It’s almost 9 days before the event launches on the Friday night. Even before that, there are a series of workshops / webinars that we are hosting as part of the event in the days leading up to the event. Even then we are:
a/ Making sure that we have people, mentors, marketing, product managers, executives lined up to help where they can. b/ Making sure that we have ideas, platforms, trials, programs, education material lined up to help where it’s feasible. c/ Making sure that we help promote, advocate, market the event so those who would benefit would know about the event and attend.
All this effort for what outcome?
This says it all. And even though this is about #anomalydetection #deepfake #cybersecurity, much of this comes down to data – where the data can be sourced, how the data can be analysed, is the data reliable and can it be trusted.
Over the coming days leading up to the event – there will be plenty of chatter around it. Follow the event on LinkedIn. Some easy ways to follow are:
I’ll be writing more about it here as we go and as new content is available. If you are interested to know or more if you want to join a team or showcase a project or product – head to the Hackmakers website https://hackmakers.com/ to learn more and register.
I would like to show how OIC log management can be achieved with OCI Object Storage (I’ll call it bucket) and OCI Logging Analytics, Visual Builder Studio (used to be Developer Cloud, I’ll call it VB Studio).
Interestingly I’m not going to use OIC to download log files, either to ingest log data from OCI Object Storage. VB Studio will be my tool to do sourcing log files and feeding it to bucket – I’ll be taking advantage of unix shell and oct-cli from VB Studio. Then OCI Logging Analytics will ingest log data from bucket based on cloud event.
On August 17th, we’ll be announcing winners of the #BuildWithAI hackathon and it will be live-streamed on youtube – https://youtu.be/URuB0FtBIJo (note – set your reminder). Cassie Kozyrkov (Chief Decision Scientist, Google), Steve Nouri (Board Member, Hackmakers), Cherie Ryan (Regional MD of ANZ and VP, Oracle) as well as an all-star judging line-up will be there.
Before we get to that, lets rewind, fast-forward and bring together some of the interesting points of the #BuildWithAI hackathon – an event that was truly global in its nature hosted by Hackmakers (https://hackmakers.com/).
July 24th 11:45am AEST – I received a calendar alert for the Leader Mentor Zoom session for the #BuildWithAI hackathon. Trying to finish as many of the things that I needed to get done before I joined this call. This will be interesting. Watching the number of competitors join the event’s slack workspace climbing from a hundred users when I first joined, to now over 3,500 users in the #introductions channel, it was an unique experience. I’m thinking about lots of different things from past hackathons that I’ve participated, mentored, sponsored, hosted – how will this one be any different. I’ll just have to wait and see. And better yet, give to the community and the competitors as much as I can in the time we have.
This moment was not the beginning nor the end of this experience. It was somewhere in between. I’ll give you some background.
Over the past two weeks, there’s been a growing community engagements in the Australian Innovation ecosystem. This specific one that I’m referring to is a … “slack channel was set up and is co-moderated by Dianna Sommerville, founder of the Regional Pitchfest and Community Manager for Bridge Hub. My (Chad Renando) interest is based on my various roles as director of Startup Status, Managing Director Australia with the Global Entrepreneurship network, ESHIP Champion with the Kauffman Foundation, and working with QUT’s Australian Centre for Entrepreneurship research and the Rural Economies Centre of Excellence at USQ.”
Being engaged from a few different angles, I’ve been working on the data itself and this is a story about that the data.
Recently I built a Facial Recognition Mobile App using Oracle Visual Builder having set up the Facial recognition APIs using Tensorflow taking some inspiration from FaceNet. As highlighted above the app does the following: record a video of your face and send it to the API that generates various images and classifies them based on the label we provide at runtime. And in turn, invoke another API that is going to train the machine learning model to update the dataset with the new images and label provided. These two APIs will build a facial recognition Database. Once I have this, I can capture the face and compare that with the dataset I have captured earlier in my Facial recognition Database to output if the face exists in our system.
Here is a quick cheat sheet if you ever wanted to build a mobile app that can take advantage of the camera built into the device, capture the vehicle or vehicles nameplate(s) in a frame and process that image and send it on API that can analyze the image and relay back the information it just scanned. This app can be extended to fulfil requirements like checking if the vehicle registration is up to date or insurance renewal is overdue etc. provided if there are APIs already available that can deliver this information.
So what is the tech involved in building this app?
To build a mobile app that can be deployed on iOS or Android, I used the Visual Builder service from the Oracle Cloud stack. This service provides the capability to build Web as well as Mobile applications through a declarative approach with the ability to introduce code for any complex requirements.
To store the captured image and use the image for downstream application purposes I used the OracleContent & Experience service that comes with a rich set of APIs for content ingestion, public document link generation etc. From an enterprise architecture viewpoint, it makes sense to store the images with metadata in a content store, so I decided to archive the image using this service as part of the mobile app build process.
The most significant bit is to use a library / API that can process the image or OCR and send back the information we are interested n. For these purposes, I used the open source ALPR library. There are API’s available already if you want to fast track your app.
This one is optional. If you want to validate the information captured, we can set up a few API’s using the Oracle Autonomous Database with some data to complete the validation flow in the app.
In November 2018, I had the privilege to attend the Australian Oracle User Group national conference “#AUSOUG Connect” in Melbourne. My role was to have video interviews with as many of the speakers and exhibitors at the conference. Overall, 10 interviews over the course of the day, 90 mins of real footage, 34 short clips to share and plenty of hours reviewing and post-editing to capture the best parts.
I’ve been using VBCS for awhile now and it has really evolved over the past nine months. I guess that’s one of the wonderful things about these PaaS offerings from Oracle; we don’t have to wait so long for new features and capabilities.
Well, I figured out a way to do this in VBCS. Now I will admit right away, this is pretty ugly, so if you are a software development purist, please turn off your TV now!
I am thrilled with the Oracle’s Gen2 Cloud Infrastructure architecture, where Oracle completely separates the Cloud Control Computers from the User Code, so that no threats can enter from outside the cloud and no threats can spread from within tenants.
Obviously with more security, there comes more coordination, especially at the moment of invoking OCI resources APIs. Luckily, Oracle did a good job at providing a simple to use CLI and SDK (see here for more information).
For the purpose of this blog, I built a simple NodeJS application that helps demystify the security aspect of invoking OCI APIs. Check this link for examples of running similar code across other Programming Languages.
My NodeJS application manages OCI resources in order to:
List ADW instances
Stop an ADW instance
Start an ADW instance
I started this NodeJS application to list, start and stop ADW resources. However, I designed this application to easily extend it to invoke any other type of OCI resources.
I containerised this application with Docker, to make it easier to ship and run.