2017 was a huge year for technology. From DeepMind’s Alpha Go/Alpha Zero platform dominating the world’s best player in the world’s hardest game (and then subsequently beating the pants off the A.I. that achieved that feat) to the ascendancy of voice-based user interfaces, 2017 saw some major advancements sure to shape the course of humanity’s near future for years to come.
Technologies like machine learning, deep neural networks and artificial intelligence are already well on their way to commercial applications — some blue-chip companies, like IBM, have bet the farm on a SAAS (software as a service) approach to making A.I. available to the masses (theirs happens to go by the name ‘Watson‘… you’ve probably heard of it). Amazon and Google Home’s seamless integration into living rooms across the country, paired with Siri’s longtime familiarity to users, has taken voice assistants truly mainstream in a way we don’t expect to slow down any time soon. If anything, we predict this will accelerate as machine learning and natural language recognition and cognition speed up, become more refined and improve its accuracy as the year progresses.
This has certainly taken our business to new and exciting spaces, like building out enterprise-grade Alexa skills for the Echo platform, integrating Watson into commercial mobile software applications and tinkering with Apple’s new ARKit for a mobile, mixed-reality future.
When it comes to the technologies we’re watching in 2018, our number one might surprise you.
We realize how ground-breaking artificial intelligence, machine learning and deep neural networks are — we’ve built an entire business around harnessing the newest and most innovative technologies in the marketplace to build custom software solutions with impact. But the thing with voice assistants and deep neural networks and biometric security is that the growth arc is somewhat predictable at this point. Of course we can’t predict how these technologies will precisely fare into the future, but we have a pretty good idea of how artificial intelligence will make sense of immense amounts of data to provide actionable intel for humanity. We know natural speech recognition will continue to get better and with that, translation apps, better voice assistants and the like will pop up everywhere.
That’s why the top technology we’re tracking closely has a much less certain future. We don’t even know if it’ll actually come to fruition or even exactly how we’d use it when it does. But, because it has the most upside of any of these technologies, it’s what we’re most excited to track in 2018:
MIT Technology Review puts it 4-5 years out, but it’s still so exciting, MIT listed it as a top 10 breakthrough technology for 2018 anyway. Quoting the article, quantum computers could, in a few years, “rewrite encryption, materials science, pharmaceutical research, and artificial intelligence.”
That’s no small potatoes.
MIT says it has toyed with including practical quantum computing on that annual list for a while, but never pulled the trigger because the technology wasn’t quite feasible enough yet — that changed this year:
… A raft of previously theoretical designs are actually being built. Also new this year is the increased availability of corporate funding—from Google, IBM, Intel, and Microsoft, among others—for both research and the development of assorted technologies needed to actually build a working machine: microelectronics, complex circuits, and control software.
Quantum bits, or qubits, hold the key to truly exponential increases in computing power within ever smaller spaces. There’s just one problem — they’re both incredibly complex and incredibly fickle:
“For qubits to be useful, they must achieve both quantum superposition (a property something like being in two physical states simultaneously) and entanglement (a phenomenon where pairs of qubits are linked so that what happens to one can instantly affect the other, even when they’re physically separated). These delicate conditions are easily upset by the slightest disturbance, like vibrations or fluctuating electric fields.
As such, getting a working design to perform was always just out of reach because of those systemic delicacies. But researches the world over are starting to find success in making qubits that are far more stable than previously observed. And the ramifications of success on that front couldn’t be bigger:
“Quantum computers will be particularly suited to factoring large numbers (making it easy to crack many of today’s encryption techniques and probably providing uncrackable replacements), solving complex optimization problems, and executing machine-learning algorithms. And there will be applications nobody has yet envisioned.
The head of Google’s quantum computing efforts says they’ll have a 49 qubit machine up and running this year; that’s a massive milestone, because at around 50 qubits, quantum computers will surpass — for good — what today’s supercomputers can compute, due to physical limits of classic supercomputer systems.
Somewhere between 30 and 100 qubits—particularly qubits stable enough to perform a wide range of computations for longer durations—is where quantum computers start to have commercial value. And as soon as two to five years from now, such systems are likely to be for sale. Eventually, expect 100,000-qubit systems, which will disrupt the materials, chemistry, and drug industries by making accurate molecular-scale models possible for the discovery of new materials and drugs. And a million-physical-qubit system, whose general computing applications are still difficult to even fathom? It’s conceivable, says Neven [head of Google’s quantum computer efforts], “on the inside of 10 years.”
I don’t know that Google will actually achieve a 49-qubit system this year. Heck, I don’t even know if any practical quantum machine will turn out this year. That still didn’t deter me from choosing it as the technology I’m most excited to watch this year, because if someone gets it right, it will literally remake the digital world forever.
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