Google Cloud’s Speech API processes more than 1 billion voice minutes per month with close to human levels of understanding for many commonly spoken languages. Powered by the best of Google's AI research and technology, Google Cloud's Speech-to-Text API helps you accurately transcribe speech into text in 73 languages and 137 different local variants. Leverage Google’s most advanced deep learning neural network algorithms for automatic speech recognition (ASR) and deploy ASR wherever you need it, whether in the cloud with the API, on-premises with Speech-to-Text On-Prem, or locally on any device with Speech On-Device.
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RaimaDB is an embedded time series database for IoT and Edge devices that can run in-memory. It is an extremely powerful, lightweight and secure RDBMS. Field tested by over 20 000 developers worldwide and has more than 25 000 000 deployments.
RaimaDB is a high-performance, cross-platform embedded database designed for mission-critical applications, particularly in the Internet of Things (IoT) and edge computing markets. It offers a small footprint, making it suitable for resource-constrained environments, and supports both in-memory and persistent storage configurations. RaimaDB provides developers with multiple data modeling options, including traditional relational models and direct relationships through network model sets. It ensures data integrity with ACID-compliant transactions and supports various indexing methods such as B+Tree, Hash Table, R-Tree, and AVL-Tree.
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PureMind
Computer vision and artificial intelligence (AI) helps train equipment to control the quality of products in manufacture, train robots for movement autonomous and safety, train cameras to control and analyze traffic on retail, recognize types and colors of cars, food in the fridge, or make a map or 3D model of space from video. Algorithms help to predict sales in your business, find the relationship between metrics, publications and grow, classify customers for prepare personal offers, interpret and visualize the data, extract most important from text and video. Data Mining, regression, classification, correlation and cluster analysis, decision trees, prediction models, graphs, neural networks. Text classification, understanding, summarization and auto-tagging, named-entity recognition, compare for text similarity, sentiment analysis, dialog and QA systems. Detection, segmentation, recognition, recovery and image/video generation.
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