Tag: Watson

IBM calls in Watson for the IoT

Sherlock-Holmes-and-WatsonThe ever shrinking Biggish Blue wants to use advanced analytics  and its Watson platform to help partners and customers stand out in the crowded Internet of Things market.

Talking to the assembled throngs at IoTConnex, IBM’s business development leader IoT for Manufacturing and Industrial Products Raghbir Kern said that analytics and cognitive computing capabilities will be an essential part of IoT as industrial companies continue to connect their manufacturing floors.

“You may have heard of Industries 4.0 … this is a concept that focuses on the digitization of the modern manufacturing plant, which means you are connecting all your equipment, data, sensors. … We are taking that and adding on one more layer, cognitive computing, and really delivering on a vision of cognitive manufacturing that our customers have,” said Kern.

Customers were collecting data from multiple sources and are making that data transparent so they can see patterns and trends in the data and deliver better insight.

Kern said that companies will come to rely on tools like analytics. “In order to get to these later stages of cognitive manufacturing … you really have to take advantage of advanced analytics and cognitive technologies,” she said.

Partners have access to advanced analytics through IBM’s Watson Internet of Things platform, which incorporates both rule-based analytics, enabling customers to see what happens when one event occurs, or model-based analytics, which allows customers to predict future events.

With these tools, IBM Watson delivers three core cognitive manufacturing applications: using IoT to sense and diagnose issues so companies can optimise the performance of intelligent assets and equipment; using cognitive processes to bring more certainty to businesses through analysing a variety of information from workflows; and using insight to optimise resources.

IBM makes gold for Alchemy API

IBM logoBig Blue said it has bought a company that specialises in creating scalable cognitive computing application program interface (API) services and deep learning technology.

IBM said it has bought the company because it is complementary to its own development of next generation cognitive computing apps.

The move brings 40,000 developers into its own Watson framework.

The Denver based company was founded in 2005 and its software processes billions of API calls per month, IBM said. It’s available in eight different languages – English, French, German, Italian, Portuguese, Russian, Spanish, and Swedish.

IBM didn’t say how much it paid for AlchemyAPI but it will integrate the firm’s software into its own Watson offerings.

IBM claims email breakthrough

ibm-officeEnterprise email will never be the same again, IBM said, as it introduced a system it calls Verse.

The company said Verse is better for enterprises because it integrates the ways employees communicate every day – through email, meetings, calendars, file sharing, instant messaging, social networking and video chats.

It claims a single collaboration environment Verse includes so-called “faceted search” – a way of letting people pinpoint and recover information they want to know through the different kinds of content.

The software also comes with built in analytics, that learns how people prioritise items and their preferences to give a contextual view of a project and people collaborating on it.

This is different from other email services that simply search inboxes.

IBM will, in the future, embed its Watson feature into their overall environment. Watson is an analytic service that will give a reply to questions with answers ranked according to their importance.

IBM bets on Watson

Sherlock-Holmes-and-WatsonBig Blue is hoping that its AI based supercomputer Watson can come up with a few ideas which will help turn it around.

IBM  is taking a kicking from cheap cloud computing services and the outfit is  facing an uncertain future.

Apparently, IBM’s research division is building on the research effort that led to Watson, the computer that won in the game show Jeopardy! in 2011. The hope is that this effort will lead to software and hardware that can answer complex questions by looking through vast amounts of information containing subtle and disparate clues.

John Kelly, director of IBM Research told MIT Technology review  that IBM was betting billions of dollars, and a third of this division now is working on artificial intelligence techniques related to Watson.

Earlier this year the division was reorganised to ramp up efforts related to cognitive computing. The push began with the development of the original Watson, but has expanded to include other areas of software and hardware research aimed at helping machines provide useful insights from huge quantities of often-messy data.

So far, the research has created new recipes by analysing thousands of ingredients and popular meals, and, less interesting, electronic components, known as neurosynaptic chips, that have features modelled on the workings of biological brains and are more efficient at processing sensory information.

The hope is that the technology will be able to answer complicated questions in different industries, including health, financial markets, and oil discovery; and that it will help IBM build its new computer-driven consulting business.

There is a growing belief that machine-learning techniques may provide ways to use big data.  Already Google, Facebook, and Amazon have their own methods for hunting through vast quantities of data for useful insights.

So far those Watson has proved a bit elementary.  Some companies and researchers testing Watson systems have reported difficulties in adapting the technology to work with their data sets. However that has not stopped IBM’s CEO, Virginia Rometty, said in October last year that she expects Watson to bring in $10 billion in annual revenue in 10 years, even though that figure then stood at around $100 million.

IBM is aggressively commercialising the technology. Last week the company announced it had teamed up with Twitter and the Chinese social network Tencent to offer a service that will try to find useful insights from messages daily sent through these services, as we reported here. A company that sells phones might, for example, learn about a possible problem with one of its products from comments made by restaurant patrons.


Big Blue’s Big Data Lab reveals the Big Unknowns

ibm-officeEver had the feeling there were things afoot that were unknown to you? You’re not alone. But fear not, for the good folk of IBM have pulled a Big Blue Rabbit out of the Big Data Hat for you.

The world’s favourite international business machines have opened a new lab called the Accelerated Discovery Lab. One of the most remarkable things about it might even be its name, which – unlike so much of what goes on in the technology sector – seems related to what it does.

The lab will offer “diverse data sources, unique research capabilities for analytics such as domain models, text analytics and natural language processing capabilities derived from Watson, a powerful hardware and software infrastructure, and broad domain expertise including biology, medicine, finance, weather modeling, mathematics, computer science and information technology,” said IBM, presumably just before it passed out. Don’t forget to breath, dear.

By making it possible for organisations to take their data and mix it with these vast and disparate data sources, the Accelerated Discovery Lab will make it possible to start to identify hitherto unknown relationships among the data.

That could be to find seasonal patterns in purchasing behaviour that go beyond the obvious, such as people buy ice cream and shorts in summer. Or it could be combining social media insights with psychology data in an attempt to create meaningful customer profiling. Or it might be finding statistically robust segmentation that takes you further than ‘our target market is men in the 35-50 age bracket.’

At the moment, analysing Big Data can mean relying on a fairly manual approach to the massive amounts of data, gathered from a broad variety of channels. Whether you’re a business or a researcher, this is a testing and expensive process with precious little in the way of meaning or value waiting for you at the end.

There is obvious appeal in being able to accelerate that process.

“If we think about Big Data today, we mostly use it to find answers and correlations to ideas that are already known. Increasingly what we need to do is figure out ways to find things that aren’t known within that data,” said Jeff Welser, Director, Strategy and Program Development, IBM Research Accelerated Discovery Lab.

And to think how people laughed at Donald Rumsfeld when he said something not too dissimilar.