AlchemyAPI
| Company type | Subsidiary |
|---|---|
| Industry | natural language processing, computer vision, big data |
| Founded | 2005 |
| Headquarters | |
| Website | www |
AlchemyAPI is a company that uses machine learning (specifically, deep learning) to do natural language processing (specifically, semantic text analysis, including sentiment analysis) and computer vision (specifically, face detection and recognition) for its clients both over the cloud and on-premises.[1][2] As of February 2014, it claims to have clients in 36 countries and process over 3 billion documents a month. ProgrammableWeb added AlchemyAPI to its API Billionaires Club in September 2011.[2][3]
Technology and business model
AlchemyAPI uses technology similar to IBM's Watson computer.[2] It gets paid per API call, and does over 3 billion API calls per month. A TechCrunch article highlights that even though the technology is similar, AlchemyAPI offers its technology in the form of software as a service (by allowing people to make API calls), making its technological capabilities more accessible to people.[2]
History
AlchemyAPI launched in 2009.[2]
In September 2011, ProgrammableWeb added AlchemyAPI to its API Billionaires Club, alongside giants such as Google and Facebook.[2][3]
In February 2013, it was announced that AlchemyAPI had raised USD 2 million to improve the capabilities of its deep learning technology.[2][4][5][6]
In September 2013, it was reported that AlchemyAPI had created a Google Glass app that could identify what a person was looking at, and that AlchemyAPI would soon be rolling out deep learning-based image recognition as a service.[7][8]
In May 2014, it was reported that AlchemyAPI had released a computer vision API known as AlchemyVision, capable of recognizing objects in photographs and providing image similarity search capabilities.[9]
In March 2015, it was announced that AlchemyAPI had been acquired by IBM and the company's breakthroughs in deep learning would accelerate IBM's development of next generation cognitive computing applications. IBM reported plans to integrate AlchemyAPI's deep learning technology into the core Watson platform [10]
Media coverage
A February 2013 article in VentureBeat about big data named AlchemyAPI as one of the primary forces responsible for bringing natural language processing capabilities to the masses.[11] In November 2013, GigaOm listed AlchemyAPI as one of the top startups working in deep learning, along with Cortica and Ersatz.[12]
References
- ^ "AlchemyAPI". Retrieved February 11, 2014.
- ^ a b c d e f g Williams, Alex (February 7, 2013). "AlchemyAPI Raises $2 Million For Neural Net Analysis Tech, On Par With IBM Watson, Google". TechCrunch. Retrieved February 11, 2014.
{{cite web}}: Italic or bold markup not allowed in:|publisher=(help) - ^ a b DuVander, Adam (September 16, 2011). "New API Billionaire: Text Extractor Alchemy". ProgrammableWeb. Retrieved February 11, 2014.
- ^ "$2m In New Financing, Hiring Several C++ Engineers". AlchemyAPI. February 27, 2013. Retrieved February 11, 2014.
- ^ "Funding Daily: Decisions, decisions". VentureBeat. February 7, 2013. Retrieved February 11, 2014.
- ^ Guess, Angela (February 12, 2013). "Alchemy API raises $2 M". semanticweb.com. Retrieved February 11, 2014.
- ^ Harris, Derrick (September 19, 2013). "AlchemyAPI says it's delivering Google-level deep learning as a service". GigaOm. Retrieved February 11, 2014.
{{cite web}}: Italic or bold markup not allowed in:|publisher=(help) - ^ Simonite, Tom (September 30, 2013). "A Google Glass App Knows What You're Looking At: An app for Google's wearable computer Glass can recognize objects in front of a person wearing the device". Technology Review. Retrieved February 11, 2014.
- ^ Harris, Derrick (May 12, 2014). "AlchemyAPI rolls out deep-learning-based computer vision as a service". GigaOm. Retrieved July 18, 2014.
{{cite web}}: Italic or bold markup not allowed in:|publisher=(help) - ^ Stankiewicz, Jay (March 4, 2015). "IBM Acquires AlchemyAPI, Enhancing Watson's Deep Learning Capabilities". IBM. Retrieved April 14, 2015.
- ^ De Goes, John (February 22, 2013). "'Big data' is dead. What's next?". VentureBeat. Retrieved February 11, 2014.
{{cite web}}: Italic or bold markup not allowed in:|publisher=(help) - ^ Harris, Derrick (November 1, 2013). "The Gigaom guide to deep learning: Who's doing it, and why it matters". GigaOm. Retrieved February 11, 2014.
{{cite web}}: Italic or bold markup not allowed in:|publisher=(help)
