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We sat down with Mary Grygleski, Callibrity’s new AI Practice Lead, for a Q+A session to learn more about her journey into technology, her goals for Callibrity's AI practice, and her vision for AI in the future. Dive into our conversation with Mary below to understand her expertise and aspirations.

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We're thrilled you have joined Callibrity. What drew you to our company?

Mark Wehby and James Carman really stood out due to their leadership styles and authenticity. I had such a great conversation with them. What impressed me the most was that they each came from a development background, and for them to advance to the business level and build up a very successful consulting practice that's unlike many typical consulting shops, I found Callibrity to be appealing. This is a company led by leaders with a good blend of hands-on experience who understand and appreciate software as a craft and not merely as a money-making tool, while also having great business acumen and integrity in the consulting space.

How did you get into technology?

When I first came to the U.S. for college, the student self-service registration system had an old-style mainframe terminal. As I have always been good at mathematics, I found the system fascinating and really wanted to know how it worked. I then had an opportunity to enroll in CS-100 (Intro to Computer Science) and started to learn programming in Pascal. I came to realize that I really enjoyed getting my mind into a "deep thinking" mode to solve problems. I then switched my major from physical education and exercise physiology to mathematics & computer science, and the rest is history.
 

What are your goals for Callibrity's AI practice?

I would like to see Callibrity become not just a thought leader, but also an implementation leader in the AI / GenAI / ML consulting space, helping customers make sound decisions on choosing the right tools and approaches for the right job, and assisting them to build sustainable and ethical AI application systems.
 

Everyone is talking about generative AI. How do you see it in practice today and in the near future?

I think today's generative AI is far from being ready for prime time. While many GPT-based apps have impressed us since ChatGPT 3.5's debut in November of 2022, we practitioners know that many aspects of this technology still require significant work before it can be safely and widely used in production. This includes increasing speed and dimensions, fine-tuning, reducing the cost of training LLMs, operationalizing multiple processing steps, error checking, and safeguarding proper usage in various scenarios.

In a crude way, I liken the current state of ChatGPT to the early history of aviation. While the Wright Brothers did not widely publicize their first documented flight in December 1903, the event was undoubtedly a major milestone in human history. However, the first commercial airplane flight did not happen until 1914. Similarly, although there is a multitude of research and implementation activities happening in the generative AI space, it will take time before it becomes truly usable.

In the meantime, we can expect various "spikes" of innovation that will continue to wow us. For example, OpenAI released Sora, a text-to-video model, in February 2024, capable of generating very realistic video scenes. Just last month (May 2024), GPT-4o, a multi-modal real-time model, debuted at OpenAI. So, I believe we will continue to see impressive models and LLMs for a while before the "birth" of something more concrete that can handle enterprise system concerns.

What is the best advice you've received?

I tend to overthink and strive to ensure that what I am doing or saying is correct. I've often been told, "Don't think too much, just do it." I believe there is some validity to this advice, and I can accomplish tasks more quickly that way. However, it is crucial to strike a balance. While it's important to avoid saying or doing something wrong, I must also be careful not to overthink.

What do you like to do outside of work?

These days, I have been very into history, and enjoy watching documentaries and movies about the world wars, and how leaderships have gone awry. I also like reading about the stories of saints, and I've found them to be very inspirational. Additionally, I like listening to NPR while doing other activities such as cooking.

How would you describe your leadership style?

I believe I have a blend of servant leadership and other relevant styles. Since one style may not fit all situations and team members have varying experience levels for different projects, I may step in to help and coach someone who is less experienced. In general, I believe in maintaining a lot of communication with people to prevent misunderstandings.

Tell us about a mistake you made professionally and how it has impacted you. What did you learn from that experience?

Early in my career, I did not want to talk much and was a loner in a sense. It was partly the result of impostor syndrome (which I was not aware of when I was less experienced). Looking back, I wish I had done things differently and was less concerned about the possibility of making mistakes or feeling too self-conscious, because I probably missed a lot of good opportunities by not making it known to my managers that I was up for more challenging work.
 

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To learn more about how Callibrity can help your organization, email us at contactus@callibrity.com to schedule a time to connect.

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Callibrity is a software consultancy specializing in software engineering, digital transformation, cloud strategy, and data-driven insights. Our national reach serves clients on their digital journey to solve complex problems and create innovative solutions for ever-changing business models. Our technology experience covers a diverse set of industries with a focus on middle-market and enterprise companies.