A lot of the projects that I end up involved in are fairly stealth. Here are some of the more public ones.
I founded the first incarnation of this machine vision company as Poikos back in 2011. This original, patented (US8842906) technology enables fast and simple 3D body measurement from only two planes (front and side), using a 2D camera, or 3D sensor.
This data powers accurate and timely personalization services in health, mass customization, and retail.
• Dematerializes body scanning, enabling ingress on any device
• Increases customer retention and discovery
• Generates large amounts of anonymizable biological data, geolocated and stratified.
The technology applies Convolutional Neural Network technologies, as discussed in my video coursebook for O'Reilly Media.
EthicsNet follows the examples of WordNet and ImageNet to create a dataset of ethics for machine intelligence. EthicsNet is founded on the principle that ethics and morality are measurable, definable and computable, across cultures, time, and geography. We believe that the future of a thriving humanity in an artificially intelligent world is predicated on the ability to create moral and ethical machines.
Social media is transforming our global society in powerful ways. The perception of increased social density has created a crucible of conflict where social interactions happen at vastly accelerated pace and scale.
The Cultural Peace Agreement aims to make and collect suggestions on how we can make fair, just, and impartial rules above conflict to preserve good faith and societal cohesion, and to help support a future détente between a multitude of memetic tribes.
An offshoot of the EthicsNet project, Bounder aims to enable a physical safety mechanism for autonomous systems such as drones. A small GSM-based tracking module can be attached to drones, so that they can be tracked in real time via web/app to ensure that they stay out of prohibited areas (or within bounds).
Also includes various pathfinding, maintenance, and mapping modules.
Scry was a prototype machine-driven health project launched during my study at SU that aimed to collect ophthalmological data from non-smart instruments using mobile phone cameras, and then pre-process it using cloud-based Deep Learning / Convolutional Neural Networks, in order to pinpoint dozens of potential major health risks in moments.