The journey of high technology into everyday life is the transition from an idea and its development to devices, services and solutions people can use every day. High-tech news helps us see which innovations are nearing this stage and how they might change familiar activities.
A headline-grabbing announcement does not always mean a finished product is on the way: it is important to understand what has actually been created, who might benefit from it and how close it is to everyday use. For a broader picture, read our overview, “Digital Technology Today: How the Modern Digital World Works.”
| Example | Field | What has been confirmed |
|---|---|---|
| Latvia | Biomedicine, photonics, new materials, engineering | 26 technologies brought to market |
| Russian organizations | Artificial intelligence | 80,9% of the solutions used in 2023 were created in Russia or substantially modified by Russian developers |
| SNOLAB, Canada | Neutrinos, dark matter, low-background physics | Research support |
| Portugal | Graphene | Production of high-quality material mentioned |
- 26 technologies Latvian laboratory developments brought to market
- 80,9% Share of AI solutions used by organizations in 2023 that were created in Russia or significantly modified by Russian developers
- 2023 The period covered by the figure on Russian AI solutions
How does a laboratory development become a product?
A laboratory development becomes a product when it is assessed not only as a scientific result but also for its suitability for practical use, and is then brought to market. In Latvia, 26 technologies have made this journey, across fields including biomedicine, photonics, new materials and engineering.
From results to real-world use
For each of these 26 developments, reaching the market is a distinct stage that follows research. A laboratory result alone does not mean that a technology can be used in real-world conditions: its practical suitability and the possibility of bringing it to market both matter.
The fields represented in Latvia show that the journey from laboratory to product is not limited to a single industry: it spans biomedicine, photonics, materials and engineering solutions. For a broader look at the digital landscape, see our overview, “Digital Technology Today: How the Modern Digital World Works.”
Where are homegrown AI technologies already being used?
Organizations in Russia are already using homegrown AI technologies. According to the Institute for Statistical Studies and Economics of Knowledge at HSE University, 80,9% of the solutions used by organizations in 2023 were created in Russia or significantly modified by Russian developers. This figure describes the solutions organizations used during a specific period; it is not an assessment of every product on the market or a figure for 2026.
What counts as a homegrown development?
When assessing adoption, it is important to distinguish between two cases: a solution was originally developed in Russia, or Russian developers substantially modified an existing technology. The second case does not necessarily mean the technology was developed entirely in-house, but the modification must be significant. The 80,9% figure covers both categories.
HSE University materials also note an increase in organizations’ use of AI technologies they develop themselves. This points to the adoption of both ready-made solutions and in-house developments; however, the information provided does not specify which industries or organizations have seen the most notable growth. The 2023 figure should therefore be treated as a snapshot of practices at the time, not applied to today’s market without newer data.
What fields do Sber’s laboratories research?
Sber’s laboratories research artificial intelligence, blockchain, cybersecurity, neuroscience, the Internet of Things, quantum technologies and experimental machine-learning systems. The names of the units identify specific fields, while machine-learning research is overseen by a department that links method development with testing.
- Artificial intelligence and blockchain: the Center for Practical Artificial Intelligence and the Blockchain Development Center.
- Security and people: the Cybersecurity Laboratory and the Neuroscience and Human Behavior Laboratory.
- The Internet of Things and quantum technologies: the Internet of Things Laboratory and the Center for Quantum Technologies.
- Machine learning: the Department of Experimental Machine-Learning Systems connects method development with experimental testing.
From development to testing
The list shows that Sber’s research covers both specific technologies—blockchain, the Internet of Things and quantum solutions—and fields related to security and human behavior. The Department of Experimental Machine-Learning Systems has a distinct role: testing methods on experimental systems rather than focusing on development alone.
Why do fundamental research projects need specialized laboratories?
Specialized laboratories help fundamental research by creating conditions that make it easier for scientists to distinguish weak signals from interference. This is essential in low-background physics: when a signal is difficult to pick out from background noise, it is more reliably studied in a specially designed environment.
SNOLAB in Canada supports research into neutrinos, dark matter and low-background physics. These fields show why scientific work needs a laboratory designed to detect elusive signals, rather than just an ordinary space for experiments.
Science does not always lead directly to the market
SNOLAB illustrates a different way scientific knowledge is put to use: fundamental research does not have to turn immediately into a commercial product. Its purpose may be to expand our understanding of neutrinos and dark matter, even if no product or service emerges directly from it. Mentioning SNOLAB in the context of Italy does not mean the laboratory is located there: the supplied materials identify it as Canadian.
Why don’t new materials and AI reach users quickly?
New materials and algorithms take time to reach users because a laboratory result still needs to be adapted for manufacturing and real-world use. The research itself does not prove that a development is already being mass-produced or solves a practical problem.
High-quality graphene production in Portugal is a concrete example of work with a new material, but the available information does not specify production volumes, prices or the industry in which it is used. The fact that it is being produced is therefore not enough to determine how widely it has been adopted or whether it is available to buyers.
What the figures say about adoption
The 80,9% figure refers to the makeup of the AI solutions used by Russian organizations in 2023: they were developed in Russia or significantly modified by Russian developers. This share describes where the solutions originated, not their accuracy, usefulness or impact on users.
In Latvia, 26 technologies in biomedicine, photonics, new materials and engineering have reached the market. These 26 examples confirm that developments have made it out of the laboratory, but do not justify treating every project in those fields as a commercial product: readiness should be judged by actual use and production, not simply by belonging to a promising field.
How can you tell news about a development from news about its adoption?
Look at the stage described: research and prototypes do not yet mean a product is being manufactured or has reached the market. Check exactly what is being described and where it is happening. For example, SNOLAB is in Canada and is associated with research into neutrinos and dark matter, while Sber’s laboratories work in quantum technologies and artificial intelligence. A laboratory’s mention alone does not confirm that the technology it developed is already available to users.
What to check in a report
- Stage. “Researching” and “developed a prototype” describe work before adoption; references to production or sales indicate a later stage. Check whether a specific product is named and who is using it.
- Organization and location. Find out who is doing the work: the examples include SNOLAB in Canada, Sber’s laboratories and developments in Latvia. For Latvian technologies, the materials state that 26 developments reached the market; this is an example of commercialization, not just research.
- Statistical period. The 80,9% figure concerns AI solutions used in 2023: systems created in Russia or significantly modified by Russian developers. Do not apply this figure to other years or all technologies.
Graphene, quantum technologies and robotics do not, by themselves, prove commercial use. Without a named product, user or adoption stage, it is more accurate to treat such a report as news about research or development—not about a technology that has already become part of everyday life.
Frequently asked questions
How many laboratory technologies has Latvia brought to market?
What share of AI solutions used by Russian organizations are homegrown?
What does SNOLAB do?
What technologies do Sber’s laboratories work on?
Key takeaways
- In Latvia, 26 laboratory technologies have reached the market.
- Of the AI solutions used by organizations in 2023, 80,9% were Russian-developed or significantly modified by Russian developers.
- SNOLAB in Canada supports research into neutrinos, dark matter and low-background physics.
- Sber’s laboratories cover AI, blockchain, cybersecurity, neuroscience, the Internet of Things and quantum technologies.
Sources
- INNOVANDO NEWS — “International Journal of Innovation”
- euronews — “Technology News | Next”
- issek.hse.ru — “Artificial Intelligence Technologies for Manufacturing: Development and Use — News — Institute for Statistical Studies and Economics of Knowledge — National”
- list provided — “From Lithium Mining to Quantum Medicines”
