The Future Is Now: Cindy Orozco Bohorquez Of Cerebras Systems On How Their Technological Innovation Will Shake Up The Tech Scene

An Interview With Fotis Georgiadis

Fotis Georgiadis
Authority Magazine
Published in
7 min readAug 23, 2022


In the professional side, it’s very easy to underestimate the power of communication. In my field, when you interact with executives, customers, users…you need to be able to translate and present your ideas and the key points to any audience. It’s very valuable for people — especially those of us in the technical field or mathematics — to understand and execute the power of communication.

As a part of our series about cutting-edge technological breakthroughs, I had the pleasure of interviewing Cindy Orozco Bohorquez, Applied Mathematician and Data Scientist for Cerebras Systems.

Cindy Orozco Bohorquez is an applied mathematician and a machine learning solutions engineer for Cerebras Systems. Originally from Colombia, Cindy has a passion for applied math, and did a master’s in applied mathematics from King Abdullah University of Science and Technology (KAUST), in Saudi Arabia, and a PhD in Computational and Mathematical Engineering from ICME at Stanford.

Thank you so much for doing this with us! Before we dive in, our readers would love to learn a bit about you. Can you tell us a story about what brought you to this specific career path?

I started in college as a civil engineering major. My father was an engineer, and it was the only thing I was exposed to at that time in my life. But then I started taking math courses, and I had no idea what I could potentially do with mathematics. I went ahead, and it was just for fun — I looked at civil engineering as something I could build a career out of, and math as a hobby.

I realized there was much more I could do. I started to work in simulations with civil engineering problems using a mathematical background — and that’s how I ended up working in applied mathematics. After my undergrad I went to grad school and realized that applied mathematics is everywhere, and that it’s fundamental for every type of research! During my PhD I discovered deep learning, and the significance hardware has in solving any type of applied mathematics. After my PhD, I wanted to get closer to what people are doing with these things in real life, and how we’re all benefiting from it today.

Can you share the most interesting story that happened to you since you began your career?

It’s very hard to pinpoint just one. It’s more than a story — it’s the transition I’ve seen in the field. When I started, people in Colombia, in the U.S., everywhere, were not aware of what applied mathematics could do. Now 10, 15 years later — everyone is jumping into AI, data science, machine learning — all the buzzwords. It’s very interesting to see the transition after all these years. I was in the right place at the right time thanks to my curiosity. Companies have become more excited about the data, what they can do with it and how they can fully utilize it. In five more years, we’ll be doing even more than we can know.

Can you tell us about the cutting-edge technological breakthroughs that you are working on? How do you think that will help people?

Right now, everyone is interested in deep learning, but there are a lot of different ways you can use it. The most interesting models you can use today are only happening in a small set of places, and by companies that have access to incredible resources in hardware and people.

At Cerebras Systems, we’re creating a new type of hardware: the largest computer chip designed for AI. That means that once we have a piece of hardware that facilitates the parallelization of many of these new types of algorithms, the barrier to access is reduced. We’re providing access to these algorithms for people who’ve not been able to access or deploy large language models (LLMs).

Looking at this globally, we need to democratize the type of data that is being used for these models. If it’s being developed in a very small subset, the interest and impact will also be for only a small subset of people. The more we increase access to these models and give more tools to the teams working on them, the more applications we will see for deep learning. That will allow us to generalize the type of applications we can see and get closer to how it impacts everyone in the world.

How do you think this might change the world?

It’s very hard to predict. With our hardware, if you’re able to train more models and deploy them at a faster pace, you’re able to explore more sectors and apply it to a larger variety of problems. Right now, it takes a lot of resources for a company to train these models, and it’s extremely hard to go back and change it or look at it from another perspective, because it costs a lot in time and money. If you have the right tools and you can get your results faster, you are able to spend more time thinking about the applications of your model — drug discovery, clean energy, etc. — vs. how you’re going to optimize the architecture of the models themselves.

Keeping “Black Mirror” in mind, can you see any potential drawbacks of this technology that people should think more deeply about?

When people think about AI, they think about “the fall of the machine” — that the machine will be the one to make the mistakes. But every time we make a decision about what we’re going to train or what we’ll do with the data, that is our own human bias. It’s not about the hardware, or the models, but how we as humans use them and the decisions we make because of them.

What do you need to lead this technology to widespread adoption?

We need to put these models in the hands of researchers — giving them new possibilities and opportunities. When you provide an extra piece of hardware and reduce the barrier to access, it causes a reset in how to think about assigning deep learning models. We must enable people to reset their assumptions, and what is possible with deep learning given Cerebras’ new hardware.

None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story about that?

My family, my parents, my brother, my husband, my son — of course they’re the ones always there waiting for me. But on the professional side, I’ve been fortunate to have mentors along the way. They’ve been people who have pushed me in the right direction and have taught me about what is possible outside of my environment. For example, I met a professor who reminded me that the things you’re learning, everyone uses them outside. You need to go literally go outside — to grad school, to these physical places — and learn about these things firsthand.

How have you used your success to bring goodness to the world?

One example is the Women in Data Science Conference. I’ve been involved for a while, and the committee has now increased dramatically. It highlights the women who have made contributions in data science. We’ve created resources for people to learn about data science, and for young people to get involved. But there is a language barrier. I’m starting to host the podcast and do it in Spanish, so we’re crossing borders, literally.

Another example is Clubes de Ciencia, Colombia, which translates to “Science Clubs.” This organization targets highschoolers who understand what research means and teaches kids what’s possible through applied mathematics. In Colombia in particular, children have access to technology resources that they wouldn’t normally.

What are your “5 Things I Wish Someone Told Me Before I Started” and why?

In the professional side, it’s very easy to underestimate the power of communication. In my field, when you interact with executives, customers, users…you need to be able to translate and present your ideas and the key points to any audience. It’s very valuable for people — especially those of us in the technical field or mathematics — to understand and execute the power of communication.

You are a person of great influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. :-)

Me as a person (vs. me as part of Cerebras), I come back to how I started my career. When people think about applied mathematics, it’s hard to connect how you can apply it in real, everyday life. I would love to bring the practical use of mathematics back into school. Kids will be more interested if they understand: “A calculator can do it, a computer can do it, but I need to be able to do it myself, understand the real-world implications, and make informed decisions based on it.

Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?

“When you have to make a decision, make it with the insight you have available at that point in time (not with the hypotheticals). Things will change that you can’t control, but at least you know you made that decision based on what was in your heart.”

“We always try or are told to give 100% in everything, but that’s impossible to do. It’s better to give 80% to one big thing that day, and then prioritize where that other 20% goes in the other aspects of your life.”

How can our readers follow you on social media?

LinkedIn: Cindy Catherine Orozco Bohorquez

Thank you so much for joining us. This was very inspirational.



Fotis Georgiadis
Authority Magazine

Passionate about bringing emerging technologies to the market