Data Clean Rooms: Advantages and Disadvantages

Data clean rooms are increasingly becoming a necessity for companies that are doing a lot of data-driven work – but they come with their own sets of advantages and disadvantages. Firms that share their own first-party data with other parties, such as outsourcing partners and research institutions, can use data clean rooms to ensure that […]

What is a Data Clean Room? What DCRs Can (and Can’t) Do

Data collaboration between multiple parties is revolutionary, offering almost endless potential for businesses and societies to innovate and improve. Yet it is also fundamental, increasingly a necessity for companies to unlock the insights they need to serve their customers effectively and maximize revenue. Collaboration often involves sensitive data, including personally identifiable information (PII). As a […]

Intel, Duality, and Security in Life Sciences 

Data Vulnerabilities and the Need for Data Security  In the life sciences field, enormous amounts of essential data exist, often containing sensitive information. This data could encompass anything from patient clinical records and genomics to clinical trial recruitment and AI model/analytics. These types of information are very attractive to cyber threats, and the consequences of […]

Duality Deepens Investment into Government Sector

GOVERNMENT BUSINESS VETERAN STEF FARRAND IS LATEST ADDITION TO DUALITY GO-TO-MARKET TEAM Hoboken, New Jersey – (February 23, 2023)  Duality Technologies, the leader in privacy preserving data collaboration, today announced its continued commitment to the government sector, with the addition of business development veteran Stef Farrand.  Farrand will lead Duality’s federal sales engagements and comes […]

Secure Federated Learning: Protecting the Data and the Model

Secure Federated Learning

Introduction to Secure Federated Learning Federated Learning (FL) is a distributed machine learning (ML) technique that enables model training on data from multiple, decentralized servers with local data samples, without exchanging or moving data. This approach ensures that the data remains in its original location and is not exposed to any other parties. Another characteristic […]