Deep learning systems have long been tough to work with, due to all the fine-tuning and knob-twiddling needed to get good results from them. Gluon is a joint effort by Microsoft and Amazon Web Services do reduce all that fiddling effort.Gluon works with the Apache MXNet and Microsoft’s Cognitive Toolkit frameworks to optimize deep-learning network training on those systems.[ Go deep into machine learning at InfoWorld: 11 must-have machine learning tools. • 13 frameworks for mastering machine learning • Machine learning pipelines demystified • Review: 6 machine learning clouds • Which Spark machine learning API should you use? ]How Gluon worksNeural networks, like those used in deep learning systems, work in roughly three phases: The developer hard-codes the behavior of the network. The developer adjusts how the data is weighted and handled by the network, by changing settings to produce useful results. The finished network is used to serve … [Read more...] about Gluon brings AI developers self-tuning machine learning
The power of machine learning comes at a price. Once you have the skills, the toolkit, the hardware, and the data, there is still the complexity involved in creating and fine-tuning a machine learning model.But if the whole point of machine learning is to automate tasks that previously required a human being at the helm, wouldn’t it be possible to use machine learning to take some of the drudgework out of machine learning itself?[ Review: TensorFlow, Spark MLlib, Scikit-learn, MXNet, Microsoft Cognitive Toolkit, and Caffe machine learning and deep learning frameworks. | Roundup: 13 frameworks for mastering machine learning. | Cut to the key news and issues in cutting-edge enterprise technology with the InfoWorld Daily newsletter. ]Short answer: a qualified yes. A collection of techniques, under the general banner of “automated machine learning,” or AML, can reduce the work needed to prepare a model and refine it incrementally to improve its accuracy.Automated machine … [Read more...] about 6 machine learning projects to automate machine learning
What we call machine learning can take many forms. The purest form offers the analyst a set of data exploration tools, a choice of ML models, robust solution algorithms, and a way to use the solutions for predictions. The Amazon, Microsoft, Databricks, Google, and IBM clouds all offer prediction APIs that give the analyst various amounts of control. HPE Haven OnDemand offers a limited prediction API for binary classification problems. Not every machine learning problem has to be solved from scratch, however. Some problems can be trained on a sufficiently large sample to be more widely applicable. For example, speech-to-text, text-to-speech, text analytics, and face recognition are problems for which "canned" solutions often work. Not surprising, a number of machine learning cloud providers offer these capabilities through an API, allowing developers to incorporate them in their applications. [ The InfoWorld reviews: IBM Watson stakes again. • Azure Machine Learning is for … [Read more...] about Review: AWS, Microsoft, Databricks, Google, HPE, IBM machine learning
Developers longing to build more intelligent, more proactive, more personalized apps seem to gain more options with every passing day. With Haven OnDemand, Hewlett-Packard Enterprise (HPE) has joined the applied machine learning fray, competing directly with IBM Watson Services, Microsoft Cortana Analytics Suite, and several Google ML-based APIs. Haven OnDemand is a platform for building cognitive computing solutions using text analysis, speech recognition, image analysis, indexing, and search APIs. While IBM based its cognitive computing/machine learning cloud services primarily on Watson, the “Jeopardy” winner, HPE based its recently announced Haven OnDemand services primarily on IDOL, its enterprise search engine. [ The InfoWorld review roundup: AWS, Microsoft, Databricks, Google, HPE, and IBM machine learning in the cloud. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ] … [Read more...] about Review: HPE’s machine learning cloud overpromises, underdelivers
The IBM Watson AI system drew the world’s attention by winning at "Jeopardy" in February 2011 against two of the game’s all-time champions, and IBM has strived to apply the Watson system to more interesting problems than a trivia quiz ever since. IBM has also extended Watson’s capabilities to developers, data scientists, and even ordinary business users. Along with IBM’s SPSS predictive analytics software, Watson forms the foundation of IBM’s cloud offerings in machine learning and advanced analytics. IBM breaks the Watson system into five parts: machine learning, question analysis, natural language processing, feature engineering, and ontology analysis. From these parts, IBM has built out a suite of composable cloud services from which you can make your own mini-Watson for a solution to your problem. (Note that compiling the knowledge base for the answers is easy: 95 percent of "Jeopardy" questions can be answered by the titles of Wikipedia articles.) … [Read more...] about Review: IBM Watson lowers the bar to machine learning
You’re not a data scientist. Supposedly according to the tech and business press, machine learning will stop global warming, except that’s apparently fake news created by China. Maybe machine learning can find fake news (a classification problem)? In fact, maybe it can.But what can machine learning do for you? And how will you find out? There’s a good place to start close to home, if you’re already using Apache Spark for batch and stream processing. Along with Spark SQL and Spark Streaming, which you’re probably already using, Spark provides MLLib, which is, among other things, a library of machine learning and statistical algorithms in API form.[ Roundup: TensorFlow, Spark MLlib, Scikit-learn, MXNet, Microsoft Cognitive Toolkit, and Caffe machine learning and deep learning frameworks. | Cut to the key news and issues in cutting-edge enterprise technology with the InfoWorld Daily newsletter. ]Here is a brief guide to four of the most essential MLlib APIs, … [Read more...] about Which Spark machine learning API should you use?
