Data Crunch

Working with structured and semistructured data can be hard, but it's currently much easier than working with unstructured data, like images, video, audio, and text. We talk with Davit Buniatyan, CEO of Activeloop, who chats with us about how he works to make unstructured data for machine learning easier and faster to work with.

What's it like to build an AI product in an industry that still uses outdated project management technology and has no clear conceptual model? After receiving his PhD at Stanford, René Morkos speaks to this very situation. He describes his journey building an AI product in the construction industry.

After graduating from the University of Pennsylvania with a master’s degree in artificial intelligence/robotics, Edward Cui  was one of the first Uber self-driving car engineers. He’s had a lot of experience working with unstructured data and shares how we can increase the efficiency of modeling unstructured data by an order of magnitude.

What is the secret culprit behind overworked teachers and administrators in much of the educational system? We're joined by one of Data Crunch's finest, James Thomas, who tells from both a technological and personal standpoint the real difficulties faced by our teachers and students, and how the right approach to data can solve many of their problems.

If you haven't heard, GPT-3 is a machine learning model that can write text. Text that looks like a human wrote it—almost out of thin air. The real opportunity is in the ease of use. GPT-3 doesn't replace your writers. It augments them, making writing faster and more accessible without compromising your results. The last thing you want to do is compromise the quality of your content because copy is an exponential business multiplier. The more you can apply it, the more business you'll get. Despite advances in technology, one thing that hasn't changed is that people still talk about products and services—and what they say matters.