphasized that the project is part of a national plan to transform the country into a hub for innovation, AI, and data centers, while also raising European digital resilience and sovereignty. He stated that Portugal is becoming the 'Atlantic gateway of Europe, the meeting point of three continents: Europe, Africa, and the Americas.'
Portugal's Atlantic coastal location is seen by the company as a privileged factor for installing intercontinental submarine cables, which also attracts investments in data centers intended for the development and operation of AI systems. Furthermore, Portugal plans to leverage its abundant low-cost renewable energy, generated from solar, wind, and hydroelectric sources, possessing over 2.6 gigawatts of energy capacity under development.
Among the highlighted projects is the Start Campus, located in Sines, with a planned capacity of 1.2 gigawatts. This initiative is expected to receive benefits from Microsoft's investments in AI infrastructure and foresees considerable expansion in the coming years.
Huawei Cloud has introduced CloudRobo, a comprehensive platform for developing embodied artificial intelligence. This platform covers the entire workflow: from data creation and model development to robot simulation and deployment. With this move, the company has declared its position as a provider of the intelligent 'brain' for robots, rather than a direct manufacturer.
This strategy mirrors Huawei's approach in the smart car sector, which led to the success of SERES/Ask. Instead of creating the final product independently, Huawei provides the intelligent core, ecosystem, and development platform, allowing other companies to create competitive products. More than twenty companies, including Youibot and Huayan Robotics, have joined CloudRobo as initial partners.
The architecture of the CloudRobo platform is based on three main elements. First, a PB-level data foundation provides access to millions of ready-made datasets. Second, a cloud engine for model production utilizes a series of Pangu models running on Ascend AI chips. Third, an internal Real-Sim evaluation system allows for realistic virtual testing.
Developers gain access to over 20 models optimized for Ascend and can connect a robot to the cloud in mere hours, while deploying a model takes minutes. The platform covers the entire process of embodied AI development: data collection, model training, simulation evaluation, hardware integration, and operation.
The logic of this strategic decision replicates Huawei's proven model. In the smart vehicle segment, Huawei supplied intelligent driving systems, cockpits, and electric drive technology, while partners handled manufacturing. This model allowed SERES to transform from an unknown manufacturer into a premium electric vehicle brand, and the M9 model became a bestseller in the segment above 500,000 yuan. Now, Huawei is applying the same division of labor concept to embodied AI: the company provides the intelligent operating system, cloud platform, and basic AI models, while robot manufacturers focus on hardware development, production, and vertical application scenarios where they possess expertise.
The high gross profit margin of controllers at 79.8% compared to the equipment margin of 38.4% confirms the priority of the strategic focus on software-defined value.
The current time reflects industry maturity. Robot motion control capabilities are largely standardized among major manufacturers, making the intelligent processor the primary differentiator. The fragmented robotics landscape, encompassing industrial manipulators, service robots, quadrupeds, and humanoids, requires a unified development infrastructure to avoid every team recreating everything from scratch. Huawei CloudRobo solves the problem of manual development, where individual groups wasted excessive resources on creating custom data pipelines, model training, simulation environments, and hardware integration instead of innovating in applications.
Although it remains unclear whether Huawei can replicate its smart vehicle ecosystem strategy in embodied AI, given that cars feature high standardization and uniformity, whereas robots have extremely diverse requirements, Huawei already possesses the M-Robots OS based on OpenHarmony and over 15 embodied AI startups founded on talent nurtured by Huawei, indicating the company's influence extends far beyond the CloudRobo platform itself.
A team of Chinese and international researchers has created the world's first spatially resolved map of the spectral index of a black hole at the scale of its event horizon, opening new possibilities for studying the extreme physical environment around these objects.
The study, published in The Astrophysical Journal Letters on Monday, was conducted by scientists from the Shanghai Astronomical Observatory of the Chinese Academy of Sciences in collaboration with international partners. The team analyzed data obtained in 2018 using the Event Horizon Telescope (EHT) and the Global Millimeter VLBI array, studying the supermassive black hole M87.
By combining images taken at wavelengths of 1.3 millimeters and 3.5 millimeters, the researchers performed the first two-frequency spectral analysis at the event horizon scale. The resulting map of the black hole's spectral index allows for a description of how the radiation brightness changes at different frequencies, which scientists compared to a high-precision 'health check' of the black hole.
The results obtained demonstrate significant changes in the properties of radiation around the black hole depending on the distance from its center. Near the event horizon, the spectral index is positive, indicating a strong influence of synchrotron self-absorption on the radiation. However, further from the center, the spectral index gradually decreases and becomes negative, suggesting a transition of the radiation into an optically thin state.
