Amazon Rekognition is an out-of-the-box machine learning platform for image and video analysis. We recently published a blog post that explored its potential use cases, from retail and hospitality to transport and logistics.

We also delved into the depths of its many capabilities, including custom labels. Here’s an overview from AWS:

With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. …

DiUS Machine Learning in Australia, National Pulse Report 2021
DiUS Machine Learning in Australia, National Pulse Report 2021
Our national pulse report

Here at DiUS, we’ve been talking with many companies about leveraging ML over the past five years and found most organisations want to adopt ML, yet this transformative technology is not being adopted at the rate it should be.

In fact, our experience has been that a great proportion of organisations struggle to move beyond proof-of-concept or pilot stage. Picking the right problem, data challenges, model accuracy and application integration can be big blockers, either delaying or preventing ML project success. …

Image credit: AWS

From personal assistants such as Siri and Alexa, to customer service chatbots like nibby and recommendation engines on Netflix, the real-world applications of machine learning are extensive. In fact, machine learning is now proving an essential technology for many organisations and industries due to its ability to streamline processes, drive efficiencies and improve customer experiences.

But one of the most widely used types of machine learning, which has vast power and potential, is computer vision. …

New idea for a business or product?

I’m always coming up with new business or product ideas. Most of the time I quickly identify a product/market fit issue and quickly discard it, but there’s the odd one that I can’t easily dismiss. The trouble is I rarely follow through and actually do anything with the idea — other than to mysteriously allude to it with friends, usually over drinks. …

How to build a recommendation engine without knowing your users. Image: Shutterstock.

How can you make recommendations for a user you know nothing about? This was the challenge posed by a hotel booking site with low conversions from searches into accommodation bookings. Enter DiUS to develop a proof-of-concept using machine learning in a custom recommendation engine to lift the conversion rate and drive more bookings, all without that essential user information that’s traditionally used to power sophisticated recommendations.

Intelligent recommender systems

Recommendation engines can have a major impact on page conversion and purchases on sites where anonymous or unidentified users are searching and browsing a wide range of content, products or services.

High-performance recommendation engines…

It’s an unusual brief to be handed… build a product that:

  • Has a small target user base
  • Shouldn’t be needed in a perfect world
  • Shouldn’t have aspirations for a rapid growth in demand

In this case, the brief was to create a suicide prevention app in partnership with Black Dog Institute.

This was certainly a shift from my experience building fairly business as usual type products prior. The process normally looked like this: undertake user research and gather insights, occasionally you would go additional rounds of research, but often you would just get on with the build. …

By Johny Mattsson

Here at DiUS, we often get brought on board to help productise “IoT” (that’s Internet of Things, if you have somehow managed to escape the acronym) devices, and depending on the domain it’s often a Linux based device. Something we commonly see is that developers who are entering the embedded Linux space from the server or desktop direction are carrying over patterns from there out of habit.

While a server or desktop Linux distribution is well suited for their respective areas, they’re designed around assumptions that don’t hold well in the embedded space. The trade-offs made in…

By Natalie White

You may have heard the somewhat alarming term ‘post-truth era’ in the headlines recently, and along with it the uprising of fake news. So, where did the truth go and what made it disappear? Is social media to blame? And what does this mean for us as Experience Designers?

Let’s start with defining the post-truth era. Predicted by Nietzsche and gaining popularity around the 2016 US presidential election, it can be described as an age where people are more likely to accept an argument based on their emotions and beliefs, rather than one based on facts. …

By Shahin Namin

At DiUS we are seeing increasing interest from businesses in how to drive new value from machine learning (ML), but the technology is not yet broadly adopted across the enterprise market.

So what’s stopping adoption? Sometimes it’s due to a lack of understanding of which ML application is going to solve the problem an organisation has, but increasingly it comes down to difficulties in productionising ML applications — actually getting them to work within existing corporate systems or consumer-facing applications at an accuracy or performance level that is required.

While we hear a lot about ML, it’s…

By Tony Davis

Startupbootcamp (SBC) is a global accelerator program that works with early stage companies through an intense 14 week program of development, learning and engagement. But unlike other accelerators, SBC’s programs are industry-focused, bringing together a network of relevant mentors, partners and investors to provide specific guidance and nuance that comes from domain experience.

DiUS is proud to once again be partnering with Startupbootcamp and working with the founders, partners and SBC team throughout the three-month virtual program. Over the past three years we’ve also been involved in the energy and sports/eventtech programs. We provide training and mentorship…


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