DeveloperWeek Seattle: Cloud Edition

I will discuss both the current state of research in Ai as well as some of the ethical and regulatory challenges that we are currently facing in the medical field.  It is estimated that data in healthcare will double every 73 days, however much of this data is lost in silos, and research and innovation stunted by poor interoperability as well as data harmonization abilities. Although we have made advances in being able to personalize medicine, image recognition, and identify target genes for novel therapies, improvements in the ability to validate these topics, lack of discourse between datascientists and physicians, and important ramifications of algorithms (e.g influencing someone's life or well being) is necessary for the field to advance. Additionally, our work has demonstrated that most ML algorithms do not perform better than logistic regression, which has been used by the medical field for decades, raising the question of what additive benefits in many clinical scenarios ML may have. Finally, I urge individuals to consider what we are optimizing (length of life? quality of life?) and how some of these metrics may be measured or achieved.

There are already hundreds of AI functions available via different APIs. Pick Machine Translation, Sentiment Analysis, Image Tagging or anything else - there's already a choice of 20-30 AI vendors to pick from. I will make a brief overview of what types of models are already available in the cloud, which of those enable customization and important things to look after when selecting the model (or a set of those) for a specific project. I will also touch AI API developer experience, to give an idea what a developer should be prepared for when choosing the API to work with.

“Shifting left” on security and compliance (finding and fixing vulnerabilities and policy violations earlier in the application development lifecycle) can have a huge payoff in being able to deliver software faster and more frequently. Applying DevSecOps approaches to cloud infrastructure can eliminate time-consuming certification processes and security audits and increase application reliability. This session will walk through how to begin thinking about and implementing “shifting left” on cloud infrastructure security and compliance. Attendees will learn practical steps to: - Create a developer and operations-oriented approach to cloud security - Automate infrastructure validations into CI/CD pipelines using policy-as-code - Automate audits for continuous compliance and cost savings - Improve collaboration and reduce friction between departments - Build a business case to gain buy-in with different stakeholders

During the presentation, I am going to talk about the building secure architecture to access remote devices using reverse proxy and ssh tunnels.