The following interview was conducted as part of The Recursive’s “State of AI in CEE” report. Download the full report with insights from over 40 experts and analysis of 900 CEE AI product companies here.
As an ecosystem builder in Hungary, Csongor Bias led co-working spaces and incubation programs, numerous startup organizations, and owned a software agency that also worked closely with startups in the country.
Today, as Managing Director of Startup Hungary, Bias actively contributes to the overall development of the Hungarian startup ecosystem.
In an interview for The Recursive, Bias discusses the country’s AI industry potential and the different verticals in which Hungarian AI startups and companies excel.
The Recursive: What are currently some of your most notable companies in the field of AI in Hungary and why?
Csongor bias: Hungary was pretty strong in AI even before it became cool. We had strong businesses before the recent AI hype fueled by ChatGPT. I’m mainly talking about some of the deep tech startups that we have, like aiMotive, which was actually acquired earlier this year by Stellantis for 250 to 300 million, which was one of the most successful acquisitions. most important in Hungary. , and they are in the autonomous vehicle industry.
Next up is Turbine, which uses machine learning for drug discovery in biotechnology. Even SEON uses many machine learning and AI algorithms.
I think Hungarian startups were taking advantage of the strong STEM education and talent pool of NLP and machine learning experts. I think we have a pretty strong pool of data scientists, and certainly a strong pool of communities. You know, it’s not a coincidence that big companies like Cloudera are also headquartered here, so I think Hungary definitely has this kind of advantage in the AI era and has the capacity to produce cool stuff.
What are the biggest challenges Hungarian organizations face when developing and using AI products?
I think these are the same problems, not only in Hungary, but almost everywhere. Europe has this dependence on big tech again – I just read a report saying that 70% of AI models are developed in the US, 13-14% in China, and that the level of AI base appears to be dominated outside the country. the European continent.
That said, I think there are still plenty of opportunities to create value at the application level and there are certainly some interesting companies popping up across the region and across Europe.
I certainly believe we have the talent pool to ride this wave. I’m not sure how big the problem is with developing large modules externally, but I nevertheless think that Hungary and Central and Eastern Europe are in a good position, due to the deep technical knowledge that will be available to them. local talent.
How do Hungarian educational institutions and universities contribute to the talent pool of AI professionals?
At a fundamental level, we have a history of training great mathematicians, the basics of fundamental computer science, etc. Hungary, Poland and other V4 countries have performed very well in the Mathematics and Programming Olympics, as well as in different competitions where very deep algorithmic skills and in-depth analytical knowledge are required. So I think the fundamental level is there.
I think that due to bureaucracy and old-school systems, universities can struggle to keep up with the latest knowledge. However, the Internet has somehow democratized the possibility for everyone to learn on their own, so we will have the necessary foundations to build solidly. I think we’re in a good position for the local talent pool to be at the forefront of innovation, but universities definitely need to catch up and try to be at the forefront of innovation.
How would you describe the current AI investment landscape in CEE? How would you compare this landscape to that of Western Europe?
Many companies in Hungary struggle to raise their Series A or B rounds, even when they have good metrics and numbers. Recently we had Colossyan, one of the other emerging GenAI synthetic video spaces, raised from Bulgarian investors and the space they operate in is pretty hot. On the other hand, other companies also have good indicators and benchmarks, and these could have more difficulties. So I think investor interest in AI is also present in Hungary and the region.
How has the landscape of the AI industry in Hungary evolved over the past few years? What types of AI technologies or applications do you see as most promising for development in the near future?
Hungary is definitely strong in the areas of autonomous vehicles and driving, everything related to visual recognition, as well as everything in the middle of various industries like biotechnology, for example between that and learning automatic. I think we have a good track record of having good companies in these sectors.
And certainly, in the application layer of AI companies, some of the best SaaS companies like SEON have rapidly adopted and introduced AI-based features into their product set and are taking advantage of these new models and opportunities.
In your opinion, what impact will the next European AI regulatory framework have on the adoption of AI products and services?
Awareness of this topic is very low – we’ve created several surveys and most people either haven’t heard of it or have just heard of it but haven’t really looked into what it might entail. And I really think that the EU should be very careful and talk with industry players and try not to create regulation that would increase the gap that we already have as a continent compared to the United States and China.
The AI law has also been heavily criticized for its lack of clarity, particularly on which particularly important sectors need to be regulated. In the last form I saw, the biggest concern was that it was too broad, that there were no limits when it came to strategically important industries and that it could undoubtedly slow down innovation.
How would you rate cooperation and networking with other stakeholders to advance AI technology in Hungary or the CEE region?
To be honest, the most notable startups in Hungary, not only in the field of AI, but also in AI, ignore the local market and try to go global from day one. So I don’t see many efforts of this type of collaboration. That said, for example, with the CEO of drug discovery startup Turbine, who is also one of the founders and board member, we started working on creating a deep biotech ecosystem. We therefore absolutely want to get in touch with decision-makers, universities, etc.
But from a market perspective and for running pilot projects and sandboxes, they focus more on the US and UK market and practically ignore the domestic market. And I think this is the right decision for them because they want to build a global business since Hungary is simply too small a market for them.
Which factors do you think will have the biggest impact on improving prospects for AI-based innovation in Hungary or CEE in general?
This is undoubtedly a long-term project: the government should absolutely increase the number of people working and studying STEM, and there is a continued need for more and more engineers. Therefore, popularize and multiply these training courses in higher education. And generally speaking, improving the state of education is the best investment that the government can make for this purpose.
Apart from that, we need to remove all kinds of regulatory barriers and try to be very careful and make sure that AI law doesn’t get in the way of innovation. I think Europe should not make the same mistake it made in trying to protect itself through bureaucracy and then regulation – but rather try to remove bureaucracy to lay the foundations that can put us at the forefront of innovations .
