Melbourne, Australia — 19 May 2022 — Australian technology consultancy, DiUS (https://dius.com.au/), announces that it is the first partner to attain the AWS Applied AI Competency in Asia Pacific and Japan.
Founded in 2004, DiUS is a leading Australian technology consultancy that specialises in using emerging technology—cloud, IoT, big data, artificial intelligence and machine learning—to solve difficult problems, get new ideas to market or disrupt traditional business models.
The AWS Competency Program is designed to showcase AWS Partner Network (APN) partners who develop, deploy, and maintain best-in-class Machine Learning (ML) solutions that positively impact customer outcomes. To become an AWS Applied AI Competency Partner, companies undergo a rigorous validation process focussing on technical proficiency with the AWS ML platform, underpinned by proven customer success. APN partners must also successfully complete a technical audit of their ML practice.
An early adopter of the cloud, DiUS has leveraged the AWS cloud platform and services since 2007 and has been an AWS Advanced Consulting Partner since 2012. DiUS was also the first partner in Australia and New Zealand to attain the AWS Machine Learning Competency in 2019.
“DiUS has always prided itself on delivering innovative and impactful outcomes for its clients, which includes helping organisations to solve complex, real world problems using the latest ML techniques and algorithms” said DiUS co-founder and CEO, Joe Losinno.
“Our strong partnership with AWS has also allowed us to leverage the latest advancements in AI services, and understand how those technologies can drive competitive advantage for our clients. Attaining the AWS Applied AI Competency builds on our long-term success with AWS and we’re thrilled to again be recognised as a leader in this space.”
There is high demand from organisations in the region to deliver on the promise of Machine Learning, from transforming the customer experience to providing operational efficiencies. DiUS’ specialist ML practice meets these needs by helping organisations focus on the right problems, address data-related challenges, take ideas from experimentation to production and build in-house ML capabilities.
Last year, DiUS surveyed over 200 organisations in Australia to understand the challenges and priorities for Machine Learning. Unsurprisingly, they found that 82% of organisations were interested in Machine Learning, yet only 21% had one or more models in production.
Applying Machine Learning in a real-world business context is still relatively new and its project management practices are less mature than those in software development. It also requires different toolsets, infrastructure and workflows. This involves being able to understand how to frame the problem, train the models, and select the right performance metrics, and finally, deploy and productionise the model—all within a much broader business context. [Download the Machine Learning in Australia National Pulse Report – https://dius.com.au/machine-
More recently, interest in DiUS’ Machine Learning services have been driven by the application of computer vision models, with a view to augment human decision-making and reinvent traditional business processes—freeing up workers to focus on more high-value tasks, increase productivity and drive better business outcomes.
Increasingly, DiUS is seeing a requirement for computer vision processing to be done locally on devices, especially in scenarios where there is a need to reduce latency and provide real-time responses, limited network availability and/or privacy and security concerns. In addition to computer vision, DiUS is seeing a strong interest in other application areas including recommendation systems, text classification, schedule optimisation, forecasting and online fraud detection.
A new kind of customer experience
DiUS partnered with bolttech (https://bolttech.io/), an international insurtech to create a new, AI-driven experience for protection and insurance for smartphones—replacing a process that typically required a physical inspection with a fully digital solution.
Working closely with bolttech’s innovation lab, DiUS helped develop a solution that leveraged multiple state-of-the-art computer vision models, run in PyTorch and hosted on Amazon SageMaker, in just six weeks.
“Delivering a production-grade, computer-vision driven customer experience needs more than technical expertise. It requires a deep understanding of the way humans interact with machines and in how to train machines to understand and process real-world data and images.
DiUS’ proven expertise in AI and learning-based image segmentation analysis helped us rapidly progress from proof of concept to production, to continuous delivery. This has been executed with improving model accuracy, accelerated training time and zero-downtime in deployment of model updates.” said Group Chief technology Officer of Bolttech, David Lynch.
In parallel, DiUS helped improve the data collection process to support model training. Then, to get the performance needed, the team trained the model by applying data augmentation and multi-GPU model parallelism. Two computer vision models were built – one edge model for real-time interaction with the user and a second, more complex model for screen damage assessment hosted in Amazon SageMaker.
Since launch, Click-to-Protect has gone live in seven markets including France, Hong Kong, Italy, Malaysia, Philippines, Thailand, and South Korea, with eight partners in total.[Learn how DiUS helped Bolttech enable a new kind of customer experience with next-gen machine learning – https://dius.com.au/case-