by Maurice E. Bakker BSc MBA – partner
In the race to build the future, speed, scale, and intelligence are everything. If you’re a startup founder, you already know that innovation moves fast — but what’s changing now is how it’s built. The game is no longer just about having a brilliant idea; it’s about having the computational firepower to bring that idea to life faster, smarter, and bigger than the competition.
This is where the convergence of High-Performance Computing (HPC) and Artificial Intelligence (AI) becomes a make-or-break factor for new businesses. Startups that embrace this duo are creating breakthroughs in medicine, climate tech, materials science, autonomous vehicles, fintech, and more. Startups that don’t? They’re either moving too slow — or solving the wrong problems.
And if that’s not enough, consider this: quantum computing is just around the corner, and it will supercharge the power of HPC+AI even further. The window for ignoring these technologies is closing — fast.
In this blog, we will explore what HPC and AI actually are (and why they matter together), we will briefly showcase real-world startup use cases across industries, we will touch on how quantum computing will reshape the horizon, and we will state why every founder needs to think like a tech founder — no matter the industry.
High-Performance Computing (HPC) refers to the use of powerful computing systems that can process massive amounts of data at high speed. Think thousands of processors running in parallel — doing in minutes what might take days (or years) on a regular computer. Artificial Intelligence (AI), in turn, is the ability of machines to learn from data and make decisions. AI enables automation, predictions, personalization, pattern recognition, and more.
Individually, these are powerful technologies. But together? Well, HPC provides the raw muscle to train large-scale AI models — like deep learning neural networks — quickly and efficiently. And AI helps interpret the complex results that HPC simulations produce, turning raw data into actionable insights. HPC is needed to accelerate AI experimentation and iteration, whereas AI enables HPC-powered simulations to “learn” from past runs and optimize themselves.
This isn’t just about technology for technology’s sake — it’s about building products and solving problems that were previously impossible, impractical, or too expensive. Here are some great examples to inspire you – food for thought.
Drug Discovery – speeding up science: biotech startups like Recursion Pharmaceuticals and Insitro use AI + HPC to simulate millions of biological interactions and chemical compounds. Instead of running physical experiments for years, they can now identify promising drug candidates in weeks.
Climate and energy – modeling the planet: climate-focused startups like Cervest and Carbon Re use HPC to simulate extreme weather, emissions, and infrastructure stress scenarios. AI models then predict long-term impacts and provide actionable insights.
Fintech – beyond algorithms: fintech startups use AI to power trading algorithms, fraud detection, credit scoring, and risk management. HPC allows those AI models to train fast and scale across millions of transactions per second.
Materials science & manufacturing – designing the future: startups like Citrine Informatics are using AI + HPC to discover new materials for semiconductors, batteries, or construction. They simulate atomic-level behaviors and optimize for sustainability, cost, or performance.
Mobility and smart infrastructure: autonomous vehicle startups, drone-based logistics, and smart city applications rely on AI models trained on massive datasets. HPC accelerates training of perception, navigation, and control models.
Still think that you don’t need HPC and AI? Think again! Too many startups still treat HPC and AI as “nice-to-haves” or something for tech giants only. But cloud-based platforms have changed the game — HPC is no longer locked behind academic labs or billion-dollar budgets. Our prediction at Polaris Enterprises, is that 2025 is the defining year, the year of the Great Chasm. The year in which those that do not embrace HPC and AI, will wither. Today, any startup with the right mindset can access a scalable HPC infrastructure from global players like AWS, Google Cloud, and Microsoft Azure. European-based platforms like Scaleway, OVHcloud, and Cloud&Heat offer high-performance, GDPR-compliant cloud solutions for startups. Access to EuroHPC supercomputers through initiatives like LUMI (Finland), Leonardo (Italy), or Luxprovide (Luxemburg) which support research, startups, and SMEs across Europe, has never been easier. Pay-as-you-go pricing to scale with growth, is the emerging model. Open-source AI frameworks (like PyTorch and Hugging Face) and developer tools that abstract away complexity, make startup life easier than ever before.
In other words: you don’t need to be a deep tech company to leverage deep tech. The startups that win are the ones who act early — while their competitors are still “waiting to explore” these technologies.
So what comes after HPC? Just when you thought the compute ceiling was far away — here comes quantum computing. Whilst still in its early days, quantum promises to exponentially expand the capabilities of HPC. Some startups are already prototyping quantum-assisted AI and simulation models, particularly in Chemical and Molecular Modeling, Optimization and Logistics, Cryptography and Cybersecurity, and Financial Portfolio Optimization. Companies like Zapata Computing and Rigetti are building platforms that combine classical HPC with early quantum hardware — preparing for what’s next.
The 2025 Great Chasm revolves around getting from Idea to Infrastructure. Startups no longer win by just being creative — they win by being computationally intelligent. That means, founders need to think in terms of data pipelines and simulation loops, not just features and MVPs. Startups need to invest early in technical partnerships that support HPC and AI needs. Founders need to build teams who understand model training, data engineering, and computational scaling. Finally, investors and founders need to stop seeing infrastructure as costs, it is not – it is a competitive advantage.
So innovation is no longer about hacking your way through. It’s about training, testing, and deploying faster than the rest. The future is computed. If you’re a startup founder, here’s the bottom line. You can no longer afford to not understand what HPC and AI can do for your business. You don’t need to build it all yourself — but you do need to build on it. The future of innovation is powered by intelligence + infrastructure.
Founders who recognize this early — and take action — will define the next generation of business. The rest will simply be computed… by someone or something else.