The Palantir company created a platform for unstructured data. The first thing required to quantify and manage such complex pools of information is a platform. That's precisely the type of software that Palantir (NYSE: PLTR) has built and continues to develop. A core "data OS," where information is shared and analyzed, is visible to many different organizational levels to make quick and timely decisions. This is a radical departure from how most businesses run today, where things are often siloed or opaque.
Taking unstructured data such as documents, memos, notes, images, videos, etc., and putting it onto an open and shared platform can be thought of as pseudo-quantification, in the same way, that our brains are pseudo-processors for unstructured data. Evolutions in hardware are expanding software's ability to quantify this type of data, matching and exceeding our own capabilities.
Today, computers are mastering images (computer vision), and tomorrow's computers will become ever more sophisticated in their ability to read and write documents and memos. Palantir's software will enable businesses to leverage this technology.
The future of the internet is enterprise and industrial innovation, rather than more abundant consumer-oriented content. Palantir is Facebook for the industrial internet.
PLTR technology will be used in the future for industrial innovation.
Here is how:
Imagine the factory of the future. Autonomous trucks are pulling up from a supplier. The supplier's cloud is transferring information about the shipment to the factory's on-site data center. Using that data, picking robots are unloading pallets and boxes. Further down the line, more robots are scurrying around, sorting, and organizing the never-ending stream of parts and supplies into various locations, additional robots pull these materials into the production line.
Blanketing this facility are sensors. Sensors for heat, for foot traffic, for production, and for quality control. Cameras. Radar. Lidar. GPS. Motion. Pressure. Some sensors are used for local analytics, a robot using its eyes to make sure it doesn't crash into its fellow robots. Some of this data is pooled and organized, sorted for important insights or anomalies, then transferred to the cloud where it can be analyzed, recorded, and studied.
Somewhere in this facility are humans, doing complex work by hand. A small team of factory workers has noticed a problem. Small plastic rivets they are using keep breaking, costing the factory time and materials. At their workstation, the team leader makes a note on a computer. Plastic rivets keep breaking ~1 out of 6 PN#13345.
Elsewhere are more humans managing the factory. Supervisors and mid-level management are using vast amounts of data collected to simulate various scenarios. The data center is hard at work crunching the numbers, done remotely in the cloud.
A mid-level supervisor receives the note from the factory floor, flagged by the system to indicate a problem. This is a different type of data and complex problem that a computer would not be good at sorting out. With the power of the organization's data at their fingertips, the supervisor can immediately look into the issue. The supplier is running the same software, and the two companies collaboratively share their data.
The computer has recognized the part number in the note, and with a single click, the mid-level supervisor can see the supplier's data regarding the plastic rivets. He turns to the specifications and notes it. Because the tools used by the team on the floor are connected to the network, he can also see that the pressure they are using may be too high for the brittle plastic. The team is alerted in real-time that they should reduce the pressure that they are applying. A note is made accessible to other assembly points that might have similar issues with the same rivets. The problem is resolved quickly and efficiently. These small advances in warehouse efficiency add up to seamless and scalable operation thanks to the software Palantir has developed.
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