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Our guest on the podcast this week is Adrian Bowles, VP of Research and Lead Analyst, Artificial Intelligence at Aragon Research.
We discuss how sometimes you can find more impactful insights from smaller boutique research firms than the larger giants. Aragon Research is a full spectrum industry analyst research firm who provides advisory services to those who are building, buying, or investing in emerging technologies.
We take a look at the latest announcements Amazon CTO Werner Vogels made at the latest AWS Summit. We look at new SaaS contracts in the AWS Marketplace allowing smaller SaaS companies to outsource their billing to AWS.
Amazon is a company that seems to keep doing things right. They are hard to avoid as leaders in cloud computing right now. Even when they make mistakes they seem to be able to pivot them quickly into useful tools. They own somewhere around 80% of the public cloud market at the moment and it is no surprise why because they have the best technology.
We also look at Amazon CodeStar, their improved database services, and upgraded machine learning tools such as Amazon Rekognition.
Amazon Rekognition uses machine learning for image detection to automatically monitor content. This allows us to identify objectionable images automatically. This has use-cases anywhere from identifying fake news to preventing issues with advertisements on objectionable content. Amazon is using machine learning to look at images and rank them on a 9-point scale of how objectionable the image is.
Rekognition is a deep learning service, meaning it is built on several layers of neural networks, the first layer being feature recognition, the next a classification of objectionable content, and so on. As of now, Amazon has built in a standard scale, but it would be interesting if they let users choose their own parameters for what is objectionable. Giving context for content is a difficult step in the process, which would be an interesting next move for Amazon also. There needs to be an objectionable rating for users so that the system can learn individual preferences as well.
We also discuss data privacy, and how zombie cloud data can haunt you when you think it has been deleted but it still exists somewhere else. There are legal issues around this zombie data that are being exposed now even with subjects like student standardized testing. Of course, sometimes this can be a great feature when you accidentally delete something and there is a way to find it again.
Our guest on the podcast this week is Adrian Bowles, VP of Research and Lead Analyst, Artificial Intelligence at Aragon Research.
We discuss how sometimes you can find more impactful insights from smaller boutique research firms than the larger giants. Aragon Research is a full spectrum industry analyst research firm who provides advisory services to those who are building, buying, or investing in emerging technologies.
We take a look at the latest announcements Amazon CTO Werner Vogels made at the latest AWS Summit. We look at new SaaS contracts in the AWS Marketplace allowing smaller SaaS companies to outsource their billing to AWS.
Amazon is a company that seems to keep doing things right. They are hard to avoid as leaders in cloud computing right now. Even when they make mistakes they seem to be able to pivot them quickly into useful tools. They own somewhere around 80% of the public cloud market at the moment and it is no surprise why because they have the best technology.
We also look at Amazon CodeStar, their improved database services, and upgraded machine learning tools such as Amazon Rekognition.
Amazon Rekognition uses machine learning for image detection to automatically monitor content. This allows us to identify objectionable images automatically. This has use-cases anywhere from identifying fake news to preventing issues with advertisements on objectionable content. Amazon is using machine learning to look at images and rank them on a 9-point scale of how objectionable the image is.
Rekognition is a deep learning service, meaning it is built on several layers of neural networks, the first layer being feature recognition, the next a classification of objectionable content, and so on. As of now, Amazon has built in a standard scale, but it would be interesting if they let users choose their own parameters for what is objectionable. Giving context for content is a difficult step in the process, which would be an interesting next move for Amazon also. There needs to be an objectionable rating for users so that the system can learn individual preferences as well.
We also discuss data privacy, and how zombie cloud data can haunt you when you think it has been deleted but it still exists somewhere else. There are legal issues around this zombie data that are being exposed now even with subjects like student standardized testing. Of course, sometimes this can be a great feature when you accidentally delete something and there is a way to find it again.