QunaSys: Simply 'Leaving It to AI' Won't Transform R&DA · FULL TRANSLATION
- Quantum-computing startup QunaSys offers a view on AI and R&D
- It argues that merely 'handing work to AI' cannot truly change research and development
- It stresses combining human expertise with AI effectively
- It flags a common myth about adopting AI in R&D
- It reflects the tech sector's rethink of pragmatic AI use
Amid 'AI can do anything' hype, a deep-tech startup saying 'just handing it to AI won't change R&D' is a coolness worth noting. R&D's core, asking the right questions, designing experiments, interpreting results, still depends heavily on human domain knowledge and judgment; AI is a powerful accelerator, not a black box that auto-produces insight.
It punctures a common myth: that buying tools and feeding data makes innovation happen automatically. Without clear problem definition and experts in the loop, AI just produces 'plausible' but useless results faster. For research-intensive fields like pharma, materials and chemistry, human-AI collaboration is the real productivity source. As firms rush to 'go AI,' are we solving problems, or manufacturing the illusion of busyness?
Quantum-computing startup QunaSys has offered a thought-provoking view on using AI in research and development: simply 'handing work to AI' cannot truly transform R&D.
The company stresses that the essence of R&D lies in asking the right questions, designing experiments and interpreting results, all of which still depend heavily on human expertise and judgment. While AI can be a powerful accelerator, without clear problem definition and the involvement of experts it cannot genuinely improve the quality and outcomes of R&D.
QunaSys argues that real change comes from human-AI collaboration that effectively combines human expertise with AI's capabilities, rather than entrusting R&D entirely to AI.