Those who have been chomping at the bit to use IBM's Watson machine-intelligence service with their apps need gnaw no longer. Watson APIs are now available for public use, albeit only through IBM's Bluemix cloud services platform. IBM's Watson Developer Cloud now offers eight services for building what IBM describes as cognitive apps, with more services promised later on. The eight services currently available include: [ InfoWorld's quick guide: Digital Transformation and the Agile Enterprise. | Download InfoWorld’s essential guide to microservices and learn how to create modern web and mobile applications that scale. ] Language Identification, which can determine what language a given text is written in (from a predetermined set of 25). Machine Translation, which translates text between multiple language pairs. Concept Expansion, which can take a colloquialism (say, "tri-state area") and map it to a set of meanings based on context (New York, New Jersey, and Connecticut). … [Read more...] about IBM debuts first Watson machine-learning APIs
At the Strata big data conference yesterday, Microsoft let the world know its Azure Machine Learning offering was generally available to developers. This may come as a surprise. Microsoft? Isn't machine learning the province of Google or Facebook or innumerable hot startups? In truth, Microsoft has quietly built up its machine learning expertise over decades, transforming academic discoveries into product functionality along the way. Not many businesses can match Microsoft's deep bench of talent. [ See what hardware, software, development tools, and cloud services came out on top in the InfoWorld 2015 Technology of the Year Awards. | Download the entire list of winners in the handy Technology of the Year PDF. | Stay up on key Microsoft technologies with InfoWorld's Microsoft newsletter. ] Machine learning -- getting a system to teach itself from lots of data rather than simply following preset rules -- actually powers the Microsoft software you use everyday. Machine learning has … [Read more...] about What is Microsoft doing with machine learning?
For any cloud to be taken seriously, it has to meet an ever rising bar of features. Machine learning seems to be on that list, as all the major cloud providers now feature it. But how they go about doing it is another story. Aside from the "curated API vs. open-ended algorithm marketplace" models, there are the "everything and then some vs. just enough" variants. Here's how the four big cloud providers -- IBM, Microsoft, Google, and Amazon -- stack up next to each other in machine learning. [ Also on InfoWorld: How machine learning ate Microsoft. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ]IBM: Turning the ship with, Watson at the helm When IBM first announced it would turn its Watson AI system into a consumable service, the questions piled up. What would it look like? How would it be consumed? But most important, how much support would it lend IBM's effort to reinvent itself as a cloud giant? Two years and change later, IBM has rolled out an array … [Read more...] about How IBM, Google, Microsoft, and Amazon do machine learning in the cloud
Google announced two services today, one new and one out of preview. They are part of the company's ongoing push to fashion itself as a provider of not only tools for building machine learning resources, but also APIs for accessing premade ones. Cloud Machine Learning (CML) can plug into Google's other storage, querying, and data-handling products to generate machine learning models. Among the data sources is Google Cloud Dataproc, the managed Hadoop and Spark platform that was previously announced but is now in general availability.[ The InfoWorld review: Azure Machine Learning is for pros only | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ]You may have been wondering when machine learning as a service would arrive in Google Cloud, considering it has been available on Amazon for months and on Azure for a year. CML is based on Google's open-sourced TensorFlow framework. TensorFlow, Google claims, was used to … [Read more...] about Machine learning finally comes to Google Cloud
Machine learning is the new battle cry for the cloud world. Until cloud computing came along, machine learning was out of reach for most enterprise IT shops. But now that it's in the cloud as a service, it's affordable. It should be no surprise that Amazon Web Services, Google, IBM, and Microsoft offer machine learning services in their clouds. Machine learning is valuable only for use cases that benefit from dynamic learning -- and there are not many of those. Examples of machine learning use cases include financial systems that deal with risk, medical diagnosis, or recommendation systems like those at Amazon.com. [ The InfoWorld reviews: IBM Watson stakes again. • Azure Machine Learning is for pros only. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ] But the online transaction processing (OLTP) style of applications that run most businesses are not a good fit for machine learning. I've used machine learning for applications that needed to … [Read more...] about Machine learning is a poor fit for most businesses
