IBM has updated its artificial intelligence (AI) product, IBM Watson, giving it the ability to recognise images. Watson, which relies on cognitive learning to help it process the world in a human-like manner, can now'guess' what's happening in images fed to it via URLs. IBM has created a'Visual Recognition Demo' to showcase Watson's latest trick, which allows users to feed Watson an image before it tells you what it believes it sees. For example, supplying Watson with the image of a tiger throws up the result 77 per cent tiger, 26 per cent wild cat and 63 per cent cat. As well as identifying objects, people or animals in photos, Watson is also fairly adept at guessing what's going on in the background of images such as sunsets and other outdoor scenes.

Former top executives from IBM Watson, GE Digital, Infosys and MicroStrategy announced last week that they have joined forces with TPG Growth to launch Noodle Analytics, Inc., the Enterprise Artificial Intelligence company. Enterprise AI represents a major step forward in merging human learning and machine learning, all fueled by big data. Enterprise AI solutions combine expertise in human-centered design, business process engineering and artificial intelligence technologies. Today's artificial intelligence technologies include machine learning, predictive data analytics and data science. "Over the next three to five years, artificial intelligence technologies and big data will be the most significant competitive differentiators in business. We are excited to be a pioneer in Enterprise Artificial Intelligence, offering timely, valuable, and affordable solutions to clients. We have the right team, an optimized business model, and the right partners to create extraordinary value," says Stephen Pratt, CEO of Noodle.ai.

Today, we create a staggering amount of information: formulas, tweets, poetry, photos, videos and many more. Even our discoveries and diagnosis generate data. Can we draw meaning from it? That let's do things we've never done before. Overcome obstacles that used to stop us.

IBM announced that its Watson AI is getting image recognition capabilities earlier in the year, but this site that lets you feed in your own photos to see what it thinks is in them is both impressive and scary. The visual recognition demo lets you give Watson an image URL or upload a photo and it'll come back in a few seconds with what it thinks it sees. This year's edition of TNW Conference in Amsterdam includes some of the biggest names in tech. In my tests I fed Watson a few random photos I had on hand and the accuracy was quite surprising. It could figure out what was in landscape shots, animals (down to the breed) and even what's in the background.

Image recognition is a hot area of research using artificial intelligence, and now IBM offers an online demo to let anyone test out the capabilities offered by its Watson cognitive computing system. Six sample photos are provided for illustration, or you can upload your own and ask Watson to analyze them. Either way, the cognitive system will produce a series of "classifiers" offering descriptions of the image's contents along with confidence scores for each of them. You can also create custom classifiers tailored for specific purposes. Watson gained worldwide fame when it won on the quiz show Jeopardy back in 2011, and IBM has been developing commercial applications ever since.

IBM has updated its artificial intelligence (AI) product, IBM Watson, giving it the ability to recognise images. Watson, which relies on cognitive learning to help it process the world in a human-like manner, can now'guess' what's happening in images fed to it via URLs. IBM has created a'Visual Recognition Demo' to showcase Watson's latest trick, which allows users to feed Watson an image before it tells you what it believes it sees. For example, supplying Watson with the image of a tiger throws up the result 77 per cent tiger, 26 per cent wild cat and 63 per cent cat. As well as identifying objects, people or animals in photos, Watson is also fairly adept at guessing what's going on in the background of images such as sunsets and other outdoor scenes.

Last month I wrote an article describing the interfaces and capabilities of Microsoft and IBM's new cloud data science products. I observed that Azure ML presents a user-friendly drag and drop data mining app for businesses, while Watson Analytics focuses on natural language queries but is still too nascent for use. A similar query for "IBM Watson Analytics" turns up 730,000 documents. Amid the deluge of coverage on both services, one could lose sight of the many upstart companies offering cloud machine learning services. However, new product categories are typically pioneered by startups.

Higher-level cognition includes logical reasoning and the ability of question answering with common sense. The RatioLog project addresses the problem of rational reasoning in deep question answering by methods from automated deduction and cognitive computing. In a first phase, we combine techniques from information retrieval and machine learning to find appropriate answer candidates from the huge amount of text in the German version of the free encyclopedia "Wikipedia". In a second phase, an automated theorem prover tries to verify the answer candidates on the basis of their logical representations. In a third phase - because the knowledge may be incomplete and inconsistent -, we consider extensions of logical reasoning to improve the results. In this context, we work toward the application of techniques from human reasoning: We employ defeasible reasoning to compare the answers w.r.t. specificity, deontic logic, normative reasoning, and model construction. Moreover, we use integrated case-based reasoning and machine learning techniques on the basis of the semantic structure of the questions and answer candidates to learn giving the right answers.

In cooperation with the Association for the Advancement of Artificial Intelligence (AAAI), the Twenty-Second International Conference on Case-Based Reasoning (ICCBR), the premier international meeting on research and applications in case-based reasoning (CBR), was held from Monday September 29 to Wednesday October 1, 2014, in Cork, Ireland. ICCBR is the annual meeting of the CBR community and the leading conference on this topic. Started in 1993 as the European Conference on CBR and 1995 as ICCBR, the two conferences alternated biennially until their merger in 2010.