Analysis If you are reading this article, it's probably that you wonder why to associate intelligence with unmanned cars. After all, it's only codes that programmers from Google, Tesla or Uber or a smaller startup wrote. Even if it were possible to make cars more intelligent, why bother about it? Aren't they already operating quite well with embedded personal computers (PCs)? You might think they are probably using PCs with a beefed-up version of their multicore processors for extra raw processing power.

Those rumors of Apple exploring facial recognition for sign-ins might just have some merit. Calcalist reports that Apple has acquired RealFace, an Israeli startup that developed deep learning-based face authentication technology. The terms of the deal aren't public, but it's estimated at "several million dollars." Cupertino would mainly be interested in the promise of the technology than pure resources, in other words. We've reached out to Apple for comment on the reported deal and will let you know if it has something to add. However, RealFace recently took its website down and left nothing but a skeleton server behind.

IBM is making machine learning technology available in the place where much of the world's enterprise data resides: the z System mainframe. Big Blue announced IBM Machine Learning, a cognitive platform for creating, training and deploying a high volume of analytic models in the private cloud. The platform draws on the core machine learning technology from its Watson Machine Learning service on its Bluemix public cloud offering. "Our mission is making data simple and accessible to clients," says Rob Thomas, general manager, IBM Analytics. "If you look at the data landscape today, over 90 percent of the data in the world today cannot be Googled. Most of that data resides behind corporate firewalls in private clouds."

Our group recently identified a ten gene pattern of differential expression in peripheral blood which may have utility for detection of stroke. The objective of this study was to assess the diagnostic capacity and temporal stability of this stroke-associated transcriptional signature in an independent patient population. Publically available whole blood microarray data generated from 23 ischemic stroke patients at 3, 5, and 24 hours post-symptom onset, along with 23 cardiovascular disease controls were obtained via the National Center for Biotechnology Information Gene Expression Omnibus. Expression levels of the ten candidate genes were extracted, compared between groups, and evaluated for their discriminatory ability at each time point. We observed a largely identical pattern of differential expression between stroke patients and controls across the ten candidate genes as reported in our prior work.

It was one of those amazing "we're living in the future" moments. In an October 2013 press release, IBM declared that MD Anderson, the cancer center that is part of the University of Texas, "is using the IBM Watson cognitive computing system for its mission to eradicate cancer." Well, now that future is past. The partnership between IBM and one of the world's top cancer research institutions is falling apart. The project is on hold, MD Anderson confirms, and has been since late last year.

In 2011, IBM Watson debuted on the TV show Jeopardy and impressed millions in a spectacle where the artificial intelligence defeated 2 of jeopardy's all time great champions. While Apple, Google, Facebook, Amazon, and Microsoft have been developing their AI to handle daily tasks such as shopping, calling an Uber, or playing music, IBM (NYSE: IBM) has been pushing Watson into tackling real world problems such as cancer diagnosis/treatment, traffic accident prevention, and tax reporting. IBM Watson, like the rest of its AI colleagues, is a product of machine learning, natural language processing, and statistical analysis. The difference lies in the types of data IBM is feeding Watson. Watson is being taught intellectual knowledge in the form of research papers, large industrial data reports, and other scholarly publishings.

Elon Musk believes that artificial intelligence will create a cyborg race. During the World Government Summit in Dubai, the SpaceX founder explains that deep artificial intelligence - the kind that is much smarter than the smartest man in the world - can be a dangerous thing. During his talk, Elon Musk believes that robot automation and artificial intelligence will be taking over 15 percent of the global workforce. The SpaceX, Tesla and Hyperloop authority believes that humans are becoming more and more dependent on technology. He sees a world where human beings are already cyborgs.

It was one of those amazing "we're living in the future" moments. In an October 2013 press release, IBM declared that MD Anderson, the cancer center that is part of the University of Texas, "is using the IBM Watson cognitive computing system for its mission to eradicate cancer." Well, now that future is past. The partnership between IBM and one of the world's top cancer research institutions is falling apart. The project is on hold, MD Anderson confirms, and has been since late last year.

Apple has acquired Tel Aviv, Israel-based Realface, a machine learning startup whose facial recognition technology can be used to authenticate users, according to reports from Calcalist (in Hebrew) and The Times Of Israel. Founded in 2014, RealFace says it has developed an innovative way of recognising people, self-reportedly building A.I software that "brings back human perception to digital process". RealFace's software enables authentication, automated on-boarding & mobile conversion optimisation. The company, led by co-founder and Columbia Business School-trained Adi Eckhouse Barzilai, says it has proprietary IP in the field of'frictionless face recognition' and effective learnings from facial features. The Israeli startup is behind the Pickeez app, which automatically choses a user's best photos from various platforms using the RealFace recognition software.

UK-based security technology company Sophos (OTC:SPHHF) (LSE: SOPH) has announced an agreement to acquire Invincea's software business for up to $120 million in total consideration. Invincea has developed security software that utilizes machine learning and behavioral modeling to quickly detect and react to endpoint, perimeter threats and malware attacks. The technology is a necessary upgrade to the Sophos Central product line and also provides middle market focused Sophos with a foothold in the small business market through the addition of Invincea's customer base. Fairfax, Virginia-based Invincea was founded in 2009 by CEO Anup Ghosh to focus on endpoint threat detection, prevention, and analysis. The company provides security software to more than 25,000 small and medium enterprise customers through its antivirus'X' system that'combines machine learning and behavioral monitoring to eliminate endpoint security blind spots without sacrificing usability.'