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Planetary Resources, Inc., the asteroid mining company, announced today that it has finalized a 25 million euro agreement that includes direct capital investment of 12 million euros and grants of 13 million euros from the Government of the Grand Duchy of Luxembourg and the banking institution Société Nationale de Crédit et d’Investissement (SNCI). The funding will accelerate the company’s technical advancements with the aim of launching the first commercial asteroid prospecting mission by 2020.

Planetary Resources’ Arkyd 6 is equipped with the first commercially licensed mid-wave infrared imager, an essential tool for detecting water on asteroids. Two spacecraft are completed and will test this technology on orbit. Planetary Resources’ President & CEO Chris Lewicki and Luxembourg’s Deputy Prime Minister Etienne Schneider pictured with the Arkyd 6 in Planetary Resources’ clean room facility in Redmond, Washington.

Core hardware and software technologies developed at Planetary Resources were tested on orbit last year. The company’s next mission, now undergoing final testing, will validate the thermographic sensor that will precisely measure temperature differences of objects on Earth. When deployed on future commercial asteroid prospecting missions, the sensor will acquire key data related to the presence of water and water-bearing minerals on asteroids. Obtaining and using these key resources in space promises to fast-track the development of off-planet economic activities as the commercial industry continues to accelerate.

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“Among policy makers alert for signs of the next financial disaster, Italy’s mountain of uncollectable bank debt is a subject discussed in tones ordinarily reserved for piles of plutonium.”

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SALT LAKE CITY, Nov. 14, 2016 /PRNewswire/ IBM (NYSE: IBM) and NVIDIA (NVDA)today announced collaboration on a new deep learning tool optimized for the latest IBM and NVIDIA technologies to help train computers to think and learn in more human-like ways at a faster pace.

Deep learning is a fast growing machine learning method that extracts information by crunching through millions of pieces of data to detect and rank the most important aspects from the data. Publicly supported among leading consumer web and mobile application companies, deep learning is quickly being adopted by more traditional business enterprises.

Deep learning and other artificial intelligence capabilities are being used across a wide range of industry sectors; in banking to advance fraud detection through facial recognition; in automotive for self-driving automobiles and in retail for fully automated call centers with computers that can better understand speech and answer questions.

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Telegram has announced the first winners of its bot competition. The BotPrize was announced in April and will see $1 million awarded to developers of the best Telegram bots submitted. The first winners come from the worlds of photo-editing, productivity, games, dating and finance.

Telegram is a messaging service with a focus on speed and security. Launched in 2013, it is cloud-based, meaning that user content syncs instantly across the platforms on which the service can be used, including PC, Mac, Linux, Android, iOS and Windows Phone.

The firm’s BotPrize will help to increase the number of bots available on the service and accelerate the speed with which the number is increased. For the uninitiated, bots are effectively apps in themselves with which users can interact via messaging. They typically run inside messaging apps such as Facebook Messenger or, in this instance, Telegram.

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Whenever cybersecurity is discussed, the topic of biometric authentication rises alongside it as a better, more effective, more secure method of security. But is it? Do biometrics actually provide a safer way to complete purchase transactions online?

“Biometrics are a device-specific authentication method,” said Madeline Aufseeser, CEO of online fraud prevention company Tender Armor, of the ways biometric authentication is presently used to secure a digital purchase transaction (as opposed to logging into a bank’s web site, to view an account or transfer money). “Typically the same biometric method does not work across multiple purchasing channels today. The fingerprint used to make a purchase with a smartphone cannot necessarily be used to authenticate a phone order purchase or purchase made with a computer. When you confirm [a purchase transaction] with your fingerprint on a smartphone, all that’s saying is that’s the same fingerprint that’s allowed to use this phone, or the specific application on the phone. Because the fingerprint is only resident and stored on the phone, the phone is authenticating itself, not the cardholder conducting the transaction.”

This sounds a little odd compared to what we might have heard about the capabilities of biometrics previously, mainly because it goes against a core assumption: that a biometric identifier (like a fingerprint) goes with transactional data, from the phone or device, to the payment processor, to the merchant.

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2 November 2016. Two companies partnering with Auburn University developed a synthetic virus to find and destroy tumor cells in a type of bone cancer in dogs. Financial and intellectual property aspects of the agreement between synthetic gene company Gen9 in Cambridge, Massachusetts, design systems developer Autodesk Inc. in San Rafael, California, and Auburn University College of Veterinary Medicine in Alabama were not disclosed.

The research team created a synthetic version of canine adenovirus type 2, or CAV2, a virus usually associated with hepatitis in dogs. In this case, the synthetic CAV-2 virus is designed as an oncolytic virus that finds and attacks cancer cells, while leaving healthy cells and tissue intact. The genome in the organism is believed to be the longest in a functional virus synthesized for cancer research, with about 34,000 base pairs of nucleic acids. The human genome, by comparison, has about 3 billion base pairs.

The technology provided by Gen9 in this project makes it possible to eventually produce synthetic therapeutic viruses tailored for specific patients. Gen9 offers customized gene synthesis and is developing a library of synthesized proteins and antibodies. One of the 4 year-old company’s founders is George Church, a geneticist at Harvard Medical School and serial entrepreneur. In August 2016, as reported in Science & Enterprise, Church and colleagues, including those from Gen9, developed a synthetic E. coli bacteria genome with redundant DNA components removed.

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Anyone who does not have QC as part of their 5+Yr Roadmap for IT are truly exposing their company as well as shareholders and customers. China, Russia, Cartels, DarkNet, etc. will use the technology to extort victims, destroy companies, economies, and complete countries where folks have not planned, budget, skilled up, and prep for full replacement of their infrastructure and Net access. Not to mention companies who have this infrastructure will provide better services/ CCE to svc. consumers.

In a recent article, we highlighted a smart beta ETF called the “Sprott BUZZ Social Media Insights ETF” that uses artificial intelligence (AI) to select and weight stocks. If we stop and think about that for a moment, that’s a pretty cool use of AI that seems well ahead of its time. Now we’re not saying that you should go out and buy this smart beta ETF right away. It uses social media data. We know that on social media, everyone’s an expert and many of the opinions that are stated are just that, opinions. However some of the signals may be legitimate. Someone who just bought Apple is likely to go on telling everyone how bullish they are on Apple shares. Bullish behavior is often accompanied by bullish rhetoric. And maybe that’s exactly the point, but the extent to which we’re actually using artificial intelligence here is not that meaningful. Simple scripting tools go out and scrape all this public data and then we use natural language processing (NLP) algorithms to determine if the data artifacts have a positive or negative sentiment. That’s not that intelligent, is it? This made us start to think about what it would take to create a truly “intelligent” smart beta ETF.

What is Smart Beta?

We have talked before about how people that work in finance love to obfuscate the simplicity of what they do with obscure acronyms and terminology. Complex nomenclature is suited for sophisticated scientific domains like synthetic biology or quantum computing but such language is hardly merited for use in the world of finance. We told you before what beta is. Smart beta is just another way of saying “rules based investing” which has in fact been around for centuries, but of course we act like it’s new and start publishing all kinds of research papers on it. In fact, a poll offered up by S&P Capital IQ shows that even 1 out of 4 finance professionals recognizes the term “smart beta” to be little more than a marketing gimmick:

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A nice read on the who’s who in QC: congrats Vern Brownell and Michelle S. in making the top 13 list.

Leaders in quantum computing discuss the challenges and potential for this technology across finance, AI, and many other fields.

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