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17 Nov 2023

Driving forces behind the evolving AI landscape and strategies for success

Zachary Simon, Senior Autonomy/Artificial Intelligence Senior AI Research Engineer, Lockheed Martin
Driving forces behind the evolving AI landscape and strategies for success
Unveiling the insights behind shared research and the impact and effect on AI if there is a downward trend toward openness and shared data.

As the AI landscape continues to evolve, we take a moment to speak with Zachary Simon, Senior Autonomy/Artificial Intelligence Senior AI Research Engineer, Lockheed Martin, ahead of his participation at The AI Summit New York 2023, to get his insights on where he thinks AI is headed, future developments we can expect to see and some drivers behind this.

Please share with us your career journey to date, and how you ended up as a Research Engineer with a focus on AI:

I’m a Senior Autonomy/Artificial Intelligence Research Engineer at Lockheed Martin on the Cognitive Mission Manager program where I predict wildfires with AI. Now based out of Manhattan, I previously worked in Silicon Valley within LM. Before that, I was in a slightly different realm.

Originally fascinated by theoretical physics, I pursued physics during undergrad only to switch majors to graduate with a B.A. in political science at UNC-Chapel Hill. However, senior year, I had a renewed interest in math and physics, which led to an M.S. in math at CUNY. Soon after graduating, I dove into AI allowing me to explore a new domain.

Combining my interests in math, statistics, physics, and programming, the opportunity to move across the country to Silicon Valley was life changing. AI is ultimately about us and extending our intelligence through computers, which requires fusing many disciplines we’ve developed over millennia. I’ve been fortunate enough to solve interesting problems in AI and software engineering while working with exceptional minds along the way.

What do you think have been the main drivers to get the AI landscape to where it is now?

There have been several factors at play. The largest has likely been the opportunity to use AI across the private sector in unforeseen areas, which was previously confined to a few companies building the technology. Moreover, once AI left academia, it was able to grow in ways that were unanticipated before the World Wide Web and spread of the personal computer in the commercial market.

What are some of the key success factors or things to be aware of as a business when implementing monetization strategies in AI?

A key success factor to be aware of is how the models are performing. Often the models are dependent on the quality of the data. Ultimately, we aim to solve problems for our customers, and using AI has been a helpful tool in that pursuit.

Why do you think that shared research is starting to close off, and what impact do you think this will have on organizations? What do you think the AI landscape will look like in 12 months?

It depends on the domain where research is closed off. In the private sector, it probably always will be to a certain extent while in academia openly publishing papers is vital to the field’s growth. In 12 months, LLMs will likely continue to increase in popularity as they become more accessible across the Internet and within apps. I’m excited to see how we use LLMs to help our lives. I expect more advances in language to build off current work to save us time—especially in web search and information retrieval. Currently, the process is tedious communicating an abstract thought to a keyboard, to a screen, and finally to a web page. Since we’re used to that process, we don’t realize how slow it is compared to the fraction of a second we have a thought to search something. There are a lot of improvements awaiting to be made in information retrieval.

Do you have any key insights you could share about your AI journey and experience to date?

Always return to the big questions that got you interested in the subject from time to time. Somehow unrelated subjects continue to find their value in AI. I expect the more we learn about the capabilities of the computing and information paradigms, the more exciting results we’ll begin to see in AI.

Make sure you join Zachary this December 6-7 at the Javits Center, New York, where he will be joining the panel discussion on, ‘Are We Closing the Door on Openness & Sharing? Evaluating the possible changes in the AI landscape,’ and ‘A Deep Exploration into the Possibilities of AI in the Metaverse.'

Secure your place now, and we look forward to seeing you there!

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