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Category: Computing & data (Page 71 of 98)

Computing and data is a broad category. Our coverage of computing is largely limited to software, and we are mostly focused on unstructured data, semi-structured data, or mixed data that includes structured data.

Topics include computing platforms, analytics, data science, data modeling, database technologies, machine learning / AI, Internet of Things (IoT), blockchain, augmented reality, bots, programming languages, natural language processing applications such as machine translation, and knowledge graphs.

Related categories: Semantic technologies, Web technologies & information standards, and Internet and platforms.

Google introduces Document AI platform for document processing

November 4, 2020 /

Google Cloud announced the new Document AI (DocAI) platform, a unified console for document processing. Transforming documents into structured data increases the speed of decision making for companies, unlocking business value and helping develop better experiences for customers. Historically, doing this at scale hasn’t been efficient. DocAI is designed to help businesses use Artificial Intelligence (AI) and machine learning to automate these processes. Today, the DocAI platform is available in preview, enabling you to:

  • Ensure your data is accurate and compliant: Automate and validate all your documents to streamline compliance workflows, reduce guesswork, and keep data accurate and compliant.
  • Make better business decisions: Improve operational efficiency by extracting structured data from unstructured documents and making that available to your business applications and users.
  • Use your data to meet customer expectations: Leverage insights to meet customer expectations and improve CSAT, advocacy, lifetime value, and spend.

With the new DocAI platform, you can access all parsers, tools and solutions (e.g. Lending DocAI, Procurement DocAI) with a unified API, enabling a document solution from evaluation to deployment. It allows creation and customization of document processing workflows. Data extraction is now easier because the specialized parsers on the platform are built with Google Cloud’s predefined taxonomy, without the need to perform additional data mapping or training. General parsers such as OCR (Optical Character Recognition), Form parser, and Document splitter are publicly accessible. You can also request access to specialized parsers such as W9, 1040, W2, 1099-MISC, 1003, invoice, and receipts.

https://cloud.google.com/blog/products/ai-machine-learning/google-cloud-announces-document-ai-platform

Expert.ai expands upon cloud offering

October 28, 2020 /

Expert.ai announced and will be presenting an enhanced release of its cloud-based Natural Language API today at API World. The new expert.ai NL API features include:

  • Relation extraction to express the connection and accurately answer questions like: “who did what when?”, and “what caused what to whom?”
  • Sentiment analysis considering the intrinsic positivity or negativity of the concepts expressed in text, based on the words used (polarity) and how relevant we judge them (intensity)
  • A new geographic taxonomy to identify and disambiguate countries and some other administrative divisions (e.g., San Jose, CA, USA vs. San Jose, Costa Rica)

Learn more about expert.ai NL API, now available for free testing, visit and sign up to start developing intelligent applications today.

https://developer.expert.ai, https://expert.ai, https://apiworld.co/

Information Model
Gilbane Advisor 6-9-21 — stacks & aggregation, JavaScript for data, news

sentiment analysis

Sentiment analysis (also known as opinion mining or emotion AI) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.

Sitecore to make AI auto personalization a standard feature of digital experience platform

October 27, 2020 /

Sitecore announced Sitecore Artificial Intelligence (AI) Auto Personalization Standard will be available as part of Sitecore Experience Platform 10 (XP) for customers beginning in early 2021. This expands the availability of Sitecore AI and brings quick and simple personalization to customers without requiring an increase in budget or team hours. Sitecore AI Auto Personalization Standard enables users to start personalization right away, without manually defining user segments and with no minimum traffic required, while also:

  • Enabling auto personalization, such as images, text snippets and calls to action for sites
  • Providing immediate personalization performance visibility with AI analytics embedded in XP
  • Tracking critical KPIs, such as engagement value and bounce rates, to measure success

Sitecore also offers Sitecore AI Auto Personalization Premium for customers who want unlimited personalization along with an AI insights dashboard with discovered audiences from both historical and daily data.

