IBM’s smart assistant is called…Watson Assistant

You saw this one coming, right? This week at its Think 2018 Conference in Las Vegas, IBM showed off its own take on the growing smart assistant category, aimed firmly at enterprise applications. Naturally, the company’s using the Watson name for the offering, and tacking on “Assistant” for good measure.

Unlike Alexa, Siri and Google’s own offering of the same name, however, Watson Assistant won’t be a chipper, consumer-facing offering loaded up on IBM-branded smart speakers. Rather, the company’s plan here is to operate mostly behind the scenes, white labeling the technology for use by companies.

In fact, the offering is so behind-the-scenes that IBM’s already rolled it out in a bunch of spots, including the Munich Airport and the Royal Bank of Scotland. The big Think unveiling also finds the company adding IFTTT as a partner along with Harman — a bit of an odd choice, given that its parent company has its own smart assistant. But then, Bixby is, well, Bixby

The plan is to make Watson Assistant the foundation of voice-based offerings in places like hotel rooms, stores and cars, so company can leverage IBM’s technology to build their own custom solutions. It’s precisely what IBM’s been gunning for with Watson — a way to make its sophisticated underlying technology more readily available to the consumer.

“The contextual element is important,” the company said in a release announcing the offering. “Watson Assistant isn’t just designed for a single location such as your home. And, it doesn’t just respond to a person’s commands and provide generic information that’s publicly available. It can be accessed via voice or text interaction and gets to know a person more through each and every interaction, gaining greater insight into who they are, what makes them happy and more.”

IBM brings its Power9 servers with Nvidia GPUs to its cloud

IBM is hosing its annual THINK conference to packed halls in Las Vegas this week. Given how important its cloud business has become to its bottom line, it’s no surprise that this event features its fair share of cloud news. Among today’s announcements it the launch of the third generation of Power Systems servers in the IBM Cloud. This comes a day after Google also confirmed that it is using these processors in its data centers, too.

These servers are designed around the recently launched Power9 RISC processor (which are themselves the latest generation of the PowerPC processors Apple once used) and Nvidia Tesla V100 GPUs. Thanks to their use of the high-speed NVLink interface, these machines are especially powerful when it comes to training machine learning models.

In addition, IBM is also bringing its PowerAI distribution to the cloud. PowerAI is essentially IBM’s deep learning platform that supports frameworks like TensorFlow, Torch and Caffe, as well as IBM’s own deep learning frameworks. Given that PowerAI has long been optimized for exactly the kind of Power servers IBM is now bringing to its Cloud (the AC922, to be exact), it’s no surprise that PowerAI will be available in the Cloud, too.

IBM launches deep learning as a service inside its Watson Studio

IBM’s Watson Studio is the company’s service for building machine learning workflows and training models, is getting a new addition today with the launch of Deep Learning as a Service (DLaaS). The general idea here, which is similar to that of competing services, is to enabled a wider range of businesses to make user of recent advances in machine learning by lowering the barrier of entry.

With these new tools, developers can develop their models with the same open source frameworks they are likely already using (think TensorFlow, Caffe, PyTorch, Keras etc.). Indeed, IBM’s new service essentially offers these tools as cloud-native services and developers can use a standard Rest API to train their models with the resources they want — or within the budget they have. For this service, which offers both a command-line interface, Python library or interactive user interface, that means developers get the option to choose between different Nvidia GPUs, for example.

The idea of a managed environment for deep learning isn’t necessarily new, With the Azure ML Studio, Microsoft offers a highly graphical experience for building ML models, too, after all. IBM argues that its service offers a number of distinct advantages, though. Among other things, the service offers a drag-and-drop neural network builder that allows even non-programmers to configure and design their neural networks.

In addition, IBM’s tools will also automatically tune hyperparameters for its users. That’s traditionally a rather time-consuming processes when done by hand and something that sits somewhere between art and science.

Apple, IBM add machine learning to partnership with Watson-Core ML coupling

Apple and IBM may seem like an odd couple, but the two companies have been working closely together for several years now. That has involved IBM sharing its enterprise expertise with Apple and Apple sharing its design sense with IBM. The companies have actually built hundreds of enterprise apps running on iOS devices. Today, they took that friendship a step further when they announced they were providing a way to combine IBM Watson machine learning with Apple Core ML to make the business apps running on Apple devices all the more intelligent.

The way it works is a customer builds a machine learning model using Watson, taking advantage of data in an enterprise repository to train the model. For instance, a company may want to help field service techs point their iPhone camera at a machine and identify the make and model to order the correct parts. You could potentially train a model to recognize all the different machines using Watson’s image recognition capability.

The next step is to convert that model into Core ML and include it in your custom app. Apple introduced Core ML at the Worldwide Developers Conference last June as a way to make it easy for developers to move machine learning models from popular model building tools like TensorFlow, Caffe or IBM Watson to apps running on iOS devices.

