The Basics of Differential Privacy & Its Applicability to NLU Models

Over the years, large pre-trained language models like BERT and Roberta have led to significant improvements in natural language understanding (NLU) tasks. However, these pre-trained models pose a risk of potential data leakage if the training data includes any personally identifiable information (PII). To mitigate this risk, there are two common techniques to preserve privacy: … Read more

The Privacy Risk of Language Models

In today’s world, large models with billions of parameters trained on terabytes of datasets have become the norm as language models are the foundations of natural language processing (NLP) applications. Several of these language models used in commercial products are also being trained on private information. An example would be Gmail’s auto-complete model. Its model … Read more

When the Curious Abandon Honesty: Federated Learning Is Not Private

Previously on Private AI’s speaker series CEO, Patricia Thaine, sat down with Franziska Boenisch to discuss her latest paper, ‘When the Curious Abandon Honesty: Federated Learning Is Not Private’.  Franziska completed a Master’s degree in Computer Science at Freie University Berlin and Technical University Eindhoven. For the past 2.5 years, she has been working at Fraunhofer AISEC as a Research … Read more

9 Companies to Help You Get Your Privacy $hit Together

9 Companies to Help You Get Your Privacy $hit Together

With the ever-growing number of global regulations, legislations, and amendments, it can be overwhelming to know where to start (or continue) your data privacy journey. Below we’ve compiled a list of 9 companies who can help you build a proactive privacy, governance, and risk management strategy within your organization.  1. Establish your company’s privacy baseline … Read more

5 Facts You Probably Didn’t Know About Data Privacy

5 Facts You Probably Didn’t Know About Data Privacy

Data privacy, in simplest terms, is the right to control how your personal information is collected and used. Although this may seem obvious, it hasn’t always been the case. With data being generated in mass amounts daily, it’s interesting that the earliest data protection laws like the Data Protection Act only started to emerge in … Read more

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Language Packs

Expand the categories below to see which languages are included within each language pack.
Note: English capabilities are automatically included within the Enterprise pricing tier. 

French
Spanish
Portuguese

Arabic
Hebrew
Persian (Farsi)
Swahili

French
German
Italian
Portuguese
Russian
Spanish
Ukrainian
Belarusian
Bulgarian
Catalan
Croatian
Czech
Danish
Dutch
Estonian
Finnish
Greek
Hungarian
Icelandic
Latvian
Lithuanian
Luxembourgish
Polish
Romanian
Slovak
Slovenian
Swedish
Turkish

Hindi
Korean
Tagalog
Bengali
Burmese
Indonesian
Khmer
Japanese
Malay
Moldovan
Norwegian (Bokmål)
Punjabi
Tamil
Thai
Vietnamese
Mandarin (simplified)

Arabic
Belarusian
Bengali
Bulgarian
Burmese
Catalan
Croatian
Czech
Danish
Dutch
Estonian
Finnish
French
German
Greek
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Italian
Japanese
Khmer
Korean
Latvian
Lithuanian
Luxembourgish
Malay
Mandarin (simplified)
Moldovan
Norwegian (Bokmål)
Persian (Farsi)
Polish
Portuguese
Punjabi
Romanian
Russian
Slovak
Slovenian
Spanish
Swahili
Swedish
Tagalog
Tamil
Thai
Turkish
Ukrainian
Vietnamese

Rappel

Testé sur un ensemble de données composé de données conversationnelles désordonnées contenant des informations de santé sensibles. Téléchargez notre livre blanc pour plus de détails, ainsi que nos performances en termes d’exactitude et de score F1, ou contactez-nous pour obtenir une copie du code d’évaluation.

99.5%+ Accuracy

Number quoted is the number of PII words missed as a fraction of total number of words. Computed on a 268 thousand word internal test dataset, comprising data from over 50 different sources, including web scrapes, emails and ASR transcripts.

Please contact us for a copy of the code used to compute these metrics, try it yourself here, or download our whitepaper.