Box CEO Aaron Levie reveals the cloud storage company's new AI upgrades at the company's Boxworks 2017 conference. Everywhere you go in Silicon Valley, the trendy technology du jour is "artificial intelligence." It's a major selling point for Google's new Pixel phones, the Amazon Echo speaker, Microsoft Office, and a whole mess of tech startups. Aaron Levie, the CEO of $2.75 billion cloud file company Box, acknowledges that when it comes to AI, people are "already tired of the buzzword." And yet, at the company's Boxworks conference where we spoke last week, Levie announced that Box was making a big bet on artificial intelligence, with new features and capabilities.
"Artificial intelligence" is a misunderstood term, thanks in part to dystopian views of the technology across pop culture -- from the iconic Terminator to Cylons in Battlestar Galactica to HAL 9000 in 2001: A Space Odyssey. In reality, most scientists working on artificial intelligence aren't trying to simulate true human intelligence at all. They are simply trying to create practical machines capable of analyzing data and making decisions to achieve a goal. CRM, 1.76% has a valuable artificial intelligence application called Einstein that it provides to clients. This AI engine helps marketing and sales teams by suggesting which customers are the most valuable, and which products they are most likely to buy.
Artificial Intelligence is no more a luxury but a necessity for all types of organization, no matter big or small. It has gracefully covered every vertical of operations and made life way to easier for the businesses. Those who were once scared of implementing Artificial Intelligence in their life today rely on it for most of their daily life chores. Artificial intelligence caters us everywhere, from an "OOO" automatic replies to accounting management, there is nothing that has left bereft of artificial intelligence intervention. From large to medium to small-scale industries, organizations of every scale are looking forward to adapting artificial intelligence in their mainstream business operations.
It has never been a better time to be a developer. Thanks to cloud computing, deploying our applications is much easier than it used to be. How we deploy our apps continues to evolve thanks to cloud hosting, Platform-as-a-Service (PaaS), and now Function-as-a-Service. FaaS is the concept of serverless computing via serverless architectures. Software developers can leverage this to deploy an individual "function", action, or piece of business logic.
Cloud content management company Box has unveiled Box Skills, a framework for applying machine learning tools such as computer vision, video indexing, and sentiment analysis to stored content. Box Skills will facilitate businesses to re-imagine the business processes considered as impractical to digitise or automate or too expensive. Audio Intelligence: Uses audio files to create and index a text transcript that can be easily searched and manipulated in a variety of use cases; powered by IBM Watson technology. Video Intelligence: Provides transcription, topic detection and detects people to allow users to quickly look up the information they need in a video; powered by Microsoft Cognitive Services. Image Intelligence: Detects individual objects and concepts in image files, captures text through optical character recognition (OCR), and automatically adds keyword labels to images to easily build metadata on image catalogues; powered by Google Cloud Platform.
Deepmind, the artificial intelligence research organization owned by Google, announced some stunning results Wednesday from research into the next generation of its AlphaGo system: the machines are getting smarter. AlphaGo Zero, the new version of the AlphaGo system that defeated the world's best Go players in competitions over the past few years, was able to teach itself how to play the ancient board game as well as its predecessors in a matter of days with no other input than the basic rules of the game, Deepmind said in a blog post Wednesday. Previous versions of AlphaGo built to compete against human masters of the game required hours and hours of training on Go gameplay, but AlphaGo Zero was able to teach itself to play using a technique called reinforcement learning. Reinforcement learning involves training a system to figure out the best reward outcome from a series of actions, unlike supervised learning, in which the system is taught which outcomes are desired and trained over and over to recognize the factors that lead to those outcomes. Deepmind set up a neural network that played games of Go against itself until it learned how to formulate a winning strategy for a game in which capturing as many stones as possible can be satisfying in early stages, but can lead to big problems as the game plays out.
Are you ready for the WWE of giant robot fighting? Don't worry, we weren't either. Anyway, it's Thursday, which means it's time to make a plan for cleaning up dead satellites. Chainsaws aren't against the rules, FYI.USA vs. Japan giant robot battle was a slow, brilliant mess On Tuesday, Team USA's mechs scrapped it out with Japan's Kuratas in an abandoned steel mill for the world to watch. There could only be one victor, and it proved to be -- well, click here if you'd like to watch without a spoiler.
Posted by Bradley Jiang, Software Engineer. Many people think designing deep learning models and training neural networks is complex and time-consuming, taking days or even weeks of work. But it doesn't have to be. There are a number of tools you can use right now to help you quickly develop and iterate on machine learning models. One such tool is Cloud Datalab.
The Democratic National Committee's chief technology officer, Raffi Krikorian, says that changes within the post-2016 political party are as much about the culture as they are about security. The MIT grad's time is physically split between his Silicon Valley home and Washington D.C., although he's looking to bridge the cultural gap between tech and politics. Krikorian previously led Uber's Advanced Technologies Center, where he was tasked with putting the ride-sharing company's self-driving cars on the streets of Pittsburgh, Pa. And preceding that, Krikorian was Twitter's vice president of engineering after successfully managing the social media giant's application programming interface. Following last year's hacks, leaks and ongoing discussion about Russian interference, his priority was to move security and communication to a trusted cloud service assisted by Microsoft.