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features
design
support

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Description

BLOOM is a sophisticated autoregressive language model designed to extend text based on given prompts, leveraging extensive text data and significant computational power. This capability allows it to generate coherent and contextually relevant content in 46 different languages, along with 13 programming languages, often making it difficult to differentiate its output from that of a human author. Furthermore, BLOOM's versatility enables it to tackle various text-related challenges, even those it has not been specifically trained on, by interpreting them as tasks of text generation. Its adaptability makes it a valuable tool for a range of applications across multiple domains.

Description

Language Understanding (LUIS) is an advanced machine learning service designed to incorporate natural language capabilities into applications, bots, and IoT devices. It allows for the rapid creation of tailored models that enhance over time, enabling the integration of natural language features into your applications. LUIS excels at discerning important information within dialogues by recognizing user intentions (intents) and extracting significant details from phrases (entities), all contributing to a sophisticated language understanding model. It works harmoniously with the Azure Bot Service, simplifying the process of developing a highly functional bot. With robust developer resources and customizable pre-existing applications alongside entity dictionaries such as Calendar, Music, and Devices, users can swiftly construct and implement solutions. These dictionaries are enriched by extensive web knowledge, offering billions of entries that aid in accurately identifying key insights from user interactions. Continuous improvement is achieved through active learning, which ensures that the quality of models keeps getting better over time, making LUIS an invaluable tool for modern application development. Ultimately, this service empowers developers to create rich, responsive experiences that enhance user engagement.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Azure CLU No 
BotCore No 
Dydu No 
Geomant No 
Geomant Wallboard No 
Ideta No 
Microsoft Entra ID No 
Neo Enterprise Assistant Platform No 
QnA Maker No 
Quickwork No 
Take Blip No 

Integrations

Azure CLU Yes 
BotCore Yes 
Dydu Yes 
Geomant Yes 
Geomant Wallboard Yes 
Ideta Yes 
Microsoft Entra ID Yes 
Neo Enterprise Assistant Platform Yes 
QnA Maker Yes 
Quickwork Yes 
Take Blip Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

BigScience

Founded

2021

Website

huggingface.co/bigscience/bloom

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

www.luis.ai/

Product Features

Natural Language Generation

Business Intelligence No 
CRM Data Analysis and Reports No 
Chatbot No 
Email Marketing No 
Financial Reporting No 
Multiple Language Support No 
SEO No 
Web Content No 

Natural Language Processing

Co-Reference Resolution No 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing No 
Part-of-Speech Tagging No 
Sentence Segmentation No 
Stemming/Lemmatization No 
Tokenization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Natural Language Processing

Co-Reference Resolution No 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing No 
Part-of-Speech Tagging No 
Sentence Segmentation No 
Stemming/Lemmatization No 
Tokenization No 

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