The European Union (EU) aims to embark on an ambitious common strategy on quantum technologies, European Commissioner for digital economy and society Gunther Oettinger said here Tuesday.
At a conference which brought together some of the world’s leading experts in the field of quantum technology, European scientists and entrepreneurs launched a “Quantum Manifesto” laying out future priorities and activities to create a new “knowledge-based industrial ecosystem” in Europe.
“We aim to launch an ambitious large-scale flagship initiative to unlock the full potential of quantum technologies, accelerate their development, and bring commercial products to public and private users,” Oettinger told the conference.
If you’ve ever seen a “recommended item” on eBay or Amazon that was just what you were looking for (or maybe didn’t know you were looking for), it’s likely the suggestion was powered by a recommendation engine. In a recent interview, Co-founder of machine learning startup Delvv, Inc., Raefer Gabriel, said these applications for recommendation engines and collaborative filtering algorithms are just the beginning of a powerful and broad-reaching technology.
Raefer Gabriel, Delvv, Inc.
Gabriel noted that content discovery on services like Netflix, Pandora, and Spotify are most familiar to people because of the way they seem to “speak” to one’s preferences in movies, games, and music. Their relatively narrow focus of entertainment is a common thread that has made them successful as constrained domains. The challenge lies in developing recommendation engines for unbounded domains, like the internet, where there is more or less unlimited information.
“Some of the more unbounded domains, like web content, have struggled a little bit more to make good use of the technology that’s out there. Because there is so much unbounded information, it is hard to represent well, and to match well with other kinds of things people are considering,” Gabriel said. “Most of the collaborative filtering algorithms are built around some kind of matrix factorization technique and they definitely tend to work better if you bound the domain.”
Of all the recommendation engines and collaborative filters on the web, Gabriel cites Amazon as the most ambitious. The eCommerce giant utilizes a number of strategies to make item-to-item recommendations, complementary purchases, user preferences, and more. The key to developing those recommendations is more about the value of the data that Amazon is able to feed into the algorithm initially, hence reaching a critical mass of data on user preferences, which makes it much easier to create recommendations for new users.
“In order to handle those fresh users coming into the system, you need to have some way of modeling what their interest may be based on that first click that you’re able to extract out of them,” Gabriel said. “I think that intersection point between data warehousing and machine learning problems is actually a pretty critical intersection point, because machine learning doesn’t do much without data. So, you definitely need good systems to collect the data, good systems to manage the flow of data, and then good systems to apply models that you’ve built.”
Beyond consumer-oriented uses, Gabriel has seen recommendation engines and collaborative filter systems used in a narrow scope for medical applications and in manufacturing. In healthcare for example, he cited recommendations based on treatment preferences, doctor specialties, and other relevant decision-based suggestions; however, anything you can transform into a “model of relationships between items and item preferences” can map directly onto some form of recommendation engine or collaborative filter.
One of the most important elements that has driven the development of recommendation engines and collaborative filtering algorithms is the Netflix Prize, Gabriel said. The competition, which offered a $1 million prize to anyone who could design an algorithm to improve upon the proprietary Netflix’s recommendation engine, allowed entrants to use pieces of the company’s own user data to develop a better algorithm. The competition spurred a great deal of interest in the potential applications of collaborative filtering and recommendation engines, he said.
In addition, relative ease of access to an abundant amount of cheap memory is another driving force behind the development of recommendation engines. An eCommerce company like Amazon with millions of items needs plenty of memory to store millions of different of pieces of item and correlation data while also storing user data in potentially large blocks.
“You have to think about a lot of matrix data in memory. And it’s a matrix, because you’re looking at relationships between items and other items and, obviously, the problems that get interesting are ones where you have lots and lots of different items,” Gabriel said. “All of the fitting and the data storage does need quite a bit of memory to work with. Cheap and plentiful memory has been very helpful in the development of these things at the commercial scale.”