After creating the model, you run it through the Core ML converter tools and insert it in your Apple app. The agreement with IBM makes it easier to do this using IBM Watson as the model building part of the equation. This allows the two partners to make the apps created under the partnership even smarter with machine learning.

“Apple developers need a way to quickly and easily build these apps and leverage the cloud where it’s delivered. [The partnership] lets developers take advantage of the Core ML integration,” Mahmoud Naghshineh, general manager for IBM Partnerships and Alliances explained.

To make it even easier, IBM also announced a cloud console to simplify the connection between the Watson model building process and inserting that model in the application running on the Apple device.

Over time, the app can share data back with Watson and improve the machine learning algorithm running on the edge device in a classic device-cloud partnership. “That’s the beauty of this combination. As you run the application, it’s real time and you don’t need to be connected to Watson, but as you classify different parts [on the device], that data gets collected and when you’re connected to Watson on a lower [bandwidth] interaction basis, you can feed it back to train your machine learning model and make it even better,” Naghshineh said.

The point of the partnership has always been to use data and analytics to build new business processes, by taking existing approaches and reengineering them for a touch screen.

“This adds a level of machine learning to that original goal moving it forward to take advantage of the latest tech. “We are taking this to the next level through machine learning. We are very much on that path and bringing improved accelerated capabilities and providing better insight to [give users] a much greater experience,” Naghshineh said.

IBM Unveils the ‘World’s Smallest Computer’

On the first day of IBM Think 2018, the company's flagship conference, IBM has unveiled what it claims is the world's smallest computer. It's smaller than a grain of salt and features the computer power of the x86 chip from 1990. Mashable first spotted this gem: The computer will cost less than ten cents to manufacture, and will also pack "several hundred thousand transistors," according to the company. These will allow it to "monitor, analyze, communicate, and even act on data." It works with blockchain. Specifically, this computer will be a data source for blockchain applications. It's intended to help track the shipment of goods and detect theft, fraud, and non-compliance. It can also do basic AI tasks, such as sorting the data it's given. According to IBM, this is only the beginning. "Within the next five years, cryptographic anchors -- such as ink dots or tiny computers smaller than a grain of salt -- will be embedded in everyday objects and devices," says IBM head of research Arvind Krishna. If he's correct, we'll see way more of these tiny systems in objects and devices in the years to come. It's not clear yet when this thing will be released -- IBM researchers are currently testing its first prototype.

Read more of this story at Slashdot.

IBM working on ‘world’s smallest computer’ to attach to just about everything

IBM is hard at work on the problem of ubiquitous computing, and its approach, understandably enough, is to make a computer small enough that you might mistake it for a grain of sand. Eventually these omnipresent tiny computers could help authenticate products, track medications and more.

Look closely at the image above and you’ll see the device both on that pile of salt and on the person’s finger. No, not that big one. Look closer:

It’s an evolution of IBM’s “crypto anchor” program, which uses a variety of methods to create what amounts to high-tech watermarks for products that verify they’re, for example, from the factory the distributor claims they are, and not counterfeits mixed in with genuine items.

The “world’s smallest computer,” as IBM continually refers to it, is meant to bring blockchain capability into this; the security advantages of blockchain-based logistics and tracking could be brought to something as benign as a bottle of wine or box of cereal.

A schematic shows the parts (you’ll want to view full size).

In addition to getting the computers extra-tiny, IBM intends to make them extra-cheap, perhaps 10 cents apiece. So there’s not much of a lower limit on what types of products could be equipped with the tech.

Not only that, but the usual promises of ubiquitous computing also apply: this smart dust could be all over the place, doing little calculations, sensing conditions, connecting with other motes and the internet to allow… well, use your imagination.

It’s small (about 1mm x 1mm), but it still has the power of a complete computer, albeit not a hot new one. With a few hundred thousand transistors, a bit of RAM, a solar cell and a communications module, it has about the power of a chip from 1990. And we got a lot done on those, right?

Of course at this point it’s very much still a research project in IBM’s labs, not quite a reality; the project is being promoted as part of the company’s “five in five” predictions of turns technology will take in the next five years.

IBM launches bare metal Kubernetes

Containers are quickly becoming the standard way for deploying new applications in the cloud and that’s even true for the most traditional of enterprises. It’s no surprise then that every major cloud provider is betting on containers — and more specifically on the open source Kubernetes container orchestration service. IBM has long offered its own […]

AI will create new jobs but skills must shift, say tech giants

 AI will create more jobs than it destroys was the not-so-subtle rebuttal from tech giants to growing concern over the impact of automation technologies on employment. Execs from Google, IBM and Salesforce were questioned about the wider societal implications of their technologies during a panel session here at Mobile World Congress.  Read More