In the last post, we talked briefly about the Oracle Digital Assistant. In this post, I would like to walk you through the provisioning process of the Autonomous Oracle Digital Assistant.
If you are following the Oracle Autonomous Mobile and Chatbot Platform announcements you would have now realised that we have announced the availability of the Oracle Digital Assistant platform as a new SKU under the PaaS offerings.
In this post, I will delve deeper into the Oracle Digital Assistant offering and answer what I anticipate will be common questions about the changes.
Building a Multi-Lingual Bot on the Oracle Chatbot Platform
First things first, if you are new to building Chatbot using the Oracle Cloud Platform, here are some quick videos to get you started on the platform and its capabilities. There is also an online MOOC (Massive Open Online Course) available on how to build your first BOT using the Oracle Platform and access the Bot through Facebook Channel.
Now that we understand how to build a bot let’s turn the Bot that can recognise the input from the end user conversing in his/her own language and respond accordingly.
The Bot platform allows you to bring your own translation keys (Google / Bing) and the Bot can be configured to detect the language. The bot further converts the user input to English, intent recognition by the NLP engine kicks off, based on the dialogue flow the bot structures the response in English which is again translated back into the language in which the question was asked by the user.
Let’s see that this in action :
The latest VBCS 2.0 release makes developing Mobile Applications faster using a declarative drag and drop approach while giving the flexibility to the developer to inspect the code and inject any additional code that the tool doesn’t provide out of the box. You can build your app from the browser itself without the need for any code editor.
Here is a quick tutorial on how to build a Mobile app using VBCS.
Once you develop your mobile app, you can create an Android or iOS build profile that will allow the tool generate the QR code so that you can test your mobile app on the device of your choice.
A few days ago, we published an article that shows how to provision and connect to Oracle Autonomous Transaction Processing Database (ATP). Based on this, we got multiple requests to also demonstrate how to extend the connection to the Autonomous DB, not only from SQL Developer, but also from polyglot microservices.
In this blog, we are going to take a step forward and create a simple “Hello World” NodeJS application that exposes some REST APIs that push and pull data using an Oracle Autonomous DB. The idea is to give you all knowledge required, to be start building your own microservices, consuming data from Autonomous DB.
Last weekend, I was at the Code Network Winter Hackathon event in Brisbane – https://codenetwork.co/winter-hackathon-2018/. I was there as a sponsor, workshop presenter, mentor and just a general supporter. As such there was some down-time between different activities. So, what a great time to sit down and work on something that I have no idea about (technically) – #Blockchain and Hyperledger. So, as a normal person does – I went searching for relevant content to help. Here’s a couple of the searches that I did.
Unfortunately, through many different searches and reading lots of things it became apparent that I didn’t know much and there was lots to learn. There seemed to a massive amount information that looked great. There was content that talked about what a Blockchain is. There was content that talked about the business use cases and examples of why you use a Blockchain technology. There was code that built a Blockchain. I found plenty smart contract examples on github. I learnt more about what I needed to know but it didn’t get me to the place that I wanted to be.
So – how do I develop and play with a Smart Contract?
We all know that data is massively valuable to businesses, whether it is to support daily business transactional activities (Online Transaction Processing – OLTP), or to help business with planning, problem solving and decision making (Online Analytical Processing – OLAP). Either way, businesses heavily rely on both ways to support their most important strategies and activities.
Until recently, companies had to heavily invest in provisioning, securing, patching and driving either way of Online Data processing mechanisms. In most cases, even with Cloud adoption, companies still had to rely on their own skills to make sure that their databases were properly patched, secured, tuned and managed.
However, today there is another option with the recent announcements that Oracle have made around Autonomous Databases for both OLAP and OLTP data processing. What this means, is that Oracle has taken automation to a totally new level with the assistance of Machine Learning. The idea is that the DB itself is self-sufficient with a full set of automated activities that range from patching, securing, optimising, etc. This will reduce not only the effort to run data workloads, but removing completely human errors, creating the opportunity to not only keep the lights on, but to focus on crucial business activities around innovation and differentiation.