Nested Technologies is an artificial intelligence firm that applies machine learning and neural network algorithms in fields ranging from architecture, web scraping, to finance.
Nested Technologies started because a few bright-eyed team members wanted to write scripts to automate as many mundane office tasks as possible.
The resulting culmination of these scripts turned into machine learning web apps that not only proved useful to the team members who created them, but to their family, friends, and more.
That’s the true story.
What do you do?
We look at resolving old problems with artificial intelligence as the missing piece to the jigsaw puzzle. Because with enough training, we can guess with good confidence the shape of that final piece.
What's in the future?
We are technologists at heart. It doesn’t matter the field of application, whether it’s from construction or finance. Because data is industry neutral. All we care is that our work can benefit those in fields that we have not even heard of today.
“I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.”
― Alan Turing, English computer scientist, and mathematician
Whether we discuss the philosophy of artificial intelligence (AI), or an AI entity's philosophy, we may or may not come up with the same answers. So while we ponder upon these questions, here are photos of two men from very different times thinking about the same thing.
Our works span across a wide variety of fields ranging from construction to finance. Here are some recent projects that we have been working hard on, and we thought we could share them with you.
Autoscrape scrapes for data via methods such as SERP and GMaps, to obtain company names, addresses, and emails. The program then verifies the validity using DNS and SMTP checks to ensure authenticity.
Quantity AI deploys machine learning to read plan views, identify hatches, and estimate the area using deep learning and semantic segregation, by training the datasets with a thousand images of rooms with hatch patterns.
Three Sigma researches fields in machine learning to apply algorithms to astronomical sets of data for instruments in the financial market. The quantitative methods intend to generate absolute returns.