There are over 1500 satellites in orbit around our little ball of dust and fish soup.
Most of them of them are in low earth orbit (LEO) which is close enough to order a pizza, but too far away to get it delivered. Between 99 and 1200 miles above us, and travelling at 17,000 miles per hour, which might seem fast, but if the Millennium Falcon’s speedometer pegged at the Speed of Light, it would idle at around 39 million miles per hour.
The satellites that aren’t in LEO are mostly in geostationary orbit. That means that they are traveling at a speed precisely equal to the Earth’s rotation so they are, in effect, hovering over one spot on Earth about 22,000 miles away.
There are also satellites in a Polar Orbit, who circle the Earth near the poles, and these are also considered LEO satellites.
So? What does that have to do with AI?
Jean, Invacio’s A.I., monitors, collects, and scrapes data from all the possible places that data comes from, including satellites in space. She pulls “tiles” (humanity taking selfies with satellites) from NASA constantly, these tiles are converted to usable data on the fly for some 300 million locations worldwide, the tiles often overlapping.
Well, all that data those satellites are gathering gets sent to a storage facility that is the equivalent of the Tower at the Citadel where Sam Tarly was copying books. A dusty old cyber-storage facility full of terabytes upon terabytes of data, most of which will never see the light of day because they’re so generic, repetitive, esoteric, and useless in and of themselves…
But Jean scrubs this immense amount of data, the minute and boring details that unfold are suddenly part of a much bigger picture. And while most of those details are truly unremarkable at first glance, as Jean starts to put the puzzle together, aided by the until recently missing pieces of unparalleled computing power and speed of learn capabilities of Artificial Intelligence, some startling facts are revealed.
Tracking shipping traffic is fairly easy. But what if you wanted to track shipping traffic and weather patterns, combined with new oil field explorations and average annual lobster harvest?
Now, what if it turns out that new oilfield explorations are in fact, a key indicator of what next year’s lobster harvest will be, and you can check 50 years of shipping, oil exploration and lobster data in a millisecond, determining that next year is going to be a very meager lobster harvest? Do you think maybe you could pull a Mortimer and Randolph and try to corner the market?
What if I told you that Jean can tell you how many iPhone 8s are going to be sold on the first day, based on satellite pictures of the amount of people waiting in line in every Apple outlet on the planet, compared with the size of the lines over the last 10 years?
Did a lightbulb just go on for you?
Invacio is able to access this data for two reasons:
1) We reached out and asked nicely on Jean’s behalf. (It’s important to have good manners).
2) We spent a shit ton of time, effort and money (years, and millions) building a system that could actually drink from the cyber-firehose that is Satellite data, and make sense of it.
Without those two things, you might as well just look at the sky and wish upon a star.
And if you wished that the scenario I described above is real and true… you’re a winner today!
Aquila, Invacio’s Fintech division, has begun to master the art of reading NASA satellite data, not just shipping zones, but including:
#Agriculture Zones #Mineral Zones #Refinery Zones #Gas Zones #Oil Zones #Retail Zones and perhaps most significantly #Chocolate zones and comparing them with other real-world data before they become major news events and can affect markets.
Aquila knows what the effects of Hurricane Harvey will be on 10 key market indicators that nobody else is thinking of, oil, agriculture, pork bellies and beef, manufacturing and mining.
That stuff is child’s play.
What about 2nd tier markets that are hit? What markets thrived after the last major hurricane? Just hurricanes or other major disasters? Jean knows.
Being able to pull data from NASA satellites, plus a few hundred more orbiting the globe, and from additional sources including The European Space Agency and Planets.com, gives Invacio, and more importantly, Aquila, a key advantage in the world of information, and how that information can and most likely will affect the markets that investors frequently trade in.
Coupled with weather (zone-wise), conflict news/war/political (zone-wise), and disaster (zone-wise) tracking, Jean analyses milestones before the information can be processed and shown on the news, or the general public understands the effect.
And satellite data is just one of close to two billion discreet data sets that can be scraped and analyzed to help make decisions of all sorts, but the impact of those analysis on finance and investing will inevitably transform the market, and Invacio and Aquila are leading the way.
Oh, and, there is no such thing as a #Chocolate zone.
 Speed of Learn is the speed at which an AI can learn a new thing and apply it to the problem it is solving at the time. Simultaneously looking through its data history and applying the new knowledge to any and all previous assumptions to adjust its overall knowledge base. Growing smarter each time.
 One of many Invacio divisions, all of which leverage Jean to produce value for shareholders and our customers.