At ExoBrain we’re obsessed with helping companies unlock the power of AI, but in many ways that really means helping them unlock the power of ‘compute’. As we’ve discussed before, it’s been the driving force behind every wave of technology progress in our lifetimes, and it’s cost, accessibility and geo-political distribution may decide our future.
For thousands of years analogue computers, such as the fascinating Antikythera mechanism, helped us unlock the concepts of time and the motion of the planets. Since Alan Turing and the cracking of the Enigma code, digital computers have dominated, but this week some news emerged from Microsoft and hardware vendor Quantinuum that suggests the next era is nearing. They announced a breakthrough in the reliability of quantum computing, reducing the error rates of their virtual or ‘logical’ qubits, the building block of the quantum computer. Previous research suggested that such error-correction strategies could require thousands of expensive physical qubits per logical qubit. Microsoft’s research indicates we may need 100x less. Notable progress is also being made on single atom qubits, these replace superconductors which need to be cooled to a rather chilly -237C.
Quantum computing (QC) is not new, but has been held back by very low reliability, and the super expensive and impractical nature of the hardware. These 2024 developments suggest things are about to change, and over the next few years as we see digital computing skyrocket with Nvidia’s Blackwell, we’re also likely to see quantum computing become widely available.
But if you’re reading this you’re thinking, what does this mean for AI? Firstly, there is an interesting flywheel developing between the use of AI to accelerate the design and development of QC, and the strengths of the quantum paradigm in AI. QC research is inspiring novel AI architectures, and as the cost of QC reduces, it can start to super charge scientific discovery, new algorithms, data and memory capacities, massive parallelism etc. But we should be aware that whilst there is a clear playbook for scaling digital AI over the next few years, there is no equivalent vision for quantum AI. Its cost and complexity to-date has limited exploration, and the engineering and research ecosystem is under-developed. But this week’s news is likely to spur development. We expect to see hybrid classical plus quantum approaches emerging in the next few years. By the end of the decade this marriage will allow AI systems to exploit digital computing for the areas in which it excels such as data processing, control flow, user experiences, and integrating with older software, and will leverage quantum strengths for the messy chaotic real-world; complex algorithms, simulations, and higher dimensional data.
Naturally there’s a flip side. A recent update for Apple’s iMessage on your iPhone for example introduced highly advanced ‘post quantum cryptography’. QC capabilities that go beyond the hundreds (of error free) qubits we see today into the thousands and millions, likely around the end of the decade, will break most current encryption standards with ease. State actors are already harvesting data with a steal-now, decrypt later mindset. The information integrity and cyber security landscapes face extreme threats from both AI and QC.
Takeaways: On a practical note and for those managing tech the next steps in preparing for post-quantum cryptography is important reading. And whilst we’re preparing for the worst, we can be exploring the hoped for tools and techniques of the future. You can get started with quantum computing and create and run quantum programs with the help of the Copilot in Azure Quantum on the Azure Quantum website. Whilst this is still just emulation, its a great chance to get to grips with QC and understand what new potential it unlocks.