ARTIFICIAL INTELLIGENCE APIs for BuildING SMART Apps
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Open AI
Open AI provides GPT-3, which can do a range of natural language tasks, and Codex, which converts natural language into code. Open AI APIs for apps include fast response times, large request volumes, scalability, and flexibility to boost machine learning team efficiency. AI programs may filter content, monitor end-users, and provide specialized endpoints for API usage.
2/10
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AWS AI Services
AWS AI Services provides AI APIs for applications and processes that are ready for use. In order to solve challenges like as modernizing contact centers, providing tailored suggestions, and enhancing safety and security, AI services may be smoothly integrated into applications. AI-based application programming interfaces (APIs) provide enhanced text analytics and automatic code reviews.
3/10
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Wit.ai
You can create smart apps with Wit.ai using AI APIs, experiences with natural language, and more. Customers may use voice or text to communicate with a brand’s goods. It is not only focused on mobile applications but also on wearable technology, smart homes, and bots that can create unique experiences. You may create callable and textable applications and devices using the AI API. Additionally, it has a natural language interface, which enables programs to convert phrases into structured data.
4/10
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IBM Watson
Using IBM Watson’s AI API you can include dialogue, language, sophisticated text analytics, and other capabilities into your projects. Organizations can utilize the IBM Watson API to derive sentiment and emotion, employ Watson Natural Language Understanding, and develop more insightful business strategies. Additionally, it enables the integration of conversational exchanges with Watson Discovery. You get access to Watson Media, Watson Health, Watson Assistant, RegTech, and Watson Health to swiftly and effectively construct very intelligent apps.
5/10
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Google CLOUD AI
Syntax analysis, sentiment analysis, entity analysis, and multilingual expectations for incoming data are just some of the things that Google is famous for being able to do. It is well-known for its success in completing the artificial intelligence stage of development. And you integrate that in your applications.
6/10
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Rev.ai
Rev.ai offers a top-notch voice-to-text API to satisfy speech recognition needs. Through a simple API, developers have access to audio and video with unmatched precision. It is renowned for using verbatim transcriptions of more than 50,000 hours of speech to build an API-driven speech recognition engine. With simple integration, artificial intelligence programs may utilize it asynchronously or in a stream.
7/10
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Komprehend AI
Software developers may use the whole collection of document categorization APIs and NLP APIs from ParallelDots’ Komprehend AI APIs. There are NLP models that have been trained to conduct sentiment analysis and emotion recognition on a billion documents. AI APIs can be used to leverage sentiment, keywords, and emotions.
8/10
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Einstein Language API
Integrate the Einstein Language API to build NLP models that can be used to identify the purpose or mood of text as positive, negative, or neutral. The Einstein Language API is divided into two sections: Einstein emotion and Einstein purpose. This set of API may be used to analyze email and chat content, as well as to create custom models.
9/10
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