The brute power of quantum computers could soon demolish the strongest cyber security. Alongside the US, China is at the forefront of this technology, says Michael Kollo of Axa Investment Managers.
At a recent client meeting in London, I found myself in a curious debate about artificial intelligence (AI) and the future of machines in decision-making. We were debating the pros and cons of neural networks when the conversation turned suddenly to processing power and model-less applications of computing.
A recent experiment at the Imperial War Museum in London by Enigma Pattern demonstrated how a simple algorithm could break the famed Enigma code of World War Two. In the experiment, Enigma was broken in less than 14 minutes, largely because of the application of parallel computing: 1,000 servers were used to test 13 million password combinations a second, and a simple language recognition algorithm was used to test if the decoded output was, in fact, German. In total, 15.4 billion combinations were tested, evaluated (for German), at a grand cost of $7 for the rental of the parallel servers. There were no AIs in sight, no sophisticated pattern recognition: this was a phenomenal demonstration of the awesome power of sheer ‘brute force’ search.
‘Brute force’ search is the act of searching through vast permutations (15 billion in this case) of possibilities to solve a problem or a code, testing and re-testing every possible permutation again and again and again. There is little finesse or elegance in this method, just an enormous tidal force of raw computing power. Consider an analogy of learning to fly an aircraft. A learning algorithm would try to understand the difference between the switches and controls, turning them on and off, all the while trying to identify a system by which it could fly the plane. A brute force algorithm would try every single possible permutation of each control with every other control, until (billions of attempts later) it takes off.
This is an untenable solution unless you have incredible amounts of computing power at your disposal (or infinite time in which to solve the problem). And for many current problems, the computing power required doesn’t exist, yet. For example, brute force is currently not powerful enough to win at a game like ‘GO’, as the permutations of moves are beyond those of our processors today. A system was built that could estimate incremental probabilities of each move that would, eventually, lead it to victory, but, importantly, that system had to rely on a model that would estimate probabilistic moves to beat the best human players in the world because it was unable to map out every possible permutation of the game.
A machine hulk
However, raw processing speeds are about to get a serious boost with quantum computing looming on the horizon. Quantum computers are still very early in their development but are widely expected to overtake conventional computers in processing speed, dramatically named ‘quantum supremacy’. And ‘quantum supremacy’ has quickly translated into ‘political supremacy’; the world’s superpowers, the US and China, are both pouring enormous resources into this area.
On the US side, Intel and IBM recently announced that they have functioning 49 and 50-qubit (quantum bit) processors1, while Google has also been building its own quantum computer. China is slated to open the National Laboratory for Quantum Information Sciences in 2020, a $10 billion investment. In the meantime, it is developing the principles behind quantum computing, using it to build networks and to strengthen cyber-defence capabilities, including building a quantum-based network in Jinan to defend (and make unhackable) the communication streams between Shanghai and Beijing. The two systems look at AI and quantum computing through a political lens: for the US it is capitalism and corporate earnings, and for China it is a state directive for the nation.
For the average bystander, the promise of quantum computers is a little like a ‘Machine Hulk’, to put it into superhero terminology. It is raw, unadulterated processing power, the like of which we have never seen.
The advent of quantum supremacy has a number of major implications both for AI and the world at large. Just as parallel computing cracked the Enigma code like an egg, so quantum computing will have enough juice to break through just about any present-day security system using terrifying brute force, with little reliance on elegance or a model. This will mean security systems themselves will need to become more complex to keep up.
It also has a bearing on the future of AI because many of today’s accomplishments are, in large part, due to sophisticated models like neural networks that, while flexible, still try to understand their problems using a modelling framework.
Both supervised neural networks and unsupervised deep-learning networks follow a basic model, a structure for estimation, that has parameters, inputs and ‘toggles’ that allow the researcher to shape the architecture of the model. With the advent of quantum computing, many doors that, until now, have only been able to be opened by elegant deep learning algorithms, will be smashed in by the ‘Machine Hulk’.
Sheer brute force
The world has become increasingly fixated on deep learning as a great methodology, but it is still only one methodology, one class of model.
An analogy is perhaps when we teach ourselves to draw a face, first by starting with the outline, then filling in detail. This is a method or a ‘model’ of drawing, and we improve our skill by going through the components, section by section.
The ‘brute force’ equivalent is to draw every face imaginable until one makes sense. While it may not sound like the best way to draw, it does work on many smaller problems. It is easy to imagine, for example, standing at your front door, late at night, trying every key on your keychain until one works.
The model-less application of computing power is a big deal, and will probably be much more critical in the future. One easy application is cyber security, where cryptography is all about large permutations, and search algorithms. But even for AI and ‘learning’ algorithms, vast amounts of data are required to teach algorithms to recognise speech, consumption patterns, and generally ‘understand’ the world. You have to take enormous amounts of data that you have to collect (it helps if you have more loose privacy policies) and interpret.
Complex problems that currently require finesse and delicate modelling will increasingly become broken through sheer brute force, through the power of silicon (or qubits) rather than neural nets. Enigma is an easy example of a puzzle that was simply overtaken by the rising tide of processing power, not by ingenuity in data modelling.
With quantum computing on the horizon, and taking centre stage in a power between two real-life ‘Hulk’ superpowers and machine learning, models generally may soon be subsumed by the sheer computing power that will flood the world.
Michael Kollo is chief quantitative strategist for Rosenberg Equities at Axa Investment Managers
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