Looking forward, Gabriel sees recommendation engines and collaborative filtering systems evolving more toward predictive analytics and getting a handle on the unbounded domain of the internet. While those efforts may ultimately be driven by the Google Now platform, he foresees a time when recommendation-driven data will merge with search data to provide search results before you even search for them.
“I think there will be a lot more going on at that intersection between the search and recommendation space over the next couple years. It’s sort of inevitable,” Gabriel said. “You can look ahead to what someone is going to be searching for next, and you can certainly help refine and tune into the right information with less effort.”
While “mind-reading” search engines may still seem a bit like science fiction at present, the capabilities are evolving at a rapid pace, with predictive analytics at the bow.
CoinFac Limited, a technology company, has recently introduced the next generation quantum computing technology into cryptocurrency mining, allowing current Bitcoin and Altcoin miners to enjoy a 4,000 times speed increase.
Quantum computing is being perceived as the next generation of supercomputers capable of processing dense digital information and generating multi-sequential algorithmic solutions 100,000 times faster than conventional computers. With each quantum computing server costing at an exorbitant price tag of $5 Million — $10 Million, this revolutionary concoction comprising advanced technological servers with a new wave of currency systems, brings about the most uprising event in the cryptocurrency ecosystem.
“We envisioned cryptocurrency to be the game changer in most developed country’s economy within the next 5 years. Reliance of quantum computing technology expedite the whole process, and we will be recognized as the industry leader in bringing about this tidal change. We aren’t the only institution fathom to leverage on this technology. Other Silicon big boys are already in advance talks of a possible tie up”, said Mike Howzer, CEO of CoinFac Limited.“Through the use of quantum computing, usual bitcoin mining processes are expedited by a blazing speed of 4,000 times. We bring lucrative mining back into Bitcoin industry, all over again”.
Google, NASA and Microsoft have been in close talk with the developers of a possible integration using quantum computing into their existing products and platform.
Recognizing the importance of biofuels to energy and climate security, the U.S. Department of Energy has announced up to $90 million in project funding focused on designing, constructing and operating integrated biorefinery facilities. The production of biofuels from sustainable, non-food, domestic biomass resources is an important strategy to meet the Administration’s goals to reduce carbon emissions and our dependence on imported oil.
Project Development for Pilot and Demonstration Scale Manufacturing of Biofuels, Bioproducts, and Biopower is a funding opportunity meant to assist in the construction of bioenergy infrastructure to integrate cutting-edge pretreatment, process, and convergence technologies. Biorefineries are modeled after petroleum refineries, but use domestic biomass sources instead of crude oil, or other fossil fuels to produce biofuels, bioproducts, and biopower. They convert biomass feedstocks—the plant and algal materials used to derive fuels like ethanol, butanol, biodiesel and other hydrocarbon fuels—to another form of fuel or energy product. This funding will support efforts to improve and demonstrate processes that break down complex biomass feedstocks and convert them to gasoline, diesel and jet fuel, as well as plastics and chemicals.
“The domestic bio-industry could play an important part in the growing clean energy economy and in reducing American dependence on imported oil,” said Lynn Orr, DOE’s under secretary for science and energy. “This funding opportunity will support companies that are working to advance current technologies and help them overcome existing challenges in bioenergy so the industry can meet its full potential.”
Governments are in the business of regulating certain activities—hopefully in an effort to serve the public good. In the case of business methods and activities, their goal is to maintain an orderly marketplace; one that is fair, safe and conducive to economic growth.
But regulation that lacks a clear purpose or a reasonable detection and enforcement mechanism is folly. Such regulation risks making government seem arbitrary, punitive or ineffective.
«— This is money. It is not a promissory note, a metaphor, an analogy or an abstract representation of money in some account. It is the money itself. Unlike your national currency, it does not require an underlying asset or redemption guarantee.
Bitcoin is remarkably resistant to effective regulation because it is a fully distributed, peer-to-peer mechanism. There is no central set of books, no bank to subpoena, and no central committee to pressure (at least not anyone who can put the genie back into the bottle). In essence, there is no choke point or accountable administrative party.
