🔥 Why advance Quantum Machine Learning before we have million-qubit fault-tolerant quantum computers? 🤔 I get asked this a lot. The answer is multi-faceted:
1️⃣ 𝐒𝐡𝐚𝐩𝐢𝐧𝐠 𝐭𝐡𝐞 𝐟𝐮𝐭𝐮𝐫𝐞 – Researching quantum ML now helps pinpoint which problems will benefit the most and steer quantum technology development in the right direction.
2️⃣ 𝐔𝐧𝐞𝐱𝐩𝐞𝐜𝐭𝐞𝐝 𝐛𝐫𝐞𝐚𝐤𝐭𝐡𝐫𝐨𝐮𝐠𝐡𝐬 – Progress in one area often spills over into others. Our work on harnessing quantum properties for ML unexpectedly led to new quantum techniques for preventing data poisoning attacks —already applicable today, even before large-scale quantum computers exist.
3️⃣ 𝐒𝐨𝐥𝐯𝐢𝐧𝐠 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐩𝐫𝐨𝐛𝐥𝐞𝐦 – Our secret source is to start solving the next problem assuming the current problem will be solved.
4️⃣ 𝐐𝐮𝐚𝐧𝐭𝐮𝐦’𝐬 ‘𝐆𝐏𝐓 𝐦𝐨𝐦𝐞𝐧𝐭’ 𝐦𝐚𝐲 𝐜𝐨𝐦𝐞 𝐬𝐨𝐨𝐧𝐞𝐫 𝐭𝐡𝐚𝐧 𝐞𝐱𝐩𝐞𝐜𝐭𝐞𝐝 – Remember when experts predicted powerful AI was decades away back in 2023? Then, boom! Breakthroughs can happen overnight—especially as AI accelerates quantum research. We’re already using AI to tackle hard quantum problems, and the results are promising. 🚀

👉 Check out CSIRO’s Data61 latest quantum ML breakthrough (led by Muhammad Usman) and my take on why this matters:
https://lnkd.in/gd5tvQGe

💬 “CSIRO’s breakthrough not only builds confidence in the benefits of quantum machine learning but also serves as a guidepost. By identifying key application performance metrics and challenges, our work helps shape the trajectory of hardware and software innovation, bringing us closer to real-world demonstrations using quantum,” – Dr. Zhu.