#data 2.0

Data 2.0/Daystrom Android M-150 playing violin 🎻 as we weren't shown this in S3 of Picard (though it's in the deleted scenes)

DATA 2.0 / Miku Hatsune

Me: once I get a micro controller, I’ll have it running by December.

He made it so the pixy cam would track and follow red objects, then part way through the day took it off of his workspace in the second year lab. I was like "what are you doing with that??"

He goes, "Jim (another instructor of mine) is wearing red today. He's in the first year lab with first years. I'm gonna take the sensor in so every time Jim walks past, it follows him. Freak out the first years."

He programmed this sensor to see red for this purpose I'm almost certain.

TL;DR - Drones are getting smarter, and this “smart” drone tech should be the basis for any future drone infrastructure development.

Drones are a key component to my Data 2.0 thesis for their ability to do things that previously weren’t possible at a commercially viable price point, as well as their value-prop that allows them to replace other areas of the imagery and geospatial analysis stack.

Drone funding has exploded in the past year, and we are probably only a year or two away from another Unicorn in the space (most likely Airware) with the potential for many more in the future. But with these fundings have come a bevy of “me too” drone entities targeting the same enterprise use-cases in the same ways (often basic capturing of aerial imagery with a technology-enabled, but somewhat manual analysis product).

The opportunity still exists for these V1 (or “dumb”) drone companies, as no players have won anything close to a majority market share across the applicable verticals, many which represent large markets. 

But this perceived opportunity in the new tech seen today opens the door for an overeager market to overfund, and overestimate the “dumb” drone industry in order to fully develop the market leaders in the first waves of the commercial drone movement.

As a counterpoint, one could argue that by establishing early winners, it opens the door for further innovation and consolidation. However, I believe the inevitable existence of “smart” drone tech companies, both on the manufacturer and service side, could upend these incumbents and cause a wasteland of overfunded or once-promising “frontier tech” companies founded between 2012-2017.

It is for these reasons that as we look towards the future, public and private entities must not build infrastructure that is made for the drone companies of today, at the cost of stunting innovation in the “smart” drone technology of 7-10 years from now.

For the first time in our history, humans are beginning to accept that machines can better handle dynamic, complex tasks - leading to a willingness to put our lives in the hands of machines like self-driving cars.

As drone usage becomes more widespread and advanced for this newly formed tier of UAVs, the conversations around how countries will utilize and regulate drones at scale are only going to increase. Today, drones are primarily manually flown, or pre-programmed to fly GPS coordinates in open space. But this industry must not follow the path that the automotive industry did. Innovation is happening at a much faster rate than ever before possible with cars, and thus, we must think about sunk costs when it comes to building the infrastructure for drones.

With companies like Amazon already working on delivery, we should capitalize on this future adoption (whether it happens in the US or elsewhere) and build out a completely new form of infrastructure with an ideal system in mind: One that supports autonomous drones and the advantages that future technology will afford us including precision flying, machine vision, real-time video analysis, and a connected platform that will enable drones to be smarter and more aware than ever before. Amazon shouldn’t ever need to pilot their drones, and drones shouldn’t have to be afforded a 1-2 meter margin of error.

A well thought-out infrastructure could even forward the Drones as a Service model - evoking a vision very similar to electric cars moving autonomously throughout cities waiting to be called. On-demand drone utilization should become as close to a commodity product as Uber, Lyft, or car-hailing has become in just 6 short years.

As stated above, this movement starts with machine vision and awareness, and the first-movers may already be here. 

Skydio was founded on the basis of developing the “visual cortex” of drones, allowing drones equipped with their technology to “navigate the world intelligently”. PreNav, uses computer vision (via LiDAR) deep neural networks and 3D path planning software to allow a similar maneuverability, initially targeting high-res industrial monitoring, but with use-cases that can expand to multiple industries. Airware could power the enterprise drone fleets of the future and SkySpecs’ technology platform could enable all drones to coexist on a broader platform without accidents.

Smarter drone technology is progressing and has surpassed the MVP stage, so why push off to tomorrow what we can accomplish in the next 5-10 years?