I must confess to be an avid reader of almost everything that comes to my mailbox from the MIT Technology Review (when the availability of time permits it is really almost everything…). It really is a wonderful, credible and full of interesting technological and scientific subjects newsletter.
Well written, well researched, with links to research repositories such as Arxiv, where the free open source publication of research papers community usually decides to post their works from now and then – despite not being the only one with a reasonable reputation and quality -, MIT Technology Review is a must read place on the wide web for anyone with an interest in those subjects. Even if the wider audience is not very much in the know of all the technoloy and science that appears there, nonetheless the language is accessible without losing the proper standard for serious communication for an educated readership.
Today I stumbled across one such article that catch your attention and you just can’t stop digging through all that is written until the final word. It is as though your mind wanders joyfully in every word and paragraph and happily awaits for the next one, felling assured that it will be similar if not more joyfull still with the apprehension of new knowledge and detail that catches our best imagination. It is the tale of a fortunate partnership between the behemoth search engine company Google and a physicist that is an expert in the new field called Quantum Computing. John Martinis, a physicist from the University of California at Santa Barbara and Google joined together to foster development of a Quantum Computer that promises to be a breakthrough in computing speed for that computer of the future; this new coming wave of computing is based on the modern Physics field of Quantum Mechanics and its weird world of particles that live in superposition states – meaning that they are never in one fixed location but exist everywhere and in every instant, in ways that aren’t easy for common sense intuition to fully grasp.
But that weird behavior is the template for the possibility of building computations unimaginably faster than today’s standard, simply for the reason that the way information is stored and retrieved is several orders of magnitude more efficient.
I would like to leave some passages from the article and hope that everyone enjoy it and discover a new field of interest in technology, keeping in mind that yours will not be time wasted in some hyped new go nowhere soundbyte:
The theoretical underpinnings of quantum computing are well established. And physicists can build the basic units, known as qubits, out of which a quantum computer would be made. They can even operate qubits together in small groups. But they have not made a fully working, practical quantum computer.
Martinis is a towering figure in the field: his research group at the University of California, Santa Barbara, has demonstrated some of the most reliable qubits around and gotten them running some of the code a quantum computer would need to function. He was hired by Google in June 2014 after persuading the company that his team’s technology could mature rapidly with the right support. With his new Google lab up and running, Martinis guesses that he can demonstrate a small but useful quantum computer in two or three years. “We often say to each other that we’re in the process of giving birth to the quantum computer industry,” he says.
Google and quantum computing are a match made in algorithmic heaven. The company is often said to be defined by an insatiable hunger for data. But Google has a more pressing strategic addiction: to technology that extracts information from data, and even creates intelligence from it. The company was founded to commercialize an algorithm for ranking Web pages, and it built its financial foundations with systems that sell and target ads. More recently, Google has invested heavily in the development of AI software that can learn to understand language or images, perform basic reasoning, or steer a car through traffic—all things that remain tricky for conventional computers but should be a breeze for quantum ones. “Machine learning is a core, transformative way by which we’re rethinking how we’re doing everything,” Google’s CEO, Sundar Pichai, recently informed investors. Supporting that effort would be the first of many jobs for Martinis’s new quantum industry.
Then NASA summoned journalists to building N-258 at its Ames Research Center in Mountain View, California, which since 2013 has hosted a D-Wave computer bought by Google. There Hartmut Neven, who leads the Quantum Artificial Intelligence lab Google established to experiment with the D-Wave machine, unveiled the first real evidence that it can offer the power proponents of quantum computinghave promised. In a carefully designed test, the superconducting chip inside D-Wave’s computer—known as a quantum annealer—had performed 100 million times faster than a conventional processor.
And the topics of Machine Learning and Artificial Intelligence, that were already covered in this blog, appear to be also involved ( at the same time a goal of this is to further these same fields) as well to further aid in this effort in Quantum Computing, maximizing the chances that we’ll ever see the light of day for all of these efforts. The major IT companies engaged or hoping to engage in Quantum Computing are also keen on pursuing their own research agendas, but it seems Google may be well ahead, specially in the practical usefulness of the technology:
Google will be competing not only with whatever improvements D-Wave can make, but also with Microsoft and IBM, which have substantial quantum computing projects of their own (see “Microsoft’s Quantum Mechanics” and “IBM Shows Off a Quantum Computing Chip”). But those companies are focused on designs much further from becoming practically useful. Indeed, a rough internal time line for Google’s project estimates that Martinis’s group can make a quantum annealer with 100 qubits as soon as 2017. D-Wave’s latest chip already has 1,097 qubits, but Neven says a high-quality chip with fewer qubits will probably be useful for some tasks nonetheless. A quantum annealer can run only one particular algorithm, but it happens to be one well suited to the areas Google most cares about. The applications that could particularly benefit include pattern recognition and machine learning, says William Oliver, a senior staff member at MIT Lincoln Laboratory who has studied the potential of quantum computing.
A last breath (I recommend further, much further reading please):
John Martinis, 57, is the perfect person to wrestle a mind-bogglingly complex strand of quantum physics research into a new engineering discipline. Not only can he dive into the esoteric math, but he loves to build things. Operating even a single qubit is a puzzle assembled from deep quantum theory, solid-state physics, materials science, microfabrication, mechanical design, and conventional electronics. Martinis, who is tall with a loud, friendly voice, makes a point of personally mastering the theory and technical implementation of every piece. Giving a tour of his new lab at Google, he is as excited about the new soldering irons and machine tools in the conventional workshop area as he is about the more sophisticated equipment that chills chips and operates them. “To me it’s fun,” he says. “I’ve been able to do experiments no one else could do, because I could build my own electronics.”
Featured (John Martinis) and main photos: Google’s Quantum Dream Machine