This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by grants from the following entities: Centre for Networked Biomedical Research into Neurodegenerative Diseases (CIBERNED, CB06/05/0066 to JDF), the Spanish Ministry of Economy and Competitiveness (grants SAF2009-09394 to JDF; Juan de la Cierva postdoctoral fellowship to RA; TIN2010-20900-C04-04 and the Cajal Blue Brain Project, Spanish partner of the Blue Brain Project initiative from EPFL, to JDF, PL and CB. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

Random forest is a highly versatile machine learning method with numerous applications ranging from marketing to healthcare and insurance. It can be used to model the impact of marketing on customer acquisition, retention, and churn or to predict disease risk and susceptibility in patients. Random forest is capable of regression and classification. It can handle a large number of features, and it's helpful for estimating which of your variables are important in the underlying data being modeled. Random forest is solid choice for nearly any prediction problem (even non-linear ones).

Many people, myself included, believe that AI will be the primary catalyst in transforming most industries over the next decade. The question that many people are asking is how to capture the alpha -- the active return on investment -- associated with artificial intelligence. In this article I will share my belief about where the market opportunities are for today's investors and entrepreneurs. The path that many startups are taking today is to provide the tools that firms will need to capitalize on the AI marketplace. Many of these startups are seeking an early exit -- and they aren't being disappointed.

Artificial intelligence has already begun to impact on our everyday lives and the technological revolution we are witnessing is set to transform the accounting profession – and the relationship between accountants and SMEs. That changing relationship will benefit accountants and businesses, heralding new ways of working and putting our service and knowledge at the heart of business development and strategy for the good of SMEs and the wider economy. There is no doubt that we are on a journey that is going in only one direction. Sophisticated accounting software and systems will change our role as artificial intelligence (AI), smart machine learning and increased automation takes over traditional accountancy roles such as bookkeeping and data entry. And the direction we are heading is already being well signposted.

Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.

Facebook have kick started a trend of AI's building more AI's and it's only going to accelerate Deep Neural Networks (DNNs) are taking over the internet. DNNs, unlike their more basic pattern matching Machine Learning cousins are able to learn and replicate human like tasks by analysing vast amounts of digital data and these artificially intelligent systems are injecting online services with a power that just wasn't viable in years past. They're identifying faces in photos, powering search, pulling meaning from videos, applying meaning to language and translating complex conversations from one language to another. But what's less discussed is how the giants of the Internet go about building these rather remarkable engines of AI. Companies like Google and Facebook pay top dollar for some really smart people – only a few hundred souls on Earth have the talent and the training needed to really push the boundaries of Deep Learning and paying for these top minds is a lot like paying for an NFL quarterback but more expensive – Google reportedly bought DeepMind for $600 million not for it's technology but for its twelve strong team of researchers.

Kristen Stewart, the Hollywood actress perhaps best known for her role in the "Twilight" movies, has co-authored a new research paper that discusses the use of artificial intelligence technology, to create art in her screenwriting debut film, "Come Swim." The 17-minute film, starring Josh Kaye and Sydney Lopez, has been written and directed by Stewart. The movie is set to feature in the Sundance Film Festival 2017 that kicked off Thursday. It was inspired by one of Stewart's own paintings that itself originated from one of her poems. "It's basically about that moment when you wake up and you get dressed and you realize ... I'm not sad anymore. I've been dropped back into everyone else's reality and now I can live again," Stewart told the New York Times Magazine while describing the concept of the film.

Avanti Recruitment is working with a multinational technology company in London to recruit a hands-on Data Science Manager to lead and manage their Data Science team working on projects for the financial services industry. We are looking for an experienced Manager who has progressed through the ranks as a Data Scientist working with a range of Machine Learning techniques. You will manage a small team of two Data Scientists and will be responsible for the output of the team and will also be involved hands-on in building models and providing technical leadership. You will be working on petabytes of complex data in a new area for exploration with the opportunity to make a huge impact in the sector. They work primarily with financial data but prior experience in the Fintech sector is not necessary as long as you have strong skills in managing a team and working with Machine Learning and statistical techniques to build predictive models.

We are living in the era of technological transformation that is bringing about changes in the way we take decisions. As big data is becoming pervasive across all the industries, use of machines to find patterns and predict future is gaining a lot of prominence in the market.

We can use them to sing, shout and whisper sweet nothings. We can use them to activate gadgets and prove who we are to banks. And now researchers believe they can also reveal whether we're getting ill. A US start-up called Canary Speech is developing a way of analysing conversations using machine learning to test for a number of neurological and cognitive diseases, ranging from Parkinson's to dementia. The project was born out of a painful personal experience for the firm's co-founder Henry O'Connell.