Emerging Tech

This week I take a look at the broad range of emerging technologies and attempt to reflect on how I might be able to leverage them as part of my working practise.

Working my way through the content this week, I couldn’t help but feel overwhelmed by the amount of emerging technologies there are and the technical ability that must surely accompany them. I was excited by the prospect of real value that these technologies could bring to an application and didn’t lack the imagination as to how they could be used in my current projects.

Over the duration of the week I touched on a variety of emerging technologies sourced from the course material and a collection of social media channels and chose to study in more depth Artificial Intelligence to really understand what might be needed to implement such a technology.

Artificial Intelligence

With machine learning and neural networks we are able to calculate variables that aren’t necessarily able to be supplied by a simple formula. Models are trained by learning from real-world data, inspiringly demonstrated at the Tesla Autonomy Day. I can comprehend the usefulness of this technology and already can imagine use cases for it in my current projects. For example it would be really interesting to recognise actors on a stage from analysing a video feed. Identification of the actors would only be the start. If you could then ascertain the position of them in a 3D space you could automate moving lights to follow them as they move around the space. You could also use machine learning for speech recognition and provide captioning for deaf, deafened or hard of hearing. Allowing captioning of works of improvisation and unscripted events.

One aspect of machine learning that worries me and requires further research is the aspect of training a model. My understanding at the moment is that there are quite a few models being used currently and are readily available for use. I am daunted though by the amount of knowledge that might be needed to train a model myself to something custom within my applications. So that I might be able to implement machine learning in my current or future projects I would like to learn the basics of this procedure and as such have devised a SMART goal as directed learning.


  • Specific - Build an iOS application that recognises a person from the camera feed and learn how the model might be improved.
  • Measurable - Have a working application and understand the basics of training a model, present the application and procedures to improve the model in a journal post.
  • Attainable - Use Apples Create ML Documentation and online tutorials for guidance.
  • Relevant - Machine Learning can allow an application to learn and improve from previous experiences. It’s areas of use are varied and in all instances can be applied to my current projects increasing the value of my current products for customers.
  • Time-Based - By the end of the next study block.


  1. Tesla Autonomy Day
  2. CoreML Models