We investigate case-based reasoning (CBR) problems where cases are represented by abstract factors and (positive or negative) outcomes, and an outcome for a new case, represented by abstract factors, needs to be established. To this end, we employ abstract argumentation (AA) and propose a novel methodology for CBR, called AA-CBR. The argumentative formulation naturally allows to characterise the computation of an outcome as a dialogical process between a proponent and an opponent, and can also be used to extract explanations for why an outcome for a new case is (not) computed.

AlchemyLanguage is a collection of APIs that offer text analysis through natural language processing. The AlchemyLanguage APIs can analyze text and help you to understand its sentiment, keywords, entities, high-level concepts and more.

Not every startup CEO can say they were able to grow their business to a point where they were acquired. Even fewer can say they did it twice. But that is exactly the case for AlchemyAPI Founder and CEO Elliot Turner. Turner launched his first startup, MimeStar, a software development company focused on network intrusion detection, while a sophomore in high school. Inc. acquired it by the time he was twenty-one. He quickly saw the shift in the market to the need to democratize artificial intelligence (A.I.), and decided to venture out on his own to start AlchemyAPI.

I would like to propose that Watson could solve one of the biggest challenges facing anyone trying to innovate and product their innovation with a US patent - the USPTO first office action. While everyone is working hard and I know the patent office is overloaded, here how three problems I've seen over my years of working that perhaps Watson could address: 1) Speed - it can take 6-12 months to get a first office action 2) Almost any patent application is nowadays first rejected due to obviousness. But the patents cited to create this argument are often taken out of context. To me, these seem like challenges that Watson would be perfectly designed to addressed. And all the literature to be reviewed is, by definition, in the public domain.

This is the direction of the future. Useful AI that can do the research of a thoudand men instantly. It's definitely worth noting that Watson is capable of learning (a point I didn't touch on in this video), so what you see here is the "baby phase" so to speak. I tried to leave out the technical jargon in this video but for those who want to know more, a wiki dump on Watson is below: According to John Rennie, Watson can process 500 gigabytes, the equivalent of a million books, per second. Software Watson uses IBM's DeepQA software and the Apache UIMA (Unstructured Information Management Architecture) framework.

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.

DUBAI – The teaching methods of Kazuya Takahashi, 35, using Lego blocks and speaking entirely in English, may not be the norm in the Japanese education system. But on a global level, the educator, who teaches at the Kogakuin junior high and high schools in Hachioji, western Tokyo, is considered ahead of the game and has won recognition for his efforts to promote global citizenship. His methods may provide clues as to where education should be heading in Japan, a nation often criticized for focusing more on cramming knowledge rather than encouraging critical thinking. At the Global Education and Skills Forum in Dubai, which ran for two days from March 12, Takahashi gave a presentation as one of the 10 finalists for the Global Teacher Prize, known in the industry as the Nobel Prize in education. The event was attended by around 1,600 people from 110 nations.

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.