Company:PolyAI
| Type | Private |
|---|---|
| Founded | 2017 |
| Founders | Nikola Mrkšić Pei-Hao Su Tsung-Hsien Wen |
| Headquarters | London , United Kingdom |
| Website | polyai |
PolyAI is a UK-based company developing enterprise voice assistants for customer service using conversational artificial intelligence.[1] The voice assistants use proprietary machine learning and natural language processing technology.[2][3]
History
PolyAI was founded in 2017 by Nikola Mrkšić, Pei-Hao Su and Tsung-Hsien Wen.[4] The three founders met at the Machine Intelligence Lab at the University of Cambridge[5] where they studied under Professor Steve Young.[6]
In 2019 the company raised €10.7 million in Series A funding in an investment round led by Point72 Ventures, with participation from Sands Capital Ventures, Amadeus Capital Partners, Passion Capital, and Entrepreneur First.[4]
The company was awarded Company of the Year 2019 by the Cambridge Computer Lab Ring.[7]
PolyAI was named to the 2021 CB Insights AI 100 List of Most Innovative Artificial Intelligence Startups.[8]
In November 2021, an early technical error during testing which resulted in the company's voice assistant responding sarcastically to customer requests was highlighted in a Washington Post article on the ethics of artificial intelligence.[9]
Technology
ConveRT
PolyAI developed a proprietary dual-encoder model, ConveRT, released on the public domain in April 2020. The model uses subword representations and light-weight transformer-style blocks to encode text, resulting in a model that can be quantized to under 60MB[10], while relying on significantly fewer training parameters than generalist models such as BERT.[11] The ConveRT model was later taken down from the public domain in September 2020.[12]
ConVEx
ConVEx is a conversational value extractor which utilizes an efficient pre-training and fine tuning neural approach for slot-labeling dialog tasks, a critical natural language understanding component of task-oriented dialog systems.[13]
References
- ↑ "PolyAI Company Profile: Valuation & Investors | PitchBook". https://pitchbook.com/profiles/company/227011-60.
- ↑ "How PolyAI is Redefining the Customer Service Call". https://tech.co/crm-software/poly-ai-conversational-customer-service.
- ↑ "PolyAI scores $12M Series A to put its 'conversational AI agents' in contact centres". https://social.techcrunch.com/2019/03/08/polyai/.
- ↑ 4.0 4.1 Loritz, Mary (March 8, 2019). "London-based PolyAI raises €10.7 million for its conversational AI customer support platform". https://www.eu-startups.com/2019/03/london-based-polyai-raises-e10-7-million-for-its-conversational-ai-customer-support-platform/.
- ↑ O'Hear, Steve. "PolyAI scores $12M Series A to put its ‘conversational AI agents’ in contact centres". https://techcrunch.com/2019/03/08/polyai/.
- ↑ "PolyAI targets $1.3 trillion market with conversational AI | Business Weekly | Technology News | Business news | Cambridge and the East of England". https://www.businessweekly.co.uk/news/hi-tech/polyai-targets-13-trillion-market-conversational-ai.
- ↑ Samols, Jan (January 23, 2018). "Hall of Fame Awards". https://www.cst.cam.ac.uk/ring/awards.
- ↑ "AI 100: The Artificial Intelligence Startups Redefining Industries". https://www.cbinsights.com/research/report/artificial-intelligence-top-startups/.
- ↑ Olson, Parmy (November 26, 2021). "That Chatbot Just Make A Rude Joke?". The Washington Post. https://www.washingtonpost.com/business/did-that-chatbot-just-make-a-rude-joke/2021/11/25/e20da8ee-4dce-11ec-a7b8-9ed28bf23929_story.html.
- ↑ Henderson, Matthew; Casanueva, Iñigo; Mrkšić, Nikola; Su, Pei-Hao; Wen, Tsung-Hsien; Vulić, Ivan (2019). "ConveRT: Efficient and Accurate Conversational Representations from Transformers". arXiv:1911.03688 [cs.CL].
- ↑ Kahn, Jeremy (October 6, 2020). "Which A.I. planet do you live on?". Fortune. https://fortune.com/2020/10/06/which-a-i-planet-do-you-live-on/.
- ↑ "PolyAI-LDN/polyai-models". March 11, 2021. https://github.com/PolyAI-LDN/polyai-models.
- ↑ Henderson, Matthew; Vulić, Ivan (2020). "ConVEx: Data-Efficient and Few-Shot Slot Labeling". arXiv:2010.11791 [cs.CL].
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