Recent advancements in AI – implications for medical device technology and certification

whitePaper | January 5, 2020

Machine learning (ML) is an application of artificial intelligence (AI) that allows systems to automatically learn and improve from exposure to more data without being explicitly programmed. ML focuses on the development of computer programs that can access data and use it to learn for themselves.1 While AI represents the broader concept of machines being able to carry out tasks in an intelligent way, machine learning is a current application of AI based on the idea that we can give machines access to data, and they can use that data to learn for themselves.

whitePaper | December 6, 2019

Machine learning (ML)-driven personalization is fast expanding from social media to the wider information space, encompassing legacy media, multinational conglomerates and digital-native publishers: however, this is happening within a regulatory and oversight vacuum that needs to be addressed as a matter of urgency. Mass-scale adoption of personalization in communication has serious implications for human rights, societal resilience and political security. Data protection, privacy and wrongful discrimination, as well as freedom of opinion and of expression, are some of the areas impacted by this technological transformation.

whitePaper | May 31, 2022

End-to-End (E2E) testing has traditionally been seen as a ‘final frontier’ of sorts in software development.

whitePaper | October 6, 2022

It is not unusual to see software development trends change year after year. The pandemic has only accelerated the whole process, and it seems that the trends are changing even faster. What was once considered as acceptable practice in software development might no longer be the case in the foreseeable future. This is why startup founders and big corporation managers should be aware and well-informed of where all the software industry trends are heading to and how to strategize in the best possible app to develop and place an app.

whitePaper | November 30, 2022

The first-generation low-code platforms required considerable adaptations and months of development in the late 1990s and early 2000s. Gartner expects that by 2024, low-code/no-code automation will account for 65% of all app development.

whitePaper | March 30, 2022

The Stanford Institute for Human-Centered Artificial Intelligence (HAI) offers the following submission for consideration in response to the Request for Information(RFI) by the White House Office of Science and Technology to the Update of the National Artificial Intelligence Research and Development Strategic Plan.