Intelligence in the cloud: Beyond the hype

If you follow developments in cloud architecture, you may have been hearing a lot recently on the importance of an “intelligent cloud” and an “intelligent edge.” Cloud providers who have traditionally focused on providing infrastructure and software have begun to realize that there is only so much value they can drive through these as-a-service offerings, and it is no surprise that the word “cognitive” has begun to creep into more marketing and speechifying on cloud.
But it’s important for developers and data scientists to be able to distinguish between the marketing and the reality of a truly cognitive cloud.
IBM is leading in artificial intelligence, with Watson’s deep domain expertise helping clients of every size, across all industries, every day.  Watson — which is available only on the IBM Cloud —has the full range of cognitive technology – ML, AI, cognitive — because that’s what is needed for decision making and transformative business outcomes.
Watson and the IBM Cloud represent the right, data-first combination for addressing these needs across industries and audiences. The value in clients’ data is not just in collecting and securing it, but also in extracting insights and knowledge from it for better decision-making. This is what IBM does. We want our clients to gain a competitive advantage through both data diversity and control. Just yesterday, for example, we announced the availability of Data Science Experience Local, a workplace designed to help data scientists more easily and quickly collaborate on analytic models that developers can use to build intelligent applications.
Our focus is on creating development environments in which it is easy for developers to navigate, create their apps and launch them – whether they are data scientists in a big bank, an analyst for a retailer, or a coder in a hospital system.
That’s also why we have the faster cloud for AI. Why is that important?
One of the key challenges in AI today is the time and cost of training a deep learning system. That’s where GPU technology on the cloud comes in. Just this week we announced that data scientists from IBM and Rescale conducted tests training deep learning models using the NVIDIA P100 GPU on the IBM Cloud and found a 2.8X performance gain — that could reduce deep learning training time by up to 65 percent. This is a major breakthrough in speed for the industry — showing IBM has the fastest cloud to run deep learning and is a major step toward reducing the cost and time required to train an AI system.
Edge analytics and the importance of Internet of Things (IoT) for a variety of industries is another topic du jour. We have been working closely with Cisco for more than a year to offer both Watson IoT analytics and Cisco edge analytics, bringing Watson capabilities to remote and autonomous operations on the edge of the computer network.
The reality is that no one has more experience and knowledge across industries than IBM. We offer a balanced platform, anchored by public, private and hybrid offerings, combined with the ability to deliver higher value cognitive services. AI, IoT, data analytics and blockchain, for us, are not added features, but are core to our cloud platform.
The IBM Cloud is also uniquely tuned to enterprises in highly regulated industries that face compliance or security challenges when adopting cloud infrastructure. That’s why we just launched Dedicated Hosts, a new offering that will provide enterprises with precise placement control of their cloud workloads. Unlike comparable offerings on the market, Dedicated Hosts on the IBM Cloud offer clients two distinct features including post-deployment control so they can move workloads at any time and the flexibility to deploy any size or combination of instances on the host.
As you listen to other cloud providers talk about intelligence in the cloud, remember to look beyond the hype and find the solution that is right for you.
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Quelle: Thoughts on Cloud