Posts Tagged ‘Alchemy API’

AlchemyAPI Improves Service Using Deep Neural Networks

While Google, Microsoft and Apple have been making significant product breakthroughs using deep neural networks (DNN), the question remains: Is using DNN a practical approach for companies that are not web giants? For some, the answer is a resounding “yes.” AlchemyAPI, a natural language processing platform, has developed the ability to train very large and deep neural networks efficiently while remaining cost effective.

“In the area of language modeling, for example, we are able to train on huge amounts of data (a hundred billion words or more) in less than 24 hours whereas in the research community, many groups are spending 4-6 weeks to train a system on fewer than a billion words,” according to Elliot Turner, AlchemyAPI Founder and CEO. Read more

Alchemy API Raises $2M

Alex Williams of TechCrunch reports, “AlchemyAPI has raised $2 million to extend the capabilities of its deep learning technology that applies artificial intelligence to read and understand web pages, text documents, emails, tweets, and other forms of content. Access Venture Partners led the Series A round, which the company will use to ramp up its sales and marketing, make hires and launch new services. Founder and CEO Elliot Turner says its natural language processing technology is used in vertical markets such as financial services, which uses Alchemy’s technology to analyze text and search for signals from the data it can plug into its trading algorithms. It is offered as a service or in the form of an appliance that companies install in its data centers.” Read more

Alchemy Aims to Add More API Wizardry

Orchestr8’s NLP- and machine learning-based AlchemyAPI service for analyzing content and extracting semantic metadata has added some new capabilities.

One new feature is dubbed Relation Extraction, which project engineer Shaun Roach tells the Semantic Web Blog “detects sentences describing actions, events, and facts, and then codes them into a machine-readable format.  It is a key feature for developers who want to go a step beyond tagging, to understand specifically how all the people, places, and things mentioned in the document are interacting.”

So, it processes natural language, and converts documents and web pages into actionable, semantically enriched “Subject-Action-Object” data, as the company blog describes it.

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