SAS announced a new open, "cloud-ready" machine learning, cognitive computing, analytics platform. Recently, Customer Think wrote: The idea is to bring together the SAS portfolio, built over some 40 years, into one platform that can be used by data scientists and other analytics professionals; business users and IT management; and senior management. Customer Think stated, SAS is also working harder to be more "open" -- in the sense of being interoperable with other enterprise systems. This is hugely important in the age of cloud-based systems and infrastructure services like Amazon Web Services and Microsoft Azure. If you can't access a key functionality via a cloud-based API, it might as well not exist.

Next-generation cognitive computing is redefining how we live and work as more businesses are using all the data available to them to improve performance and customer service, and drive innovation and revenue. Today's business challenges have never been more complex, and the critical insights that can help address these challenges are often buried in an avalanche of data. Previously, these insights were beyond the capabilities of conventional computing solutions – programmable systems based on mathematical principles that harken back to the 1940s. But IBM Watson has changed the game. IBM Watson is built upon a new foundation called cognitive computing – a system that learns and reasons from interactions with humans, files, online interactions and its environment.

Airbus Group is using machine learning and data analytics to help guide pilots through catastrophic emergencies. In a speech at the Connect Expo in Melbourne, Airbus Group head of data driven technologies Ronny Fehling said the business was working on ways to reduce the information overload pilots face during a crisis. "Right now if there's something bad happening, every light goes on in the cockpit, and that's not what we want. We want to reduce the amount of information and false positives," Fehling said. "If the engines are burning, we need it to say'focus on this right now, and all the rest will be handled by the system'. We want to give [pilots] the right tools and information so they can make the right decision to save lives."

IBM Research is to collaborate with the Massachusetts Institute of Technology (MIT) to develop machine-vision systems. The new IBM-MIT Laboratory for Brain-inspired Multimedia Machine Comprehension's (BM3C) will work on the development of cognitive computing systems that can emulate the human ability to comprehend visual and audio inputs. BM3C will address technical challenges around both pattern recognition and prediction methods in the field of machine vision that are currently impossible for machines alone to accomplish. For example, online retailer Ocado has talked to Computing about the need for such systems in order to automate the packing of supermarket items for delivery so that potatoes are packed before tomatoes. The BMC3 collaboration will bring together brain, cognitive, and computer science specialists to conduct research in the field of unsupervised machine understanding of audio-visual streams of data, using insights from next-generation models of the brain to inform advances in machine vision.

IBM Research announced a multi-year collaboration with the Department of Brain & Cognitive Sciences at MIT to advance the scientific field of machine vision, a core aspect of artificial intelligence. The new IBM-MIT Laboratory for Brain-inspired Multimedia Machine Comprehension's (BM3C) goal will be to develop cognitive computing systems that emulate the human ability to understand and integrate inputs from multiple sources of audio and visual information into a detailed computer representation of the world that can be used in a variety of computer applications in industries such as healthcare, education, and entertainment. The BM3C will address technical challenges around both pattern recognition and prediction methods in the field of machine vision that are currently impossible for machines alone to accomplish. For instance, humans watching a short video of a real-world event can easily recognize and produce a verbal description of what happened in the clip as well as assess and predict the likelihood of a variety of subsequent events, but for a machine, this ability is currently impossible. Beginning in September 2016 in Cambridge, the BMC3 collaboration will bring together leading brain, cognitive, and computer scientists to conduct research in the field of unsupervised machine understanding of audio-visual streams of data, using insights from next-generation models of the brain to inform advances in machine vision.

Next-generation cognitive computing is rapidly changing how we live and work. Thousands of brands like 1-800-Flowers and Sesame Street are already using cognitive solutions like IBM Watson to redefine how they improve performance, customer service and revenue. Today's business challenges have never been more complex, and the critical insights that can help address these challenges are often buried in an avalanche of data. With cognitive computing, we are now able to unlock the value in ALL the data -- from internal, external and even publicly available sources -- available to a business. Much of this data was previously inaccessible as it existed in was unstructured (documents, emails, social media posts and images etc.), or was dispersed among any many systems and silos.

It was a heady mix of business and technical sessions on how to take advantage of the power of analytics. Of course there are innumerable applications for analytics, from fraud detection to supply chain optimization to garden variety business intelligence. For this post I'll focus mainly on customer-related applications, and some of the more advanced SAS capabilities discussed at the conference. Let's start with what SAS announced: SAS Viya -- billed as a new open, "cloud-ready" analytics platform. The idea is to bring together the SAS portfolio, built over some 40 years, into one platform that can be used by data scientists and other analytics professionals; business users and IT management; and senior management.

IBM and the Massachusetts Institute Technology (MIT) are teaming up to advance the development of machine vision using insights from the brain and cognitive research. The multi-year partnership will see IBM Research collaborate with MIT's Department of Brain & Cognitive Sciences (BCS) to advance frontiers of artificial intelligence in real-world audio-visual comprehension technologies. The organisations are building a research laboratory for brain-inspired multimedia machine comprehension (BM3C) in Cambridge, Massachusetts. Together they plan to develop cognitive computing systems that mimic the human ability to understand and integrate input from several sources for use in various computer applications in industries like healthcare, education, and entertainment. MIT researchers will work with IBM scientists and engineers, who will offer technology expertise and advances from the IBM Watson platform.

Chatterbox Labs is a Cognitive data science company focused on delivering real world business outcomes that drive multi-million dollar outcomes. As a company we often find ourselves explaining the key differences between RPA and Cognitive. Fundamentally, RPA and Cognitive are two completely different offerings that both have merit, however, we describe RPA as the "Finger Tapping" as opposed to the "Brain Mapping" of Cognitive. RPA is a different and lower value proposition compared to Cognitive. Cognitive is built and ready to address 90% of the worlds data that is unstructured and not monetized…..RPA cannot address this market Cognitive is focused on processing 148K documents per second and achieving accuracy of 80% which is higher than human accuracy.

IBM and MIT announced a joint research partnership, with the aim of creating artificial intelligence that understands audio and visual data the way people do. At a high level, IBM Research and MIT's Department of Brain and Cognitive Sciences are forming the IBM-MIT Laboratory for Brain-inspired Multimedia Machine Comprehension's (BM3C). There, researchers will work to develop cognitive computing systems that can overcome the technical challenges surrounding pattern recognition and predictions methods. As IBM explains, a human can watch a short video of an event and easily describe what is happening during the video and even predict the likelihood of subsequent events. For machines, this ability is currently impossible, IBM says.