When Satya Nadella made machine learning the centerpiece of the Microsoft Build conference, I think it became official: 2016 is the year of machine learning. All the major clouds now (or will soon) have machine learning APIs. In fact, InfoWorld's Martin Heller has already reviewed the machine learning services offered by AWS, Azure, and IBM Cloud. Even more telling, a couple of years ago only a handful of machine learning startups were out of stealth. Now there are -- what -- a thousand? [ The InfoWorld reviews: IBM Watson strikes again. • Azure Machine Learning is for pros only. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ] Oddly, Nadella's Build talk revolved around intelligent bots, which operate a little like today's highly annoying interactive voice response systems. Whereas the prevailing wisdom is that the greatest potential of machine learning arises when you apply it to big data. Recently I encountered a machine learning startup … [Read more...] about Machine learning’s biggest job InfoWorld
Google has been offering public cloud services for several years now, but the company has continued to lag behind Amazon and Microsoft in customer growth. Under the leadership of VMware co-founder Diane Greene, who serves as the executive vice president of Google Cloud Enterprise, the tech titan has focused harder on forging partnerships and developing products to appeal to large customers. It has added a number of key customers under Greene's tenure, including Spotify. [ The InfoWorld review roundup: AWS, Microsoft, Databricks, Google, HPE, and IBM machine learning in the cloud. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ]One such win is Evernote, which announced Tuesday it would be migrating its service away from its private data centers and to Google's public cloud. When Evernote was looking for a public cloud provider, the company was interested in not only the base level infrastructure available, but also high-level machine learning services … [Read more...] about Could machine learning help Google’s cloud catch up to AWS and Azure?
Google unveiled today machine learning-related additions to its cloud platform, both to enrich its cloud-based offerings and to offer expanded toolsets for businesses to develop their own machine learning-powered products.The most prominent release was the public beta of Google Cloud Machine Learning, a platform for building and training machine learning models with the TensorFlow framework and data stored in the BigQuery and Cloud Storage back ends.[ The InfoWorld review roundup: AWS, Microsoft, Databricks, Google, HPE, and IBM machine learning in the cloud. | First look: Google Cloud Machine Learning soars. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ]Google says its system simplifies the process of creating and deploying machine learning back ends for apps, in part simply by making models faster to train. Google claims Cloud Machine Learning's distributed training "can train models on terabytes of data within hours, instead of waiting … [Read more...] about Google Cloud Machine Learning hits public beta, with additions
Amazon Web Services has unveiled a new generation of GPU-powered cloud computing instances aimed squarely at customers running machine learning applications. The P2's a major step up from the previous generation of GPU-powered AWS instances, and it has plenty of memory to burn. But it's built with an earlier generation of GPU, so it's less suited for the bleeding-edge machine learning work that needs the most recent advances in GPU technology. [ The InfoWorld review roundup: AWS, Microsoft, Databricks, Google, HPE, and IBM machine learning in the cloud. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ]New hotness ... The prior variety of AWS instances with GPUs, the G2, maxed out at four GPUs with 4GB of video RAM and 80GB of system memory per instance. Amazon is currently billing the G2 as suitable for "graphics-intensive applications," rather than machine learning specifically. The P2, on the other hand, is definitely for machine learning. P2 instances … [Read more...] about AWS machine learning VMs go faster, but not forward
