Veterans Day, WW I, and Technology

Posted by David Simon on November 12, 2018 at 2:57 PM

This Veterans Day I wanted to specifically look at some technology and innovation that happened during WW I and draw several parallels since it's been 100 years since the signing of the treaty that ended that war.

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Topics: NNCompass Government, Veterans Day, NNCompass Enterprise, Data Preparation, Technology

Podcast: All Things Data with Oscar Wood

Posted by Steven Aberle on October 29, 2018 at 3:57 PM

By popular demand I’m sitting down with Oscar Wood, CEO of NNData, to talk about many different things, including hidden data workforces, democratizing AI across a business, how the world of ETL is changing… we also get into leadership philosophy, when it's ok to be wrong, and second chances. Buckle up. This is a good one!

PODCAST HIGHLIGHTS:

Oscar walks me through his thought process on ideating NNCompass, where he saw the gaps, and who specifically we’re trying to enable

We've talked before about this assumption that there’s a “hidden data workforce”, a group of people in any given organization, whether they’re business analysts, marketing professionals, low-level all the way to c-suite… technology for this group of people is quickly being democratized… so we talk here about the hidden data workforce, and what they need to validate their mental models.

I ask Oscar, is the end goal to democratize AI and those insights across an organization…? “Machine Learning for the Masses”? Or maybe automating some of the difficult data management workflow tasks associated with assembling data for AI and ML?

We dive deeper into what it takes to assemble data for AI and ML, who’s job is that, what needs to happen, how do we use software to make it a team effort? Project controllers, business analysts, data scientists, do all these people need to work together?

There’s been some complacency in the world of data management and ETL in the last few years, everything really being tied to a database offering - - almost always very expensive… I ask him how NNData is trying to disrupt that model by looking at the “data” landscape from a different angle?

 

 

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Topics: Machine Learning, Data Management, NNCompass

Podcast: Text AI with Jerry Gay

Posted by Steven Aberle on October 15, 2018 at 10:13 AM

Cool episode this week where Jerry Gay, NNData CTO, and I talk about about machine learning for unstructured data management, natural language processing (NLP), Gate’s Annie, Stanford NLP, why it’s difficult for companies to incorporate unstructured data into their pipeline or data management workflows, and why industry has a tough time responding to this gap.

PODCAST HIGHLIGHTS:

Traditional, unsupervised natural language processing has been a discipline for the last 15 years, we talk about what it can do for you, and how much has it improved….

Jerry and I built a system together a few years ago called Big Data Ecosystem while we worked together at a company called Data Tactics... we included a version of Gate's Annie and Stanford NLP into the ecosystem, with mixed results, which we discuss here…

NNCompass takes a different approach to unstructured data management, inserting the human into the enrichment and extraction process, I talk to him about why we did that, and why it’s unique…

Today was a good day to have this conversation about unstructured data, since both Jerry and I had met with a company called ExpertSystem USA for most of the morning, having a deep technical dive into the textual AI software they engineered called Cogito…. 

With the release of Google’s Auto ML and Amazon Rekognition, I ask Jerry if we’re approaching a sea change in the way businesses view unstructured data, or if these tools are really focused on image AI problem sets…

 

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Topics: Machine Learning, TextAI, Unstructured Data

Podcast: Applied AI with Joe Clark

Posted by Steven Aberle on October 4, 2018 at 4:28 PM

Talking to Joe Clark on the podcast, who is the principle scientist and owner of HSB Intel, a firm focusing on applied AI and machine learning, a variety of customers from NASA to the Defense Department… we talk about a range of AI-related subjects, but first I ask him to tell us a little bit about himself and how got involved in applied AI.

PODCAST HIGHLIGHTS:

Joe recently authored a paper on self-assembling neural networks that is getting national attention, he dives further into that topic.

We also spent some time together in Chicago a couple of weeks ago, where we talked about the basics of AI, what is it, what’s the different between AI, machine learning, deep learning, neural networks… I wanted to include that conversation in this podcast for everyone here to get a baseline of exactly how the field of AI is structured.

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PureAI article covers low-code AI/ML & NNCompass

Posted by Steven Aberle on September 27, 2018 at 9:01 AM

Author John Waters talks about how NNData and NNCompass can bridge the gap between a shortage of data scientists and organizations that are looking to accelerate their journey towards being an AI-driven enterprise.

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Topics: Machine Learning, NNCompass

University of Virginia Data Science Institute

Posted by Steven Aberle on August 28, 2018 at 12:12 AM

Join the Data Science Institute for the inaugural fall 2018 Distinguished Lecture Series talk with Oscar Wood, Founder & CEO of NNData.

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NNData Launches Online SaaS "Smart Data" Software

Posted by Steven Aberle on August 21, 2018 at 9:32 AM

FAIRFAX, Va., Aug. 21, 2018 /PRNewswire/ -- NNData today announced the launch of its online SaaS "Smart Data" software, as part of its flagship product NNCompass. It delivers easy to use ways to manage data along with use case-focused machine learning algorithms for anyone to use without having any training as a data scientist or programming background. 

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Podcast #1 is Online!

Posted by Steven Aberle on August 16, 2018 at 6:08 PM

Welcome to our Podcast, where everyone here at NNData gets to sound off on the latest things happening in the AI and machine learning space, talk about new ways to manage data. And or, talk about all the geeky things we love to hate... or is it hate to love.

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Topics: Machine Learning, Data Management, Unified Data Format, AI

How do you define data?

Posted by Lori Alexander on August 8, 2018 at 10:07 AM

Here at NNData we spend a lot of time talking about data but when we talk to people outside our bubble and ask how they manage their data many people kind of look around and respond with “well, I don’t really have any data” or “we don’t really manage data”.  We have come to understand that not everyone thinks of data in the same way we do.  In fact, I would venture to say that 80% of the population never gives the word “data” a passing thought.  However, I believe that almost everyone deals with data in one form or another, it’s just called a different name.  What is data?  It’s spreadsheets, logs, documents, briefings, images, completed forms, reports, emails, articles, publications, the list goes on and on and we call all of them “data”. 

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Topics: Data Preparation

NNDATA Named as a Finalist for the Moxie Awards

Posted by David Simon on July 29, 2018 at 8:29 PM

Last week the company found out that it had been nominated and selected for the 2018 Moxie Awards. "Simplicity drives Productivity" was the message being discussed around the table this past week at NNData Headquarters as the Washington, DC committee interviewed the leadership about our NNCompass software.

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Topics: Machine Learning, NNCompass, Awards

Everyone Should Be Able to Create Smart Data.

You can do amazing things with data now. This is where everyone involved in bringing NNCompass to life talks about how your business can start using things like machine learning to create "Smart Data".

If any of this sound familiar to you, you're in the right spot...

  • I really want to take advantage of things like machine learning, and see what it can do for my business, but I don’t know where to start

  • I have a data problem. Too much, too different, coming in too quickly. I don’t have 4M USD to hire teams of people to overcome my data problems.

  • I wish I could ingest and get a handle on all of my data, not just beautifully structured CSV and XLS files, but all my emails, MS Word docs, Adobe PDFs.

  • I don’t have the resources or time to first hire data engineers, then data scientists just so I can start using machine learning algorithms to answer some of my most difficult business problem sets.

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