Designing Streamplate

Written by bryanjordan | Published 2018/12/02
Tech Story Tags: machine-learning | apps | design | programming | software

TLDRvia the TL;DR App

Adding. Changing. Hacking flavours.

After 3 years of developing, I’ve begun publicly marketing Streamplate.

Over time it’s shifted in design, scope and intent, and now stands as an operating-like-system for consumers and merchants alike to manage their eating and drinking needs.

At its core, Streamplate offers a personalised assortment of merchants with a sorted listing of menu-items to cater for each user’s needs. While the first iteration of the Alpha app has been completed, there’s still much to be done.

Presently, each computation of the merchant listings takes into account approximately a few thousand-variables.

What I’ve realised over the past few months is that while having such a high-dimensional space isn’t anything unique, the frequency of these calculations is. Eating and drinking isn’t based on “universal truths” which sets it apart from the paradigms that guide Google’s search engine or Spotifys’ playlists curations. What someone wants to order is a function of their perspective in that moment in time.

When we break down what a “perspective” is in factor-analysis, a high-level structure emerges:

  1. Perception => State of values,
  2. Consciousness => Stream of perceptions,
  3. Levels of consciousness => Attentiveness to rates of changing intensities of consciousness.

A key-insight here is how underlying any listing is a measurement of “values”, hence the need for a broad-spectrum of values and hence an increasingly-growing dimensional-space. What this means is that Streamplate needs to consistently be measuring the pulse of a user’s perception so when they do call for a listing, we can be sure to accurately match their needs.

Think of how varying your tastes can be, particularly under duresses like unforgiving summer heat or compelling social influence.

Reaching this understanding required a progressive set of design iterations, each time further investigating the guiding principles affecting our users’ decisions. As I continue working on the back-end code to implement these understandings, I’d like to briefly share some moments in the design process.

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Published by HackerNoon on 2018/12/02