cloud


Google's self-training AI turns coders into machine-learning masters

#artificialintelligence

Google just made it a lot easier to build your very own custom AI system. A new service, called Cloud AutoML, uses several machine-learning tricks to automatically build and train a deep-learning algorithm that can recognize things in images. The technology is limited for now, but it could be the start of something big. Building and optimizing a deep neural network algorithm normally requires a detailed understanding of the underlying math and code, as well as extensive practice tweaking the parameters of algorithms to get things just right. The difficulty of developing AI systems has created a race to recruit talent, and it means that only big companies with deep pockets can usually afford to build their own bespoke AI algorithms.


A new service would make deep learning more accessible to millions of coders

#artificialintelligence

Google is one of the biggest tech companies paving the way for artificial intelligence and machine learning, and a recent announcement from the company stands to bolster that reputation. This week, Google announced the launch of a new service that will enable both businesses and individuals to begin building their own AI systems. Officially called Google Cloud AutoML, the service comes in the wake of Google's recognition that only a handful of big businesses currently have the budgets necessary to take advantage of AI and machine learning. At the same time, these are often the businesses best positioned to bring on new talent specializing in AI and machine learning engineering. While Google does have pre-trained models, they're typically trained to perform very specific tasks.


Google launches Cloud AutoML to automatically build custom AI models

#artificialintelligence

Google today announced a new cloud service that's designed to make it easier for companies to create custom machine learning algorithms for processing images. Called Cloud AutoML Vision, the system allows developers to upload a bunch of images to Google's cloud and receive a custom model in return. It's based on Google's research into training machine learning models to construct models that perform particular tasks well. In theory, companies should be able to feed the system a set of sample images and, within a day, get back an automatically trained model that's optimized for their specific data. Cloud AutoML, which will eventually expand beyond images, is supposed to help bridge the gap between the companies that need custom machine learning tools and the handful that are able to pay top dollar for the technical talent needed to implement those tools.


3 Companies Using Artificial Intelligence to Their Advantage

International Business Times

This article originally appeared in Motley Fool. Artificial intelligence (AI) is already impacting our lives in many ways. From intelligent video curation on Alphabet's (NASDAQ:GOOG) (NASDAQ:GOOGL) YouTube and Google web search to Apple's (NASDAQ:AAPL) Siri personal assistant, AI is already making our lives easier. AI can also help corporations and customers fight against rapidly evolving cyberthreats. For instance, FireEye's (NASDAQ:FEYE) Helix cybersecurity platform is able to automate threat detection and prevention with the help of this emerging technology.


Plot2txt for quantitative image analysis

@machinelearnbot

In recent times, computation has become both pervasive and less constrained by Moore's Law. This is due in large part to the emergence of cloud computing and the rise of massive parallelism. The former has benefited from network improvements and ever increasing connectedness, the latter from the appropriation of hardware like Graphics Processing Units (GPUs) for general purpose computing. This computational leap, coupled with the process of disintermediation [1] taking place around the globe will continue to support revolutions like artificial intelligence (AI), as many have remarked. AI has a long and interesting history.


IBM and Salesforce double down on AI, announce Watson Einstein collaboration

#artificialintelligence

Salesforce and IBM announced an expansion of their strategic partnership on Friday, with the firms combining the power of IBM Cloud and Watson services with Salesforce Quip and Salesforce Service Cloud Einstein, the firms announced in a joint press release Friday. Two top tech firms like Salesforce and IBM connecting their artificial intelligence (AI) platforms reinforces the growing value of AI and big data in the enterprise. AI, especially, is taking center stage as one of the battleground technologies for business, and this is a clear example of two CEOs making a move to reinforce that with their partnership. In the release, IBM CEO Ginni Rometty said that the combination of Watson and Einstein will "help enterprises make smarter business decisions." Salesforce CEO Marc Benioff echoed this sentiment, saying in the release that the combo will "deliver even more innovation to empower companies to connect with their customers in a whole new way, leveraging the power of the cloud and AI." SEE: IT leader's guide to the future of artificial intelligence (Tech Pro Research) Specifically, the Watson/Einstein combination will provide actionable next steps in a given process, the release said.


New Google Service Makes Machine Learning More Accessible

#artificialintelligence

Google on Wednesday released its Cloud AutoML Vision service in Alpha. It is the first in a planned series of Cloud AutoML services designed to help people with limited machine learning expertise build their own custom models using advanced techniques such as learning2learn and transfer learning. Learning2learn is a process for automating machine learning, while transfer learning "takes a fully trained model for a set of categories and retrains it from the existing weights for new classes," a Google Cloud spokesperson told the E-Commerce Times in a statement provided by company rep Danny McCrone. Cloud AutoML Vision makes it faster and easier to create custom ML models for image recognition. Its drag-and-drop interface lets users upload images, train and manage models, then deploy those trained models directly on Google Cloud.


IBM, Salesforce expand AI partnership for deeper customer insights

ZDNet

IBM and Salesforce announced Friday an expansion of their strategic partnership that brings more data integration to companies so they can better interact with customers. SaaS had a major impact on the way companies consume cloud services. This ebook looks at how the as a service trend is spreading and transforming IT jobs. Under the extended partnership, IBM will build a Watson app for Salesforce's Quip Live Apps, launching AI tools on the collaborative document platform. Salesforce introduced Live Apps in November 2017 to be embedded directly into any Quip document.


New Trends in Artificial Intelligence & Machine Learning

@machinelearnbot

This article was written by Hardik Gohil, Sr Content Writer. Artificial Intelligence has effectively convinced its necessity to the entire world by performing excellently in various industries. Almost all the industries including manufacturing, healthcare, construction, online retail, etc. are adapting to the reality of IoT to leverage its advantages. Machine learning technology is constantly evolving and the current trends in the field promise that every enterprise will be data driven and will have the capacity of using machine learning in the cloud to incorporate artificial intelligence apps. Companies will be successful in analyzing large complex data and providing meticulous insights without spending a huge amount on installing and maintaining machine learning systems.


Google Launches Cloud AutoML for Building Image Recognition Models

#artificialintelligence

Yesterday, tech giant Google announced its latest solution, the Cloud AutoML, that will enable developers, even those that lack machine learning expertise, to build image recognition models. It is said to be a part of the company's initiative to democratize AI learning and provide a simple approach that anyone can easily understand. "Our goal was to lower the barrier of entry and make AI available to the largest possible community of developers, researchers and businesses," Fei-Fei Li, Google Cloud AI chief scientists, and Jia Li, Google Cloud AI Head of R&D, wrote in the company blog. According to the duo, their latest solution would help businesses with limited machine learning expertise build "their own high-quality custom models by using advanced techniques like learning2learn and transfer learning from Google." The two believe that Cloud AutoML will make experts in artificial intelligence more productive and take the technology to greater heights while helping less-skilled engineers build more powerful machine learning systems.