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Showing posts from 2018

2019 - Tech predictions, the realistic view

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Every year I read the tech predictions of the major media outlets, and research companies and I have a different view that I share with my friends. This year I realized it's probably easier to for me to bring the ideas to all my readers as my own 2019 technology predictions. I used the work done from Forbes, and Gartner as my starting point as both have glimmers of truth that help form my list. Forbes and Gartner predictions high level Before I jump in my predictions let's look at the   Forbes 2019 tech prediction article   and  Gartner 2019 top 10  articles. The thematic of their articles are based on these eight ideas: Rise in autonomous things - the idea is that many more manual tasks will be automated in 2019. This includes the use of drones, and robotics powered by better Artificial Intelligence (AI) that will allow the machines to learn and adapt in the natural world.   Augmented reality, and Virtual Reality (VR) will grow into commercial, and industrial

Deploying AI/ML in the cloud securely

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Last month I finished a project with the Azure team that involved building a secure PaaS based solution that provides a step by step guidance and automation to allow researcher to be able to use Machine Learning to run scientific experiment securely. Key thing here is that it's built to be /Secure/ Problem Most times when a traditional experiments are run, an experimenter or researcher starts with a data set they got their hands on, and uses tools such as Jupyter notebook to create an R or Python based experiment. Frequently this experiment is using a simple data science VM or a workstation. The scientist will then run the experiment (which maybe computationally intense) and turn to a cloud solutions to score the experiment in Google or Azure, and finally run Tableau or PowerBI or Excel for visualization. Since researchers are not security experts and do not think that what they are working on should consider their work as possibly sensitive they may expose their work