IBM doubles transistor density through vertical stacking at 0.7 nanometers and expects up to 70 percent energy savings — production readiness in approximately five years.
Giotto.ai and KPS combine AI technology with SAP integration to offer enterprises AI infrastructure that can be operated without external cloud providers.
OpenAI has completed its first in-house developed chip, Jalapeno, designed for its AI models to directly address hardware requirements and increase efficiency.
Data sovereignty and AI performance can be reconciled through hybrid infrastructures with GPU-as-a-Service and local data processing, but require elevated cybersecurity standards.
Google invests billions in TPU chip production and data center financing to threaten Nvidia’s 90 percent AI market share, copying Nvidia’s proven infrastructure lock-in strategy in the process.
56 percent of companies operate or plan productive AI inference in private cloud, while public cloud usage declined by 15 percentage points globally; Germany saw a more pronounced drop of 24 percentage points.
Companies must build their own AI expertise and learning loops rather than simply purchasing external models to remain independent and competitive in the long term.
European infrastructure providers like eww ITandTEL are positioning themselves as alternatives to US hyperscalers, enabling companies to build hybrid-flexible AI infrastructure with local data sovereignty.
Germany currently has only just under three gigawatts of data centre capacity, with 500 megawatts for AI, but must expand to up to six gigawatts—delays caused by local resistance jeopardize global competitiveness.
The EU is developing a sovereignty package to achieve technological independence in critical infrastructure and AI systems amid shifting geopolitical dynamics.
Bull and Foxconn are establishing European manufacturing capacity for AI and cloud infrastructure in Czechia and France to strengthen technological sovereignty and supply chain independence.
