Tech Startups Germany – Startups and Venture Capital by Startuprad.io™

There are genuine non-obvious claims—particularly around cost reduction economics, the algorithm-discovery bottleneck preceding hardware utility, and the data-loading breakthrough—but they are buried in lengthy analogical explanations and broadly optimistic framing that adds little for a smart operator.

“running something on these largest machines could cost you easily tens to hundred thousand dollars if you want to get truly interesting new results. With the help of technologies like ours, we can reduce this cost to tens of dollars or up to hundreds of dollars”

“one of the breakthroughs that we did at Haiku was particularly unlocking this capability of loading large scale data sets, which are of the industrial scale number of features into quantum computers”

The CUDA/BASIC-for-quantum framing is the episode's sharpest original move, and the argument that algorithm-discovery lag—not hardware lag—is the real enterprise risk is underappreciated; however, the rest tracks the standard quantum-hype-cycle narrative that circulates widely.

“right now I would say there is no CUDA or no BASIC for quantum computers. It's still very hard to program them. You literally work on the quantum assembly level”

“Imagine that your competitor already did it today. And then in the year from now, quantum computers suddenly start to showcase value. So you still will need to take few years in order to build, test, integrate the workflow in your organization. So you will be already losing.”

Mykola is a genuine deep-tech practitioner—theoretical physics training at elite institutions, industrial R&D leadership, and now CTO of a funded company with named enterprise clients; he speaks from first-hand execution experience rather than thought-leadership positioning, though his answers occasionally drift toward polished investor narrative.

“I used to work, for example, on some of the largest supercomputing centers in Germany. And those simulations cost a lot. They can cost easily like $200,000”

“we can reduce this cost to tens of dollars or up to hundreds of dollars. Such that we dramatically democratize the level of accessibility of these technologies”

A handful of concrete numbers appear—$50,000/hour quantum machine time, $200,000 supercomputer simulation costs, 10-100x cost reduction, 4-to-10 qubit experiments two years ago versus hundreds now—but the methodology behind them is never challenged, and most claims about enterprise timelines and application domains stay at an abstract level.

“one hour of execution on the quantum computer can cost up to $50,000 or even more”

“those simulations cost a lot. They can cost easily like $200,000. And you can run those simulations sometimes for weeks in order to get some reasonable result”

The host has clearly prepared and frames some questions with genuine editorial sharpness (noise vs. qubit count, middleware as responsibility boundary), but he consistently allows expansive non-answers to pass unchallenged and introduces off-topic tangents—energy/data centers, COBOL/Claude—that dilute momentum rather than deepen it.

“For founders watching quantum from the outside, noise, not qubit count, is the real reason most pilots fail quietly. What actually happens inside these systems that makes noise such a dominant constraint?”

“Out of curiosity, you've been talking about that quantum computing can now deliver what high performance computing as state of the art computers can deliver right now. So I was wondering, if you extrapolate when quantum computing has its full capability, what could this mean?”