Time is ticking for effective GPT data management

Yes, “knowledge is power”. These words of Sir Francis Bacon take on a different meaning now, four centuries after he said them. Today, we are powered by generative AI, a technology based on large-scale language models (such as GPT) that can continuously generate information based on vast amounts of data.

From software code to illustrations to movie scripts to synthetic data, the ability to automatically generate content from data makes it easier for anyone, not just data scientists and engineers, to manipulate, analyze, and build data. It’s the next evolutionary stage.

Data is the new oil for organizations, but as with “black gold,” the collection process itself does not provide real value. Only the ability to accurately leverage data with AI and ML and a secure infrastructure can actually turn data into valuable information and economic gain. A decade ago, data management wasn’t a huge challenge, and a small team was usually enough to handle limited amounts of information.

Today, the landscape is more complex, with roles within a given organization becoming more broad and involved in enterprise data operations. The move to cloud environments, the move to microservices and the use of APIs has increased the amount of data and various organizational applications. At the same time, the accelerated development of AI technology has resulted in organizations implementing various application layers on top of the data to analyze the information and generate valuable insights.

What we’re seeing is that most people (and the media) are primarily focused on: use It focuses on holistic management of data rather than dealing with holistic management of data. For example, there is more attention and investment in startups looking to build on top of GPT, and less attention in startups building data management and infrastructure solutions.

However, AI systems, information security processes, and automated information flows require proper data management. Otherwise, you could end up in a “bottleneck” or worse.

However, the IDF development force is adapting to this new reality and will follow a similar trajectory as we have witnessed with Israeli military cybersecurity. Until a decade or so ago, there was no “data unit” in IDF’s development department at all (or it existed only for ad hoc activities). Today, more and more IDF coding development departments no longer focus solely on cyber and telecom, but also on active data management. This allows us to shine a light on the next generation of founders entering the high-tech sector in Israel after military service.