The world's first unmanned ship set sail on April 7. The new ship, called the Sea Hunter, will hunt enemy submarines lurking in the deep. A new hunter is lurking in the deep -- and it's made of metal, silicon, and lots and lots of artificial intelligence. The Defense Advanced Research Projects Agency (DARPA) officially launched its unmanned submarine-hunting ship, holding a christening ceremony on Thursday (April 7) for the "Sea Hunter." The new vessel is part of DARPA's larger initiative to use artificial intelligence (AI) for a wider array of military decisions and tasks.

The next wave of artificial intelligence (AI) will likely be used by hedge funds making long-term macro plays around things like oil prices, involving more data than an analyst could crunch in a lifetime. Although habitually secretive, the use of machine learning and AI among the hedge fund community has been well publicised. Bridgewater Associates, the world's largest hedge fund with about 154 billion ( 109bn) under management, has been vocal about its use of AI. And it's not uncommon to hear about investment firms hiring data scientists with PhDs in neural networks, or physicists and astronomers who can remove the noise from data signals. Publicis.Sapient AI leader Josh Sutton, who has worked in financial services for 15 years and has some hedge funds among his clients, expects to see a confluence of causal analytics and long-term macro strategies.

In this special guest feature, Dave O'Flanagan, CEO and co-founder of Boxever, outlines how airlines are leveraging big data and predictive capabilities to transform how they engage with customers. Dave is the CEO and co-founder of Boxever, a data science and omni-channel personalization platform for travel companies. At Boxever, Dave's focus is enabling airlines and travel providers to improve the customer experience, generate revenue and enhance loyalty through one-to-one, personalized marketing. Dave has more than 15 years' experience developing and managing enterprise software in mobile telecoms, travel and cloud. Earlier he was VP of engineering at CUSP, a cloud-based document management startup and was a lead architect at CAPE Technologies.

The latest buzz about Panama Papers has shaken the world. As we all know the Panama Papers is a set of 2.6 TB of data that includes 11.5 million confidential documents with detailed information about more than 214,000 offshore companies listed by the Panamanian corporate service provider Mossack Fonseca. The Panama Papers has set an excellent example for the world about the importance of data science when it comes to analyzing big data. This leak makes us realize that appropriate approaches are needed to handle the challenges of data management for the present and the future. Let's take a deep dive into the Panama Papers and dig down the secret behind the biggest leak ever This leak contains 4.8 million emails, 3 million database entries, 21.5 million PDFs, around one million images and 320,000 text documents.

Breast cancer is the most frequently diagnosed cancer in women worldwide excluding skin cancer and it is ranked second for deaths among cancer patients [1]. Early diagnosis of breast cancer is crucial for patient prognosis. Currently, however, clinically diagnosed breast tumors have a median size of 2 to 2.5 cm [2], which are likely to be later stage (stage III) breast tumors that have already metastasized to axillary lymph nodes. A highly accurate diagnostic test for breast cancer is currently lacking. The standard mammography test has sensitivities of merely 54 to 77 % [3].

Small business financing can be challenging and risky, especially with the uncertain nature of small businesses given that large corporations are aggressively penetrating various market niches. While traditional financial institutions may turn away from SMEs, some alternative lenders are quite successful in delivering financing to these businesses. One of the market leaders in the alternative small business finance space, CAN Capital, has announced that it reached 6 billion in delivering access to working capital for small businesses. During its 18 years in business, CAN Capital has provided access to more working capital than any other company in the space. To date, CAN Capital has helped facilitate over 170,000 small business fundings in hundreds of unique industries, such as restaurants, medical offices and beauty salons.

Artificial Intelligence is a tool. Planning is a management task. Can AI help to better plan? Or AI is even going to replace humans in this exercise? Let's proceed with order: can we give a better definition of planning and artificial intelligence?

In 2011, IBM stole the artificial intelligence show when Watson, a talking cognitive computer, won Jeopardy! By feeding the computer millions of pages of unstructured data -- that is to say, no numbers or values neatly organized in spreadsheets -- the company "taught" Watson everything he needed to thoroughly whack human Jeopardy! For the first time ever, a computer with some sense of understanding of the world was not only on display, it was on television. At present, some 80,000 developers and 500 businesses are using this cloud to create the next generation of smart apps that can make use of language, speech, vision, and data that seem sure to become powerful, useful pieces of software. It's as though we are sitting on the precipice of a time when it will become easy -- perhaps even boring -- to speak to your computer as you might speak to a coworker, and to have that speech turned into useful action.

Which are the most important machine learning algorithms? Anyone who has been part of this domain must have faced or posed this question at some point of time. I too am asked this often. First things first – there are no winning algorithms. For different circumstances, different algorithms, even though they might be designed for similar outcome, result in differently oriented output.

Marvin Minsky was a neuro scientist, engineer and philosopher who considered the future of machines and computer learning. He died in January 2016 aged 88. He was on the MIT faculty from 1958 to his death. In 1959 he and John McCarthy founded what is now known as the MIT Computer Science and Artificial Intelligence Laboratory. In 1951, Minsky built the first randomly wired neural network learning machine, SNARC.