This transition occurs at approximately 30 microarcseconds from the center of the black hole, corresponding to the size of the ring structure observed at the 3.5 millimeter wavelength. This discovery suggests that this ring is not only a visible feature of the black hole image but also reflects the state of the plasma near the event horizon.
The researchers note that future observations at additional frequencies will allow for more precise measurements of the plasma conditions around black holes. This will help track the evolution of accretion flows and jets over time, advancing the study of black holes from static imaging to dynamic physical diagnostics.
A study conducted by CGTN raises fundamental questions about humanity's role as machines begin to acquire cognitive abilities. The authors note that every technological revolution has always been accompanied by both the expansion of human capabilities and a re-evaluation of the very essence of humanity, but artificial intelligence represents a deeper shift.
AI is no longer just recording what happens; it is beginning to predict the future. It goes beyond merely interpreting the existing world, gradually building a hierarchy of possible scenarios before their realization. Thus, prediction transforms from a description of a potential future into an active force shaping subsequent events.
The central question that artificial intelligence poses to us is not whether machines can think like humans, but rather what authority their judgments are beginning to acquire. Questions arise about who grants this authority, who is responsible for it, and what future this will create for all of humanity.
At the World Conference on Artificial Intelligence and the high-level meeting on global AI governance in China, a concept for AI regulation was presented, which calls for maintaining a human-centric approach. The goal is for AI to serve as a powerful engine for common prosperity and collective security, contributing to the construction of a fair and equitable global AI governance system.
This vision aims to eliminate not only the gap in technological capabilities but also the growing divergence between the speed of technological progress and the pace of achieving consensus on governance. Since technological advancements outpace the formation of rules, power may emerge before appropriate norms are established. Therefore, AI governance is not just about managing risks, but also about finding a balance between innovation and rule-based order.
A global online survey by CGTN showed that 85.4% of respondents believe that the rapid development of AI generates new challenges for global security and governance. Furthermore, 92.6% expressed concern that deepfakes and AI-generated disinformation could undermine the foundations of social trust, while 87.8% worry that technological barriers and 'digital walls' could lead to the fragmentation of international scientific and technological cooperation.
These data indicate that issues related to AI have long gone beyond purely technological spheres. Strengthening global governance and forming broad international consensus have become shared tasks in the age of artificial intelligence. The survey also revealed that 82.6% of participants believe that developing countries and the Global South should play a more significant role in defining AI governance rules to ensure fairness and inclusivity of the system. Moreover, 87.5% hope that the international community will work to promote accessible and comprehensive AI, preventing technology from becoming a new source of inequality.
These results reflect not only general public expectations regarding AI governance but also a growing international consensus that the future of AI should be determined by openness and cooperation, rather than technological monopolies, and by inclusivity and common benefits, rather than regulatory restrictions. A civilization that can be understood, generalized, and interpreted exclusively through the models of another's AI has not yet reached a true era of intelligence. A truly fair global AI governance system must respect the diverse trajectories of development and the value systems of different countries and cultures, guaranteeing every civilization the right to understand the world through its own conceptual framework, to train intelligent systems on its own terms, and to appropriately shape the future of AI.
The values and ways of thinking inherent in different civilizations are not 'noise' that algorithms should eliminate, but indispensable sources of wisdom necessary for humanity to navigate an uncertain future. The goal of global AI governance is not to create a single 'correct' model of the world, but to ensure that no single understanding of the world becomes dominant. Governance is not the enemy of innovation; it is the second creation of innovation. The first occurs in the laboratory, where machines gain capabilities; the second is realized through institutions, ethical norms, and international cooperation, where technologies are endowed with purpose, boundaries, and responsibility. Intelligence without governance is merely force. However, intelligence shaped by shared values allows technology to become a genuine force for the benefit of all humanity.
In the age of artificial intelligence, AI governance concerns more than just common prosperity and collective security; it concerns our collective ability to shape the future. A truly just AI order must do more than just ensure the distribution of benefits from technological progress among all. It must also guarantee that every country and every civilization has a voice in setting the rules and determining the direction of AI's future. The future should not be a pre-determined model generated by a system, but an unfinished draft written collectively by humanity, remaining open to revision by all parties. The fact that machines have begun to think marks a milestone in technological history, and humanity's ability to jointly bear responsibility and maintain freedom of choice is a sign of civilizational progress.