Sitecore also announced new content delivery capabilities, coming in early 2021, that will bring additional options for brands, including:

  • Sitecore Experience Manager (XM), which will have an added option for customers to leverage a scalable delivery platform for static publishing of Sitecore JSS sites and runtime content delivery for headless sites
  • Sitecore Content as a Service (CaaS) capabilities built upon the Sitecore Content Hub SaaS platform, enabling brands to perfect their content strategy with centralized planning and collaboration tools and publish atomic content to a scalable delivery platform through APIs to any channel, on demand.

https://www.sitecore.com/company/news-events/press-releases/2020/10/sitecore-makes-ai-powered-auto-personalization-a-standard

Information Model
Gilbane Advisor 6-9-21 — stacks & aggregation, JavaScript for data, news

dotData announces integration of dotData Stream and Amazon SageMaker

October 27, 2020 /

Automated Machine Learning (AutoML) vendor dotData announced that dotData Stream now supports integration with Amazon SageMaker, a Machine Language Operations Platform (MLOps). Amazon SageMaker is a managed service that provides developers and data scientists with the ability to deploy machine learning (ML) models quickly. Now, with simple point-and-click operations, dotData users can launch dotData Stream on Amazon SageMaker and leverage the platform’s capability to monitor, manage, orchestrate, govern and maintain AI/ML models developed using dotData Platform. This integration provides dotData/AWS users with a full-cycle data science automation experience, from automated AI/ML development using dotData Enterprise through instant AI/ML deployment using dotData Stream to AI/ML lifecycle management with AWS SageMaker. The combination of dotData and Amazon SageMaker helps make AutoML accessible to more enterprises. In July, dotData announced dotData Stream, a portable containerized AI/ML engine that enables real-time predictive capabilities. dotData users can develop AI/ML models using dotData Enterprise or dotData Py and then deploy AI/ML models just with a single docker command using dotData Stream. dotData Stream is designed to be easily deployable on an out of the box MLOps platform or container orchestration frameworks.

https://dotdata.com

Solace updates PubSub+ Event Portal

October 27, 2020 /

Solace announced the general availability of a new version of PubSub+ Event Portal that makes it easier for developers and solution architects to discover, catalog, govern, and visualize Apache Kafka event streams, including those from Confluent and Amazon MSK. Solace first announced these capabilities at Kafka Summit in August and has worked with beta customers to refine functionality and usability. PubSub+ Event Portal gives application teams the ability to:

  • Discover and import Apache Kafka events and application interactions;
  • Catalog event streams already used within Apache Kafka environments;
  • Visualize Apache Kafka topologies;
  • Audit to flag discrepancies between design intent and runtime; and,
  • Add application and event governance to Apache Kafka data.

PubSub+ Event Portal’s new Kafka-centric capabilities are generally available now.

https://solace.com/products/portal/kafka/

Apache Kafka

Apache Kafka is an open-source distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.

Sensory unveils VoiceHub portal

October 21, 2020 /

Sensory unveiled VoiceHub, an online portal that enables developers to quickly create wake word models and voice control command sets for prototyping and proof-of-concept purposes. VoiceHub allows users to select languages and model sizes through drop down menus. Sensory’s VoiceHub provides developers with free tools to immediately create custom wake words and voice command sets for their applications. These projects take just moments to put together and some models are trained and downloadable within an hour of submitting them. VoiceHub outputs wake word and voice command set models, compatible with a companion Android application for quick prototyping, or as code for specific target DSPs for more advanced proof-of-concept testing. The tools allow developers to create wake word models, either custom branded or based on today’s most popular voice assistant platforms, and command set models targeting a desired memory footprint. This makes it suitable for all applications, ranging from ultra-low power, resource limited wearables to high-power, high-performance appliances on the edge.

Based on Sensory’s TrulyHandsfree technology, VoiceHub supports numerous languages for testing voice control across global product lines. Since VoiceHub trains voice models similarly to TrulyHandsfree, the wake word and voice control models created in VoiceHub are accurate and in most cases suitable for mass production. VoiceHub users can expect a steady stream of updates and new features, including support for more languages, expanded DSP platform support, and the ability to quickly develop large vocabulary natural language models. At launch, the platform supports DSP platforms from: Ambiq, Analog Devices, Cirrus, Cypress, DSPG, Foretmedia, Knowles, Motorola, NXP, Qualcomm, Renesas, ST Micro and TI.

https://www.sensory.com/voicehub

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