Žiga Vaupot's Blog

I recently returned from Reading, UK, where I had the opportunity to attend the UKOUG 2023 conference . This year's event was particularly engaging, commemorating the 40th anniversary of the UK Oracle User Group. My participation at the conference had a dual purpose. Firstly, I attended to present, and while I was there, I had the chance to join several presentations that piqued my interest. I'm genuinely impressed by the innovative solutions showcased and the quality of work demonstrated by the presenters and their teams. My winners My standout presentation was LLMs are the Future of Conversational AI  by Antony Heljula of TPXimpact. Antony shared his experiences in developing chatbots that leverage large language models in conversational AI. Truly groundbreaking! A close second for me was Gianni Ceresa's (DATAlysis) presentation titled ID Please: Did You Already Ask That to Your Data?  Gianni delved into the crucial aspects of data lineage and governance, addressing the...

This little exercise started a few weeks back. What we tried to test is how Oracle AI Vision performs on a larger database for real. In order to perform this little test we used Chest X-Ray Images (Pneumonia)   dataset from kaggle.com . Let me begin with the following note:  We built the model as described below, but then we encountered an error which caused all the images to be classified as “pneumonia ” .  In the same time we had an opportunity to work closely with Oracle AI Services development team who have responded instantly and successfully removed the bug. And here are the results. Train The process of training the model is code free . Similarly as described in one of my previous blog posts , we needed a new custom project. Project acts as a container which can contain several models we created. There is a wizard that helps users to create a new one. The wizard is executed in three steps.  In the first step, basic parameters are set, such as the type of the ...

Oracle AI Services With this blog post I am still discovering various cloud services that constitute Oracle Data Lakehouse . This time I am looking at Oracle AI Services . Oracle describes these AI services as pre-trained models that can be custom trained with an organisation’s own data to improve model quality, making it easier for developers to adopt and use AI technology . OCI provides the following prebuilt services: Digital Assistant Language Speech Vision Anomaly Detection. In this blog post, I am playing wih Vision AI Service.  Vision AI Service OCI Vision   applies computer vision to analyze image-based content. Developers can easily integrate pretrained models into their applications with APIs or custom train models to meet their specific use cases. These models can be used to detect visual anomalies in manufacturing, extract text from documents to automate business workflows, and tag items in images to count products or shipments . Basically, what Vision AI Service d...