Cleveland Clinic to use IBM Watson for Genomic Research: Researchers at Cleveland Clinic will use IBM Watson technology in the area of genomic research to help oncologists deliver personalized medicine by uncovering new cancer treatment options for patients. The Lerner Research Institute's Genomic Medicine Institute at Cleveland Clinic plans to evaluate Watson's ability to help oncologists develop more personalized care to patients for a variety of cancers. Clinicians lack the tools and time required to bring DNA-based treatment options to their patients and to do so, they must correlate data from genome sequencing to reams of medical journals, new studies and clinical records. At a time when medical information is doubling every five years, a faster option is needed. This use of Watson aims to find the "needle in the haystack" through identifying patterns in genome sequencing and medical data to unlock insights that will help clinicians bring the promise of genomic medicine to their patients.

Watson has it's visualisation tool called WatsonPaths to show how it has derived answers logically. AI needs large amounts of data and Google, Facebook and Amazon are sitting very pretty in this space. IBM will probably be unable to match either of the 3 – but if it becomes an industry expert – it will mint money in the more expensive and much needed business vertical. To be fair, IBM seems to be transparent on this topic. In this case – they're rolling it out for free!!! Well – upto a point IBM Bluemix services helps with development of a rapid prototype solution.

We begin with a case study exploring the recently popular task of image captioning and its limitations as a task for measuring machine intelligence. An alternative and more promising task is Visual Question Answering that tests a machine's ability to reason about language and vision. We describe a dataset unprecedented in size created for the task that contains over 760,000 human generated questions about images. Using around 10 million human generated answers, machines may be easily evaluated.

As machines have become more intelligent, there has been a renewed interest in methods for measuring their intelligence. A common approach is to propose tasks for which a human excels, but one which machines find difficult. However, an ideal task should also be easy to evaluate and not be easily gameable. We begin with a case study exploring the recently popular task of image captioning and its limitations as a task for measuring machine intelligence. An alternative and more promising task is Visual Question Answering that tests a machine’s ability to reason about language and vision. We describe a dataset unprecedented in size created for the task that contains over 760,000 human generated questions about images. Using around 10 million human generated answers, machines may be easily evaluated.

Amazon recently announced Amazon Machine Learning, a cloud machine learning solution for Amazon Web Services. Able to pull data effortlessly from RDS, S3 and Redshift, the product could pose a significant threat to Microsoft Azure ML and IBM Watson Analytics. Upon selecting a model, the service asks whether the user would like to holdout data for validation from the training set or to provide holdout data from a different source. Once these selections are made, Amazon ML trains the model on the given dataset. Using the sample dataset of dummy bank customers (5MB in size), training takes roughly 10 minutes. When evaluating the evaluation metric for a binary classification task, Amazon ML reports the area under the ROC curve (AUC).

Looking at the performance of IBM shares over the past five years, it is clear that a change in strategy is needed. IBM's share price is down approximately 9% since 2011 compared to a 54% gain in the S&P 500. The goal of this article is to develop a strategy for IBM to leverage the power of IBM Watson artificial intelligence to stage a comeback. The proliferation of cloud, social and mobile technologies have led to the most successful and innovative companies becoming increasingly concerned with the ability to successfully build a digital platform. Apple, Google, Facebook and Amazon each created platforms that co-create value by connecting to other business who can build products and services on their platforms.

When you think about it, the tech world has a lot in common with old-time religion. There are impassioned camps -- think Android vs. iOS or Mac vs. Windows -- devoted to a particular software or hardware platform. And tech conferences that attract the faithful often embrace the fevered intensity of a tent revival. This isn't a bad thing, of course, as a little enthusiasm never hurt anybody. And it makes sense that major companies, including IBM, hire charismatic, persuasive individuals as evangelists to spread the word about their products and services.

Every 60 seconds, Facebook users share 2,460,000 pieces of content and Yelp receives 26,380 reviews. Then there's the 2 million blog posts created each day and the 1 billion websites available for us to peruse. With all of this content floating around the internet, marketers struggle to truly engage and convert an increasingly fragmented online audience. Using Watson services, Opentopic helps clients solve that problem in a 2-step process. First, they help the client discover and analyze target audiences.

IBM's Watson just gave doing the robot a whole new twist. While dancing has never been a forte of machines, IBM's artificial intelligence system is proving that robots really can have fun (even if it has to be programmed in). In a demo presented during Nvidia's GTU technology conference, IBM Watson's chief technology officer, Rob High, showed off a concierge robot named Watson Nao, whose many talents include singing and dancing -- all in an attempt to humanize these humanoids. The multi-lingual robot is powered by IBM Watson, and the AI has come a long way since winning Jeopardy back in 2011. Now, Watson is on a mission to show that it's more than just a super impressive brain -- it's kinda like you and me, too!

As data grows, organizations are increasingly seeking for an intelligent information discovery and analytics platform that goes beyond keyword searches and better understands users' intent. With Google Now and Cortana, advanced question answering systems are starting to become ubiquitous. Recently, Gartner has also started discussing'insight engines,' a new technology that can provide natural, total, and proactive search, analytics, and discovery. Please let us know the email address we should be sending a PDF copy of the white paper to. A download link will be immediately emailed to you - please check your junk mail if you have a strong email filter.