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One of the most persistent problems within many fields is the lack of communication. We have access to vast amounts of data, but all that information is siloed. You have so many different systems and hundreds of ways to access various pieces of data, but nothing... Read more
Data science is about a half-century old in the way we think of it now, but with the advent of AI, we’re reaching a precipice of how we want to model our AI initiatives. Moving forward with not just effective but ethical AI, we need a... Read more
50 years ago, the concept of privacy meant disappearing. You built a wall around your private data, and it was pretty easy to keep that wall secure. Aside from governmental intrusion, you didn’t have to worry much about constant feeds of data streaming from your daily... Read more
A lot of discussion over AI is hyperbolic comparisons to the Terminator. While this isn’t helpful to the discussion, addressing ethics concerns with bigger, faster AI on the horizon is a necessary part of development. Instead of willful ethics violations, we may have more trouble with... Read more
We’ve focused a lot on what AI can do for language processing, but one aspect of AI that’s gaining speed is visual. So much of our data is visual, so using these AI models to parse and work with visual media is a crucial aspect of... Read more
Generative Adversarial Networks are transforming what we’re able to do with neural networks, and it’s unfortunate that almost all the press goes to those wildly accurate facial constructions like that of This Person Does Not Exist. GANs have some incredible potential so let’s take a look... Read more
“Data can either be useful or perfectly anonymous but never both.” – Paul Ohm Privacy and data collection go together like peanut butter and jelly, but in the world of big data, it’s becoming increasingly difficult to work with anonymous data without crossing a privacy line.... Read more
Ever since the term “data scientist” came onto the tech scene, there’s been a cross-generational debate raging, attempting to define and distinguish newly branded data scientists and traditional statisticians. I personally adopted the data scientist title around 2012, and I recall a rather pithy definition float... Read more
Building a website is meant to help your business grow. If you have to set aside a team of engineers just to code and deploy the website, spending precious time and human resources just to build and maintain the website, that seems to defy the purpose.... Read more
With the current generation of data scientists working tirelessly to satisfy the accelerating demand for data-driven insights on behalf of industries pretty much across the board, it’s natural to take a step back and ask what the “data scientist 2.0” might look like in the next... Read more