NetEase Technology News, April 11th news, according to foreign media reports, Google today released a series of artificial intelligence tools, the core of all these new tools and services is the company plans to achieve distributed artificial intelligence through pre-built models and convenient services And machine learning, while serving more advanced developers, enabling them to build their own custom models.
Today Google’s focus is on releasing the company’s beta artificial intelligence platform. The idea is to provide end-to-end services for developers and data scientists to build, test, and deploy their own models. To this end, the service brings together a variety of existing products and new products, allowing developers to build complete data pipelines to extract data, tag data with new built-in tag services, and then use existing classification, object recognition or entity extraction Model, or train and deploy custom models using existing tools such as AutoML or machine learning cloud engines.
Before the official launch, a Google spokesperson said at a press conference that "artificial intelligence platform is such a place. If you know how to use artificial intelligence in the enterprise, familiar with the whole process from release to secure and reliable deployment, artificial intelligence platform. It can help you complete each phase in a safe way. This way you can start with exploratory data analysis, let data scientists start building models, decide which specific model you want to use, and deploy with a single click. ”
Google also announced many new features about Cloud AutoML. Cloud AutoML is a new tool released last year by Google to automate model training for developers with limited machine learning expertise.
One of these new features is AutoML Tables, which captures existing table data that may be in the Google BigQuery database or storage service and automatically creates a model to predict a given column value.
AutoML Video Intelligence, currently in beta, is also a new feature that automatically adds annotations and tags to videos, uses object recognition to categorize video content, and makes it searchable. To detect objects in photos on edge devices, Google also today introduced the AutoML Vision beta, which includes the ability to deploy these models to edge devices.
Many corporate data comes in the form of direct, unstructured text. For these use cases, Google today launched a beta version of the custom entity extraction service and custom sentiment analysis service. Both tools can be customized to meet the different needs of different companies. Using generic entity extraction services to understand documents is one thing, but for most companies, the real value is the ability to extract information specific to their needs and processes.
Speaking of documentation, Google also released a beta version of the Document Understanding API today. This is a new platform that can automatically analyze scans or digitize documents. The service combines the ability to convert scanned pages into machine-readable text and then extracts data from other machine learning services from Google.
After releasing the preview version last year, the company also launched a beta version of the Contact Center AI today. Built by partners such as Google and partners Twilio, Vonage, Cisco, Five9, Genesys and Mitel, the service provides a complete call center artificial intelligence solution that uses tools such as Dialogflow and Google Text Voice to allow users to develop Virtual customer service system. When this system goes wrong, it can turn the customer to manual customer service.
It’s no secret that many companies are struggling to combine all of Google’s tools and services into a coherent platform to meet their needs. Google today also launched its first artificial intelligence solution for a specific vertical sector: Google Cloud Retail. The service integrates the company's Vision Product Search, Recommendations AI, and AutoML Tables into a single solution for processing retail practices. It is very likely that in the near future, we will see more packages in other vertical areas. (晗冰)