Google continues to make inroads into developer tools for artificial intelligence. At this week’s Google Cloud Next ’17 conference, the search-engine giant unveiled the Cloud Video Intelligence API, which leverages deep-learning models and frameworks such as TensorFlow to search and discover elements within video content. “This API is for large media organizations and consumer technology companies who want to build their media catalogs or find easy ways to manage crowd-sourced content, and for partners like Cantemo to build it into their own video management software,” Google announced in a blog posting. Using the API (which is in private beta at the moment), a developer can enable a search function to scour a video for very specific things. For example, let’s say you had an enormous archive of wildlife video footage; with the API in play, a developer could type “monkey run” to find clips of monkeys running. Cloud Video Intelligence is only the latest API opened by Google to developers. Other APIs in that growing stack include Cloud Natural Language and Cloud Speech APIs, as well as ones for Translation, Vision (as of this week, updated to 1.1 in beta), and, now, Jobs. In theory, all those APIs will turn Google into much more of a one-stop shop for both companies and developers seeking to update their software with machine-learning capabilities. But Google doesn’t have the field all to itself: Microsoft, Facebook, and other large firms are pouring tons of resources into machine learning, in hopes of creating sizable ecosystems that draw in (and keep) developers. At this year’s Google Cloud Next, Google also rolled out Cloud Datalab, which it described on the blog as a tool that “makes it easy for developers and data scientists to explore, analyze and visualize data in BigQuery, Cloud Storage or local storage.” That could also prove an especially “sticky” feature for keeping data scientists and other tech pros in Google’s fold. If you’re curious about Google’s approach to A.I. and machine learning, and you’re new to the field, check out the three-hour course on the Google Cloud Platform blog that gives an intro to deep-learning fundamentals. Google Unveils Cloud Video Intelligence API
Google continues to make inroads into developer tools for artificial intelligence. At this week’s Google Cloud Next ’17 conference, the search-engine giant unveiled the Cloud Video Intelligence API, which leverages deep-learning models and frameworks such as TensorFlow to search and discover elements within video content. “This API is for large media organizations and consumer technology companies who want to build their media catalogs or find easy ways to manage crowd-sourced content, and for partners like Cantemo to build it into their own video management software,” Google announced in a blog posting. Using the API (which is in private beta at the moment), a developer can enable a search function to scour a video for very specific things. For example, let’s say you had an enormous archive of wildlife video footage; with the API in play, a developer could type “monkey run” to find clips of monkeys running. Cloud Video Intelligence is only the latest API opened by Google to developers. Other APIs in that growing stack include Cloud Natural Language and Cloud Speech APIs, as well as ones for Translation, Vision (as of this week, updated to 1.1 in beta), and, now, Jobs. In theory, all those APIs will turn Google into much more of a one-stop shop for both companies and developers seeking to update their software with machine-learning capabilities. But Google doesn’t have the field all to itself: Microsoft, Facebook, and other large firms are pouring tons of resources into machine learning, in hopes of creating sizable ecosystems that draw in (and keep) developers. At this year’s Google Cloud Next, Google also rolled out Cloud Datalab, which it described on the blog as a tool that “makes it easy for developers and data scientists to explore, analyze and visualize data in BigQuery, Cloud Storage or local storage.” That could also prove an especially “sticky” feature for keeping data scientists and other tech pros in Google’s fold. If you’re curious about Google’s approach to A.I. and machine learning, and you’re new to the field, check out the three-hour course on the Google Cloud Platform blog that gives an intro to deep-learning fundamentals. 
