Articles about IBM

IBM has announced its commitment to a multi-million pound project that will see the company construct four new data centers in the UK to increase its cloud capabilities in the region.

The company revealed its new project ahead of the Autumn Statement, which offered a boost to the Government that has recently seen a number of large US technology companies increasing their operations in the country. IBM's decision to create four new data centers will triple its cloud computing capacity in the UK.

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Businesses are turning to the cloud as a way of coping with ever larger amounts of data. But moving to the cloud at the same time retaining control of where data resides and how it’s accessed is a challenge.

To help enterprises migrate and more easily generate business insights, IBM is announcing a range of new services on its Bluemix cloud platform.

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IBM's Watson project has been a leader in cognitive computing, enabling machines to understand the world in a similar way to humans.

Today the company is unveiling the experimental release of Project Intu, a new, system-agnostic platform designed to allow developers to embed Watson functions into various end-user device form factors, offering a next generation architecture for building cognitive-enabled experiences.

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Amazon Web Services is the undisputed leader in the public cloud market, with a market share larger than the next three competitors -- Microsoft, Google and IBM -- combined, according to a new report from Synergy Research Group.

In Q3 2016, AWS had a share of around 45 percent in the public IaaS (infrastructure as a service) market, while Microsoft's Azure, Google's Cloud and IBM's cloud did not even get past the 20 percent mark.

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Businesses today face having to deal with huge quantities of documents and data. Gaining meaningful insights from this pool of information can therefore be a major challenge.

Enterprise search specialist Lucidworks is aiming to make sense of things by using the IBM Watson Developer Cloud platform for its Fusion application framework to help developers create enterprise discovery applications so companies can better understand their data.

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Addressing endpoint vulnerabilities is a major challenge for businesses, often compounded by a lack of visibility into which devices are being actively exploited.

According to Gartner 99 percent of vulnerabilities exploited are ones that professionals have known about for a year, but have lacked the solutions to address.

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In an attempt to improve its financial capabilities, IBM will acquire the Promontory Financial Group which will be integrated with its global business and will aid in training its Watson artificial intelligence (AI) platform. The company announced the acquisition on Thursday but it did not disclose the financial terms of the deal.

Promontory was founded by Eugene A. Ludwig, who is a former top banking regulator and a friend of of former President Bill Clinton from law school. The Washington firm became one of the leading financial organizations following the 2008 financial crisis. Promontory's current employees include many former financial regulators from across the globe, and it has advised numerous banks on regulatory matters.

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Five of the biggest names in the world of technology have joined forces to create the Partnership on AI. The aim of the group is to increase public awareness of artificial intelligence, conduct research, and promote best practice guidelines.

Comprising Amazon, Google, Facebook, IBM and Microsoft -- although, interestingly, not Apple -- the group says that it does not intend to lobby government or government bodies. Instead, the aim is to promote AI so that it can be used to "help humanity address important global challenges such as climate change, food, inequality, health, and education".

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When it comes to corporate IT security, one of the biggest pain points is the mobile device. With almost every employee having one, and many bringing their own, the cyber-attack surface increases dramatically, putting corporate data at huge amounts of risk. Now, IBM is stepping into the game with a service of its own, which aims to protects mobile devices, via IBM Cloud.

The mobile-security-as-a-service, called IBM MaaS360, aims to help IBM’s clients address local data protection standards. It is currently in operation in the US, Germany and Singapore, with France and India already in the works. They will be followed by an "additional eight countries" planned for the next two years. IBM didn’t go into further detail, but we’re hoping the UK will be among them.

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IBM introduced a series of new servers dubbed "x86 killers". The devices, designed to give a significant boost to artificial intelligence, deep learning and advanced data analytics, were picked up by the Chinese telecommunications company Tencent, and IBM claims the results are basically out of this world.

"A large cluster of the new IBM OpenPOWER servers was able to run a data-intensive workload three times faster than its former x86-based infrastructure", IBM says in a press release. "While reducing the total number of servers used by two-thirds".

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Thanks to a new partnership between Box and IBM, Box users will be getting a new workflow solution which will allow any business users to build, manage and track custom and pre-built workflows.

The new solution, called Box Relay, will be a part of the "all new Box", to be presented during BoxWorks 2016, Box's annual San Francisco conference.

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I have a TV producer friend I worked with years ago who at some point landed as one of the many producers of American Idol when that singing show was a monster hit dominating U.S. television. She later told me an interesting story about Carrie Underwood, the country-western singer who won American Idol Season 4. That story can stand as a lesson applicable to far more than just TV talent shows. It’s especially useful for the purposes of this column for explaining IBM’s Watson technology and associated products.

You see the producers of American Idol Season 4 knew before the season was half over that Underwood would win. And, by the same token, I’m about to argue that IBM already knows that its Watson artificial intelligence technology has lost. In each case they chose not to tell us.

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After it was reported that China has the world’s fastest supercomputer, IBM unveiled a few details about its upcoming behemoth, which is already branded as the computer that will dethrone the Chinese Sunway TaihuLight.

IBM's supercomputer is called Summit. It is expected to reach US Department of Energy’s Oak Ridge National Laboratory in early 2018, and should have a quarter more computational power than originally intended.

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Rumors are flying within IBM this week that the z Systems (mainframe) division is up for sale with the most likely buyer being Hitachi. It’s all a big secret, of course, because IBM management doesn’t tell IBM workers anything, but the idea is certainly consistent with Big Blue’s determination to cut costs and raise cash for more share buybacks. And the murmurs are simply too loud to be meaningless. Think of this news in terms of a statement made last week by an IBM senior executive: "In a world of Cloud Computing, it does not matter what equipment or whose hardware the cloud runs on. We are a Cloud company…"

This move by IBM would not surprise me in a bit. It is my guess IBM wants someone else to make and support the hardware. They’ll be happy to sell time sharing services, AKA cloud services. They’ll be happy to let someone else sell and maintain systems.

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There is a difference between knowledge and understanding. Knowledge typically comes down to knowing facts while understanding is the application of knowledge to the mastery of systems. You can know a lot while understanding very little. Just as an example, IBM’s Watson artificial intelligence system that defeated the TV Jeopardy champs a few years ago knew all there was to know about Jeopardy questions but didn’t really understand anything. Ask Watson to apply to removing your appendix its knowledge of hundreds of medical questions and you’d be disappointed and probably dead. That’s the problem with most analytics, which is why it can be a hard sell.

The answer to this problem, we’re told, is not just machine learning but Deep Machine Learning, the difference between the two being that plain old machine learning is a statistical process that could be (and used to be) replicated by hand, while the deeper variety looks several generations deep in a longitudinal analysis that quickly grows too big for mere mortals to comprehend. Deep machine learning will, theoretically, find all the interconnections and dependencies that until now we’ve had to rely on domain experts to provide, yet even then it can only happen if you happen to be gathering the right data.

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