There's an arms race among public cloud providers to provide businesses with the best machine learning capabilities. Enterprises are increasingly interested in creating intelligent applications, and companies like Amazon, Microsoft, and Google are rushing to help meet their needs.Google fired its latest salvo on Tuesday, announcing a set of enhancements to its existing suite of cloud machine learning capabilities. The first was a new Jobs API aimed at helping match job applicants with the right openings. In addition, the company is slashing the prices on its Cloud Vision API and launching an enhanced version of its translation API.[ The InfoWorld review: Google's TensorFlow shines a light on deep learning. | Start here with TensorFlow. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ]On top of that, Google is offering GPUs in its cloud both through the company's managed services and its infrastructure-as-a-service product. Companies that want to roll … [Read more...] about Google goes all in on cloud machine learning with new services
2015 was the year machine learning emerged from the academic closet. No longer was it an esoteric discipline commanded by the few, the proud, the data scientists. Now it was, in theory, everyone’s business. 2016 was the year theory became practice. Machine learning’s power and promise, and all that surrounded and supported it, moved more firmly into the enterprise development mainstream. [ Give yourself a technology career advantage with InfoWorld’s Deep Dive technology reports and Computerworld’s career trends reports. GET A 15% DISCOUNT through Jan.15, 2017: Use code 8TIISZ4Z. | Cut to the key news in technology trends and IT breakthroughs with the InfoWorld Daily newsletter, our summary of the top tech happenings. ] That movement revolved around three trends: new and improved tool kits for machine learning, better hardware (and easier access to it), and more cloud-hosted, as-a-service variants of machine learning that provided both open source and … [Read more...] about Machine learning: From science project to business plan
Developers are independent thinkers, often preferring to work on their own projects and shying away from cross-team collaboration. Yet, as the pressure for organizations to implement successful machine learning strategies grows, the role of the collaborative developer is more critical than before. But why? [ Jump into Microsoft's drag-and-drop machine learning studio: Get started with Azure Machine Learning. | The InfoWorld review roundup: AWS, Microsoft, Databricks, Google, HPE, and IBM machine learning in the cloud. ] Machine learning has come a long way since it was a novel idea in 1959 to automate processes. Today, the stakes are much higher for enterprises applying machine learning technology, so here's an approach for developers to become more comfortable with their new role in the machine learning workflow. Establish common ground with data science teams Successful machine learning strategies require complete buy-in from all parts of the organization. Teams must be prepared to … [Read more...] about The role of the developer in the machine learning workflow
Google has already carved out a niche for itself in machine learning with projects like TensorFlow and Google Brain. Now, it's adding data science provider Kaggle, which runs contests related to machine learning and provides services for data discovery and analysis, to the fold. The company also is moving ahead with other machine learning projects, including an API providing intelligence for video. Google Cloud is gaining access to Kaggle's community of more than 850,000 data scientists and vice versa. Kaggle and Google Cloud will continue to support machine learning training and deployment, while the community gets the capability to store and query large data sets. [ Roundup: TensorFlow, Spark MLlib, Scikit-learn, MXNet, Microsoft Cognitive Toolkit, and Caffe machine learning and deep learning frameworks. | Get a digest of the day's top tech stories in the InfoWorld Daily newsletter. ]Google on Wednesday also introduced its Cloud Video Intelligence API, providing an ability to search … [Read more...] about Google machine learning gains Kaggle and more
From Amazon’s product recommendations to Pandora’s ability to find us new songs we like, the smartest Web services around rely on machine learning–algorithms that enable software to learn how to respond with a degree of intelligence to new information or events. Now Google has launched a service that could bring such smarts to many more apps. Google Prediction API provides a simple way for developers to create software that learns how to handle incoming data. For example, the Google-hosted algorithms could be trained to sort e-mails into categories for “complaints” and “praise” using a dataset that provides many examples of both kinds. Future e-mails could then be screened by software using that API, and handled accordingly. Currently just “hundreds” of developers have access to the service, says Travis Green, Google’s product manager for Prediction API, “but already we can see people doing some amazing things.” … [Read more...] about Google Offers Cloud-Based Learning Engine