Sure—it is possible to trace some transactions and legislate against ‘mixers’ and other anonymization methods—but there is no way to prevent a transaction before it occurs or to know the current distribution of assets. Bitcoin can exist as a printed QR code and it can be transmitted from a jail cell with a blinking flashlight. Sending bitcoin from Alice to Bob has no intermediary. Settlement requires only that one of the parties eventually has access to the Internet. But, there is no credit authority or central asset verification. [continue below image]…
If you are thinking of legislating against the use of Bitcoin, you might as well pass laws to ban the mating of feral cats or forbid water from seeping into underground basements. These things are beyond the domain of human geopolitics. You can try to shape the environment (e.g. offer incentives to cats and water levels), but you cannot stop sex or seepage.
Fortunately, Bitcoin is not a threat to governments—not even to spending or taxation. A gross misunderstanding of economics and sociology has led some nations to be suspicious of Bitcoin, but this improper perception is abating. Governments are gradually recognizing that Bitcoin presents more of an opportunity than a threat.
“I need a stealth bomber that’s going to get close, and then it’s going to drop a whole bunch of smalls – some are decoys, some are jammers, some are [intelligence, surveillance, and reconnaissance] looking for where the SAMs are. Some of them are kamikaze airplanes that are going to kamikaze into those SAMs, and they’re cheap. You have maybe 100 or 1,000 surface-to-air missiles, but we’re going to hit you with 10,000 smalls, not 10,000 MQ-9s. That’s why we want smalls.”
SAMs stands for “Surface-to-Air Missile,” and they’re one of the reasons that the Air Force has invested so much in stealth technology over the years: if a missile can’t see a plane, it can’t hit it. The problem is that the economics don’t quite work that way: it’s easier to make a new, better missile than it is to make an existing airplane even stealthier, and modern Air Force fighters serve for around 30 years each—longer if they’re bombers. Missiles are generally cheaper than airplanes, so anyone who wants to protect against aerial attack just needs to invest in a lot of missiles.
Here in the Lifeboat Blog, I have the luxury of pontificating on existential, scientific and technical topics that beg for an audience—and sometimes—a pithy opinion. Regular Lifeboat readers know that I was recently named most viewed Bitcoin writer at Quora under a Nom de Plume.
Quora is not a typical Blog. It is an educational site. Questions and numerous answers form the basis of a crowd-sourced popularity contest. Readers can direct questions to specific experts or armchair analysts. A voting algorithm leads to the emergence of some very knowledgeable answers, even among laypersons and ‘armchair’ experts.
During the past few weeks, Quora readers asked me a litany of queries about Bitcoin and the blockchain, and so I am sharing selected Q&A here at Lifeboat. This is my professional field—and so, just as with Mr. Trump, I must resist an urge to be verbose or bombastic. My answers are not the shortest, but they are compact. Some employ metaphors, but they explain complex ideas across a broad audience.
As you browse some recent Bitcoin questions below, click a question for which you know the least. (Example: Do you know what the coming ‘halving event’ is about?). Leave a comment or question. I am interested in your opinion.
How could global economic inequality survive the onslaught of synthetic organisms, micromanufacturing devices, additive manufacturing machines, nano-factories? (http://www.beliefnet.com/columnists/lordre/2016/04/obsessed-with-equality-my-techno-utopia.html#S5Ogqvv8PL36KMDo.99)
Narrated by Harry J. Bentham, author of Catalyst: A Techno-Liberation Thesis (2013), using the introduction from that book as a taster of the audio version of the book in production. (http://www.clubof.info/2016/04/liberation-technologies-to-come.html)
I could tell you one scenario after another about Robots serving Robots, making robots, owning their own country, having their own military, etc. However, for me we’re still many, many decades off from this. However, we do have some situations that I have seen robots assembling other robots; however, they’re still requiring human engagement and oversight.
If that sounds like something you’re interested in.
«— This is money. It is not a promissory note, a metaphor, an analogy or an abstract representation of money in some account. It is the money itself. Unlike your national currency, it does not require an underlying asset or redemption guarantee.
