Our Auckland office enjoyed an evening of social and competitive cooking at Sachie’s Kitchen in Parnell organised by Shane Ingley and Andy Bartle, for the company’s social club. The group of staff and partners were split into four teams, each assigned a different cuisine, and challenged to cook a range of dishes within a 40 minute timeframe. The competitive format meant that the teams were judged on knowledge of cuisine, presentation, timing, taste, and their oral presentation of the dishes. New graduate Jack Chipperfield won valuable points for his team – the Red Dragons, who were responsible for a Korean Bibimbap with his colourful recounting of how the dish formed an integral part in peace talks between North and South Korea, outscoring Courtney Groundwater’s story of her green curry and Son-in-Law eggs from Thailand made by Team Orangutans.
In September 2020, we conducted a routine staff survey measuring how Abley team members commute to the Christchurch and Auckland offices. As a company with a professional focus on sustainable transportation, monitoring our own commuting CO2 emissions is important to us, to help inspire positive change.
As human beings, we are constantly using our past experiences to learn and do things that we haven’t seen before. When you train a model from scratch, it’s like learning the road rules without ever having been in a vehicle. It is achievable but takes much longer.
Merry Christmas to you and your families, we hope you have safe and happy holidays ahead!
The focus of our Computer Vision blog series to date has been focused on understanding the limitations, benefits, and complexity of applied computer vision. Machine learning is a broader field that encompasses numerous methods, including computer vision and more organisations are beginning to see the value in its application to their day-to-day operations.
If you’ve been following our "Computer Vision" blog series, you will have gained an appreciation for the complexity and effort involved in preparing data before it can be modelled. Previously we discussed data sampling, this time we will cover another important step in the pipeline called data augmentation.
On 11th November (during Road Safety week), Abley held an industry breakfast event in conjunction with the Australasian College of Road Safety. The event included presentations from Bryan Sherritt (Auckland Transport), Hamish Mackie (Mackie Research & Consulting) and Jeanette Ward (Abley) on topics relating to creating safe urban environments for people.
Have a read of our latest Street Smart newsletter, featuring 3D visualisation, walking research, HERE mapping tools, a Rally app, meet our new team members and more!
In our previous computer vision blog, we talked about how big data can be managed in the context of computer vision. As part of that discussion, we mentioned that selecting a smaller sample from a much later dataset can be a practical strategy for handling big data for computer vision applications. There are many ways to define a sample. These sampling strategies are not unique to computer vision but are rooted in statistics. This blog will look at more traditional methods based around random sampling, as well as a machine learning option and why these samples are important.
Think about this for a second: globally, men die six years earlier than women. To make it worse, the reasons are largely preventable. One in eight men across the world will be diagnosed with prostate cancer in their lifetime. Testicular cancer is the most common cancer among young men. Three quarters of suicides globally are men. Pretty shocking, right?
