If you’re partial to using Google’s cloud services, and interested in exploring the potential of machine learning, then the search-engine giant has a pair of new toys for you: the Cloud Natural Language and Cloud Speech APIs, now in beta. Google has recently made a concerted effort to open up its machine-learning platforms to tech pros. Back in May, the company open-sourced SyntaxNet, a neural network framework implemented in the open-source TensorFlow machine-learning system. SyntaxNet included the memorably named Parsey McParseface, which uses machine learning to parse the English language for meaning—a difficult feat for any machine. “Cloud Natural Language lets you easily reveal the structure and meaning of your text in a variety of languages, with initial support for English, Spanish, and Japanese,” read a note on Google’s Cloud Platform Blog. The API, which is based on Google’s extensive research into natural language, includes sentiment analysis, entity recognition (which identifies “relevant entities” within a block of text, including locations and events), and syntax analysis. In theory, the Cloud Natural Language API will allow developers to build products that can analyze massive datasets—such as online product reviews or transcriptions—for sentiment. For example, if you wanted to determine what visitors to your company’s Website thought about your products, you could leverage the API to scrutinize the comments. With the accompanying Cloud Speech API, the blog added, “enterprises and developers now have access to speech-to-text conversion in over 80 languages, for both apps and IoT [Internet of Things] devices.” The API is powered in part by the same voice-recognition technology that undergirds Google Search and Google Now. With the rise of devices and services such as Apple’s Siri, Amazon’s Echo, and Google Assistant, it’s clear that tech firms are betting their future on people interacting with computers as they would another human being. That means services that leverage natural language—whether through voice activation, or by analyzing written comments—will have a significant future advantage. For those developers interested in testing out what machine learning and natural language can do, Cloud Natural Language and Cloud Speech APIs might provide a good starting point.