AI News, Software artificial intelligence
Software Development Manager, Alexa Artificial Intelligence -- New Initiative
The ideal candidate will have experience in deep neural networks, and will have developed highly available systems (four nines) over the course of their career.As part of the team you will:· Green-field opportunity to create the artificial intelligence platform behind Alexa!· Design and build systems that scale across millions of active users and devices.· Be in charge of the complete software development lifecycle;
Artificial Intelligence and Machine Learning in Software as a Medical Device
Artificial intelligence and machine learning technologies have the potential to transform health care by deriving new and important insights from the vast amount of data generated during the delivery of health care every day.
The FDA is considering a total product lifecycle-based regulatory framework for these technologies that would allow for modifications to be made from real-world learning and adaptation, while still ensuring that the safety and effectiveness of the software as a medical device is maintained.
real-world examples of artificial intelligence and machine learning technologies include: Adaptive artificial intelligence and machine learning technologies differ from other software as a medical device (SaMD) in that they have the potential to adapt and optimize device performance in real-time to continuously improve health care for patients.
The ideas described in the discussion paper leverage practices from our current premarket programs and rely on IMDRF’s risk categorization principles, the FDA’s benefit-risk framework, risk management principles described in the software modifications guidance, and the organization-based total product lifecycle approach (also envisioned in the Digital Health Software Precertification (Pre-Cert) Program).
This plan would include the types of anticipated modifications—referred to as the “Software as a Medical Device Pre-Specifications”—and the associated methodology being used to implement those changes in a controlled manner that manages risks to patients —referred to as the “Algorithm Change Protocol.” In this approach, the FDA would expect a commitment from manufacturers on transparency and real-world performance monitoring for artificial intelligence and machine learning-based software as a medical device, as well as periodic updates to the FDA on what changes were implemented as part of the approved pre-specifications and the algorithm change protocol.
- On 25. oktober 2020
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