Derrick Harris of GigaOM reports, “Denver-based startup AlchemyAPI is keeping proactive in the world of artificial intelligence, launching on Monday night a new service that lets users perform computer vision tasks such as image-tagging and photo search via API. The product, called AlchemyVision, is the company’s first foray outside the natural-language processing space where it has focused since 2011. It also probably foreshadows a spate of computer vision services yet to come. AlchemyAPI first demonstrated its object recognition service in September but Turner said the company has done a lot of work in the meantime to get it ready for commercial use. Among the big differences is the sheer scale of the new system, which is running unsupervised across millions of online images and using context from the pages they’re housed on in order to determine what they are.” Read more
Posts Tagged ‘AlchemyAPI’
Seth Grimes posted to Smart Data Collective a conversation he had with Elliot Turner of AlchemyAPI. He asked Turner, “How well are we doing with Natural Language Processing, noting that formally, ‘processing’ includes both understanding and generation, two parts of a conversation?” Turner responded, “Google has trained us to search using keywords, and this won’t change overnight. But the trend is easy to spot: the interactive question-answering capabilities made famous by IBM’s Watson will become commonplace, offered at a fraction of today’s costs and made available as easy-to-integrate web services.” Read more
DENVER, Aug. 6, 2013 /PRNewswire/ – One of the hottest buzzwords in technology today is “big data.” Companies that learn how to leverage the massive amount of data that exists in the ether have an automatic advantage over their competitors. However, most companies don’t realize that 80% of data is unstructured and rarely utilized by businesses. Natural language processing software makes unstructured text meaningful and valuable for enterprises with big data initiatives. Today, AlchemyAPI released the first in a series of white papers explaining the benefits of text analysis and the reasons companies should use text analysis as part of their business strategy. Read more
Amy Castor of Programmable Web reports, “AlchemyAPI wants to make a type of artificial intelligence known as deep learning accessible not only to giant corporations, but to the public. Over the last year, the Denver company has been weaving the technology into its text mining API, recently announcing updates in the areas of relation extraction and named entity extraction. Launched in 2008, AlchemyAPI crunches through hundreds of billions of words of text on the Internet to delve meaning out of what people are saying, doing, thinking and writing about. The company offers its service, which developers use for media monitoring, ad targeting, surveillance and more, in the form of a RESTful API or a behind-the-firewall appliance.” Read more
AlchemyAPI is looking for a C++ Engineer – AI/NLProc/Big Data in Denver, CO. The post states, “We’re looking for experience C++ engineers to join our team. If you can write multi-threaded code in your sleep — call us. If you love STL and Boost, come talk to us. If you enjoy writing performance-optimized code that must run reliably for years without memory leaks or segmentation faults, we want to talk to you. You’ll get an opportunity to work on some really interesting projects that have a major impact.” Read more
AlchemyAPI has announced “the release of German sentiment analysis, adding to the company’s already-supported languages for identifying positive / negative opinions within any document or web page. ‘Our German sentiment analysis engine provides advanced functionalities such as amplifier, diminisher, and negation support,’ said Elliot Turner, CEO of AlchemyAPI. ‘We’re the first commercially-available German sentiment engine to support document-level processing as well as entity/keyword/user-targeted analysis’.” Read more
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In this segment of our “Innovation Spotlight” we spoke with Elliot Turner (@eturner303), the founder and CEO of AlchemyAPI.com. AlchemyAPI’s cloud-based platform processes around 2.5 billion requests per month. Elliot describes how their API helps companies with sentiment analysis, entity extraction, linked data, text mining, and keyword extraction.
Sean: Hi Elliot, thanks for joining us, how did AlchemyAPI get started?
Elliot: AlchemyAPI was founded in 2005 and in the past seven years has become one of the most widely used semantic analysis APIs, processing billions of transactions monthly for customers across dozens of countries.
I am the Founder and CEO and a serial entrepreneur who comes from the information security space. My previous company built and sold high-speed network security appliances. After it was acquired, I started AlchemyAPI to focus on the problem of understanding natural human language and written communications.
Sean: Can you describe how your API works? What does it allow your customers to accomplish?
Elliot: Customers submit content via a cloud-based API, and AlchemyAPI analyzes that information in real-time, transforming opaque blobs of text into structured data that can be used to drive a number of business functions. The service is capable of processing thousands of customer transactions every second, enabling our customers to perform large-scale text analysis and content analytics without significant capital investment.
One of the issues organizations confront when they take to semantically processing data is how to handle all the results of that work. The output of extracting entities, tagging concepts, classifying page topics and parsing sentiment makes its way to a data store that can get pretty big, making for intense storage and analytics demands.
Orchestr8’s NLP- and machine learning-based AlchemyAPI service, which just last week added sentiment analysis to its retinue, gives content providers, social media monitoring companies, and contextual advertising sectors the tools for all of the above that leads to those big data stores, and now it has in beta a solution for dealing with the demands that creates, too. Its Alchemy SAS (Semantic Analysis System) – a name that is subject to change, by the way – processes content, takes what is generated thanks to the functionality within the AlchemyAPI, and stores and organizes the content analysis and meta-data results into a cloud data store for customers to query and discover patterns in.