What if you couldn't fact check the investment data you wanted to buy, but the data was verified by a cryptographically proven, immutable blockchain? One major bank that is solely responsible for managing an estimated 11% of all the world's financial assets is exploring just such a possibility. Following a State Street report published last week on the long-term value of blockchain and other technologies, the bank's executive vice president of global exchange, Lou Maiuri, elaborated on how his group is experimenting with new ways to capitalize on blockchain tech. In conversation with CoinDesk, Maiuri explained how combining artificial intelligence and blockchain could lead to new revenue streams derived from valuable client data. "Anyone who's not looking at these pools of data will be arbitraged, will lose out."

MIT SMR and Boston Consulting Group are collaborating on a new research initiative, Artificial Intelligence & Business Strategy, to explore the most important business opportunities and challenges for managers posed by AI. The field of artificial intelligence (AI) is finally yielding valuable smart devices and applications that do more than win games against human champions. According to a report from the Frederick S. Pardee Center for International Futures at the University of Denver, the products of AI are changing the competitive landscape in several industry sectors and are poised to upend operations in many business functions. MIT Sloan Management Review and the Boston Consulting Group have joined forces to find out. Our new research initiative, Artificial Intelligence & Business Strategy, explores the most important business opportunities and challenges from AI. Artificial intelligence covers a diverse set of abilities, much like Howard Gardner's breakdown of human intelligence into multiple intelligences.

In March 2016 Insilico Medicine initiated a research collaboration with Life Extension to apply advanced bioinformatic methods and deep learning algorithms to screen for naturally occurring compounds that may slow down or even reverse the cellular and molecular mechanisms of aging. Today Life Extension (LE) launched a new line of nutraceuticals called GEROPROTECTTM, and the first product in the series called Ageless CellTM combines some of the natural compounds that were shortlisted by Insilico Medicine's algorithms and are generally recognized as safe (GRAS). "Life Extension's mission is to extend the healthy human lifespan; and as such, we are focused on identifying natural products with critical health and wellness properties," said Andrew G. Swick, PhD, senior vice president of scientific affairs, discovery research and product development for Life Extension. "Our collaboration with Insilico Medicine fostered a novel approach to formulating anti-aging supplements utilizing artificial intelligence and sophisticated biologically-inspired algorithms and resulted in the very first AI formulated supplement," Swick said. The global nutraceuticals market was valued at US$165.62 billion in 2014 by Transparency Market Research and is expected to reach US$278.96 billion by 2021.

WikiLeaks has published a huge trove of what appear to be CIA spying secrets. The files are the most comprehensive release of US spying files ever made public, according to Julian Assange. In all, there are 8,761 documents that account for "the entire hacking capacity of the CIA", Mr Assange claimed in a release, and the trove is just the first of a series of "Vault 7" leaks. Already, the files include far more pages than the Snowden files that exposed the vast hacking power of the NSA and other agencies. In publishing the documents, WikiLeaks had ensured that the CIA had "lost control of its arsenal", he claimed.

It appears Apple is serious with launching a new iPhone installment with facial recognition capabilities. The Cupertino giant has just been awarded with a patent for an invention that involves face detection using depth information. U.S. patent 9,589,177 was granted to Apple by the U.S. Patent and Trademark Office on Tuesday, and it is a patent that details how face detection or facial recognition will work on an upcoming device, which is very likely to be the iPhone 8. Based on this new document, Apple is working on a technology that would allow the recognition of faces in digital video feeds using depth map data and images of the scene or background. The depth map will help in plotting the coordinates of the human faces that will be detected at a particular location. A respective face detection window will then mark the human face.

Marketers are turning to machine learning to find patterns in data and use analytically derived insights to predict future actions at a more finite level. Organizations are putting machine learning to use in myriad ways, including powering personal voice assistants, enhancing recommendation engines, reducing fraud and guiding self-driving cars. If you're exploring how to put machine learning to work in your marketing, here's how you can use it to minimize guesswork and bolster four key marketing actions immediately. Use information from both external sources and customer interactions to provide more variant-rich customer views and enable personalization at micro levels not previously possible with traditional segmentation approaches. Machine learning allows organizations to more rapidly analyze and learn from high-volume, varied and detailed data -- whether structured, unstructured or semi-structured.

Yahoo has launched another bot, called Captain, with the specific mission of reminding you about things you need to do. This SMS-based tool will manage lists and reminders, and all you have to do is text "Hi" to 773-786 to begin the process. This Siri-meets-Evernote bot lets you input any reminders you want to receive, and when the deadline approaches texts you with a follow-up message. You can also easily create lists within the bot. While many developers produce bots for messaging apps, Yahoo has instead elected to center Captain around text messaging.

Given how much several tech giants throw around the terms "artificial intelligence," "machine learning" and "deep learning," it's easy to assume that they're all trying to do similar things. And in some cases, the companies are indeed using AI to tackle problems that have much in common, particularly when it comes to making sense out of real-life sounds, images and dialogue. But a closer look shows that tech giants are at times not only tackling very different challenges, but employing different AI techniques to do so. IBM (IBM), which has set a goal of obtaining $10 billion in annual revenue related to its Watson AI platform by 2023, is especially an outlier -- not seen as a leader when it comes to certain large-scale, consumer-focused AI solutions, but very much one when it comes to AI offerings that require a measure of industry-specific expertise. The companies plan to pair Watson's ability to make sense out of data unique to fields such as health care, retail and financial services with Salesforce's Einstein AI platform -- it relies on the data taken in by Salesforce apps -- to deliver industry-specific insights, predictions and recommendations that can be useful for customer interactions. One such example given by the companies: By having Salesforce's Marketing Cloud apps plug into Watson programming interfaces (APIs), weather, local shopping and retail industry data analyzed by Watson could be paired with customer-specific shopping data analyzed by Einstein to "send highly personalized and localized email campaigns to shoppers."

Today, IBM and Salesforce announced they will connect their artificial intelligence platforms to help companies target and serve customers. IBM's natural-language AI program Watson -- which conquered the television quiz show "Jeopardy" -- will be integrated with Salesforce's Einstein, the AI that helps mine its hugely popular customer relationship management software, to provide customer purchasing habits and shopping data for businesses that run Salesforce. That means that an insurance company that uses Salesforce, for example, can also use Watson's weather data to target customers before a snowstorm to help reduce potential damages. By combining Watson's data on local retail trends with specific customer data from Salesforce, companies will be able to send highly targeted campaigns to shoppers, according to the companies. Salesforce customers will be able to start using Watson's smarts to refine their customer targeting starting in the second half of this year.

They are able to infer what you want. As a result, they respond with appropriate actions. They operate autonomously i.e. without human supervision. They are able to infer what you want. As a result, they respond with appropriate actions.