Vertex AI Vision is an AI-powered platform to ingest, analyze and store video data. Vertex AI Vision lets users build and deploy applications with a simplified user interface.

Using Vertex AI Vision you can build end-to-end computer image solutions by leveraging Vertex AI Vision's integration with other major components, namely Live Video Analytics, data streams, and Vision Warehouse. The Vertex AI Vision API allows you to build a high level app from low level APIs, and create and update a high level workflow that combines multiple individual API calls. You can then execute your workflow as a unit by making a single deploy request to the Vertex AI Vision platform server.

Using Vertex AI Vision, you can:

Ingest real-time video data
Analyze data for insights using general and custom vision AI models
Store insights in Vision Warehouse for simplified querying and metadata information

Whisper’s speech-to-text API can convert audio and voice recordings into text data, which can be used for transcription, voice search, and voice commands. The Whisper API offers pre-built models such as Speech Enhancement and Speaker Verification. It allows developers to eliminate background noise and authenticate the identity of speakers respectively.

Enable people to interact with your products using voice and text.

Wit.ai can help you understand what your users say by extracting relevant information. The following recipes are designed to help you by looking at common problems and recipes to address them.

expert.ai Natural Language API is a cloud-based software service providing a comprehensive set of natural language understanding capabilities based on expert.ai technology

Indico Project Official site - Indico is a powerful event (meetings, conferences, lectures) management system developed at CERN

Random Stuff API (RSA) is a powerful API developed by PGamerX, and it’s free to use as well as open-source. It can give AI-based responses, random jokes, memes, anime, animal images and much more!

The central data structures in spaCy are the Language class, the Vocab and the Doc

object. The Language class is used to process a text and turn it into a Doc object. It’s typically stored as a variable called nlp. The Doc object owns the sequence of tokens and all their annotations. By centralizing strings, word vectors and lexical attributes in the Vocab, we avoid storing multiple copies of this data. This saves memory, and ensures there’s a single source of truth.

Text annotations are also designed to allow a single source of truth: the Doc object owns the data, and Span
and Token are views that point into it. The Doc object is constructed by the Tokenizer, and then modified in place by the components of the pipeline. The Language object coordinates these components. It takes raw text and sends it through the pipeline, returning an annotated document. It also orchestrates training and serialization.

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