IBM and SK Holdings C&C, a South Korean IT services company, are planning to bring IBM's Watson cognitive technology language services to South Korean banking. The alliance, which includes training Watson to understand Korean, is designed to "dramatically accelerate" the adoption of cognitive computing throughout the region, giving South Korea-based developers a set of localised APIs and services they can use to help create their own applications and build new businesses. David Kenny, general manager, IBM Watson, says: "The South Korean marketplace is moving quickly to embrace the disruptive opportunities from next generation technology. Our strategic alliance with SK Holdings C&C will put cognitive services in the hands of more businesses and developers." SK Holdings C&C will run Watson and IBM Bluemix from its Pangyo Cloud Center, in support of universities, developers, and local businesses, across "diverse" industries including banking.

It's no secret that much of the wisdom of the world lies in unstructured data, or the kind that's not necessarily quantifiable and tidy. So it is in cybersecurity, and now IBM is putting Watson to work to make that knowledge more accessible. Towards that end, IBM Security on Tuesday announced a new year-long research project through which it will collaborate with eight universities to help train its Watson artificial intelligence system to tackle cybercrime. Knowledge about threats is often hidden in unstructured sources such as blogs, research reports and documentation, said Kevin Skapinetz, director of strategy for IBM Security. "Let's say tomorrow there's an article about a new type of malware, then a bunch of follow-up blogs," Skapinetz explained.

It's no secret that much of the wisdom of the world lies in unstructured data, or the kind that's not necessarily quantifiable and tidy. So it is in cybersecurity, and now IBM is putting Watson to work to make that knowledge more accessible. Towards that end, IBM Security on Tuesday announced a new year-long research project through which it will collaborate with eight universities to help train its Watson artificial-intelligence system to tackle cybercrime. Knowledge about threats is often hidden in unstructured sources such as blogs, research reports and documentation, said Kevin Skapinetz, director of strategy for IBM Security. "Let's say tomorrow there's an article about a new type of malware, then a bunch of follow-up blogs," Skapinetz explained.

As you may read from our first article farming robots are shaping agriculture and will feed humans of the future. Economics will demand a leap from theoretical concept of artificial intelligence to its practical application in agriculture, many experts suggest. But this process has already begun and is irreversible. Automated irrigation systems, crop health monitoring, face recognition systems for domestic cattle, CBR systems for fishing industry and many others are clear examples of how AI can be the Holy Grail for the farming industry. Irrigation systems are as old as man itself since agriculture is the foremost occupation of civilized humanity.

IBM will launch a Korean version of its AI platform Watson next year in cooperation with local IT service vendor SK C&C, the companies have announced. SK announced Monday that it signed a cooperation agreement with Big Blue on May 4 and will together build an integrated system to market Watson in South Korea. They will develop Korean data analysis solutions based on machine learning and natural language semantic analysis technology for Watson within this year, and will commercialise it sometime in the first half of 2017, SK said. IBM and SK will also build a "Watson Cloud Platform" at the Korean company's datacentre in Pangyo -- the local version of Silicon Valley -- that IT developers and managers can access to make their own applications. For example, an open market business can apply the Watson solution to its product search features to make a personalized contents recommendation solution.

The first Monday in May brings one of the marquee fashion events of the year -- the Met Gala. Held at the Metropolitan Museum of Art in New York City as a benefit for the museum's Costume Institute, this year's gala comes with an unexpected high-tech twist. The theme of the evening, and the accompanying museum exhibition, is "Manus x Machina: Fashion in an Age of Technology." In keeping with the theme is a rather unlikely collaboration -- IBM is joining forces with the fashion house Marchesa, known for its whimsical, romantic designs. For Monday's event, Marchesa designers and co-founders Georgina Chapman and Keren Craig teamed up with IBM's cognitive computing system Watson to design a "cognitive dress" that will be worn by a yet-to-be-named model.

Reinforcement learning (RL) is a popular choice for solving robotic control problems. However, applying RL techniques to controlling humanoid robots with high degrees of freedom remains problematic due to the difficulty of acquiring sufficient training data. The problem is compounded by the fact that most real-world problems involve continuous states and actions. In order for RL to be scalable to these situations it is crucial that the algorithm be sample efficient. Model-based methods tend to be more data efficient than model-free approaches and have the added advantage that a single model can generalize to multiple control problems. This paper proposes a model approximation algorithm for continuous states and actions that integrates case-based reasoning (CBR) and Hidden Markov Models (HMM) to generalize from a small set of state instances. The paper demonstrates that the performance of the learned model is close to that of the system dynamics it approximates, where performance is measured in terms of sampling error.

This paper presents a novel approach to retrieval in process-oriented case-based reasoning (POCBR) which considers the adaptability of workflows cases during the retrieval phase. A novel concept of adaptability in POCBR is proposed, which assesses the potential similarity increase of a case which can be gained by adaptation. The adaptability of a case is learned from the case base in an off-line pre-processing phase prior to the retrieval. The proposed approach is generic as it can be used in combination with different adaptation methods. An empirical evaluation in the domain of cooking workflows demonstrates the benefit of the approach.

Explanations play an important role in AI systems in general and case-based reasoning (CBR) in particular. They can be used for reasoning by the system itself or presented to the user to explain solutions proposed by the system. In our work we investigate the approach where causal explanations are automatically extracted from textual incident reports and reused in a CBR system for incident analysis. The focus of this paper is evaluation of such explanations. We propose an automatic evaluation measure based on the ability of explanations to provide an explicit connection between the problem description and the solution parts of a case.

IBM Japan has teamed up with Subaru to investigate how its Watson Supercomputer could help improve the automaker's EyeSight driver assist technology. As well as developing a data analytics system, the two companies are keen to integrate cloud and artificial intelligence technologies, which bodes well for the ongoing development of autonomous, networked cars. The benefits of networked autonomous vehicles were recently demonstrated by the European Truck Platooning Challenge, where teams of autonomous trucks made their way from their respective factories to Rotterdam. As well as demonstrating the fact autonomous vehicles can effectively make long trips without causing the end of the world (shocking, we know), the trucks were able to maintain a gap of just 15 m (49 ft) and react to sudden braking manoeuvres in just 0.1 seconds thanks to a WiFi connection keeping them all linked. Daimler has also invested in Car-to-X technology, which features in its latest E-Class.