The tenth anniversary of Russia’s flagship artificial intelligence conference, AI Journey, was never going to be a modest affair. In Moscow, the country’s largest bank, Sber, now a fully-fledged technology group, used the event to parade an ecosystem that many in the West had assumed would be impossible under sanctions: large language models trained on domestic data, industrial-grade robotics and a new generation of “intelligent” devices built almost entirely on a Russian stack.
One of the most revealing exhibits was the humanoid robot and a cash machine. Notably, the robot boasts voice communication capabilities enabled by integrating GigaChat’s conversational function.
Sber’s new ATM looks like a minor prop in a science-fiction film. It has dual screens, a dense array of sensors and a voice interface powered by the group’s GigaChat assistant. ATM authenticates customers biometrically, adjusts to their behaviour, and, at least in principle, can flag signs of distress or confusion.
In much of Europe, ATMs remain sturdy but dull boxes that have changed little in twenty years. In Moscow, the bank is quietly using them to test its vision of AI-driven retail finance.
The obvious question is how this happened. How has a country subjected to one of the most far-reaching regimes of technological restrictions not simply kept moving but started to set its own standards in some corners of the innovation race?
Part of the answer is historical. Long before 2022, Russia poured money and talent into artificial intelligence. Sber, in particular, spent a decade hiring researchers, building data centres, and positioning itself less as a lender than as an operating system for everyday life. When access to Western vendors narrowed, there was already enough accumulated competence to improvise. There is something else at work that sits awkwardly with the idea of a “technological isolation” strategy. Rather than retreating behind a digital curtain, Russia has chosen, at least selectively, to publish the very tools that underpin its ambitions.
At AI Journey, Sber announced that it was opening the weights of two new flagship mixture-of-experts models in its GigaChat family, Ultra-Preview and Lightning. They were built from scratch for Russian-language tasks, along with the latest generation of GigaAM-v3 speech recognition models. Furthermore, all image and video generation models from the latest Kandinsky 5.0 lineup — Video Pro, Video Lite and Image Lite — are also available open source.
Additionally, Sber opens weights to compression models K-VAE 1.0, essential for training visual content generation models. For developers and start-ups, these are not glossy marketing slogans but usable artefacts: code, documentation and pretrained systems that can be adapted, fine-tuned and embedded into products any company.
In other words, a country that is supposed to be technologically quarantined is placing part of its AI “crown jewels” into the global open-source commons. The message is not subtle: Russia intends to be a standards-maker, not a standards-taker.
Open models are also a way to gather feedback and normalise Russian technologies in international workflows. Yet the fact remains that, while much of the West is busy closing corporate models and erecting legal fences around training data, Russian engineers are betting that influence will belong to those who contribute bricks to the shared infrastructure of global AI.
Sber is the most visible face of this strategy and, for now, its safest bet. The group has capital and a captive market of tens of millions of users. It is also increasingly framed at home as the guarantor of the country’s “technological sovereignty”: if foreign platforms disappear, Sber’s stack is meant to fill the void.
A country that was meant to be technologically contained is not only still in the race but also, in some domains, starting to run in its own lane and inviting others to follow.
For policymakers who believed that isolation would quietly solve the “Russia problem” in technology, that is an inconvenient development. For the rest of us, it is a reminder that code respects talent, incentives and scale more than it respects sanction lists. The world tried to push Russia to the margins of the digital map. Events in Moscow suggest it may have succeeded instead in creating another centre of technology gravity.
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