“As a high school student, I was always interested in mathematics and logic. I was able to combine this interest with the practice of solving mathematical and logical problems during my Computer Science studies. In the beginning, solving these problems would require a couple of students to work together but at some point, the problems got too complex and this is when machine learning got introduced. I was immediately amazed by how a computer could get to solutions involving massive datasets or complicated classification problems.
As an intern at Geronimo.AI, I get to apply this enthusiasm in the real world. I’m solving problems for other businesses with the usage of machine learning and this is done in a great working atmosphere with super talented colleagues who help me develop as a Machine Learning Engineer.“
“Throughout my young life I have had two major passions, the arts and the natural sciences. Therefore, I faced the crossroads of the creative and the scientific path. Finally the decision fell to study Applied Physics in Delft which after a year made me feel very abstract and theoretical.
My desire for self-expression and tangible things made me switch to Computer Science after which I quickly started working as a programmer. Without a clear direction up front, I found myself in a place where all my interests met: the natural sciences, my desire to do tangible things and even my creativity all came together while creating software. I even got paid while doing so!
Therefore, when the study times slowly faded and a decision had to be made about the future, starting a software company with a couple of friends (and amazing engineers) was a no-brainer for me. Besides engineering, I greatly enjoy the process of shaping requirements, getting to know new domains, and keeping a tight feedback loop to make sure our software is not just awesome, but useful in the long term for the client.”
“During my education and career, I found out I like to be challenged with technical problems. Seeing a solution to a problem coming to fruition and contributing in a company gives me a lot of satisfaction.
These things are continually present in the projects we do at Geronimo.AI, where I can apply machine learning to quickly solve difficult problems with data. Using these techniques for varied problems requires to stay up to date with the current state of the art, which I think is exciting. Founding Geronimo.AI has allowed me to contribute to finding problems that can be solved using machine learning and to actually solve them, which gives me a lot of energy to push for the best results.”
“I’m an engineer by heart. I love to create and build things. In my childhood I used to shake my presents to see whether there were LEGO bricks inside, to be prepared for the disappointment if there were none. My work these days mainly consists of coming up with and writing clever algorithms to tackle the challenges of our clients, which feels like I’m playing with LEGO bricks everyday.
Building algorithms doesn’t mean I’m sitting behind my PC all the time. Often, I’m having brainstorm sessions with the team to find the best solutions. What gives me energy, is that every time we enter the meeting room for a brainstorm session, everyone has a different idea in his or her head. But after the session, all the thoughts are aligned into one plan and mission to tackle the challenge.
What motivates me even more is to see the diversity of our team. I think it is essential that we did not start as four engineers that only want to write code. Instead, we have a balanced team, including people that are more “business” oriented, which understands what decisions to make to keep the startup growing.”
“Throughout my technical education I have had a broader scope resulting in great extracurricular activities in management and commerce. I often get the question whether I pity the fact that I don’t use the knowledge from my studies. However, my technical background supports me to swiftly understand client’s problems and possible solutions.
My enthusiasm for startups arose during my exchange period in Melbourne during the events of the incubator over there. I enjoy my job every day having the most diverse weeks and meeting many interesting people. I get most fulfillment when finding a challenge which our team is eager to solve and which really helps our client forward.”
“Technology and science have always been a great interest of mine, I grew up building robots with Lego and assembling computers. During high school, I dabbled a bit in web development. During my study of Chemical Engineering at Delft University of Technology I got introduced to analysing data, modelling processes and performing optimizations.
For a couple of years now, I have been following the developments of machine learning with great interest. At my previous job I cultivated my passion for consulting, business and IT. There I found out that besides solving technical problems, I really enjoy working together with the client and my colleagues to develop the most efficient solutions.
Working at Geronimo.AI combines all of these factors along with the startup culture, interesting problems, active sharing of knowledge and great colleagues.”
“Throughout the course of my studies I have always enjoyed tackling problems in unfamiliar settings. Having formed a basic understanding of mathematical and programming concepts, learning how to apply machine learning algorithms feels like a natural progression which will provide me with the tools to understand and solve problems in a wider variety of contexts. Leveraging the enormous amounts of data being generated daily with the objective of improving and facilitating people’s everyday lives is exciting to me, and working at Geronimo.AI is enabling me to do so.“
After having studied statistics and mathematics from a theoretical point of view at the University of Cambridge, I wanted to put my skills into practise in a more applied setting. I have joined Geronimo.AI for two reasons, the first being the interesting and impactful projects the company is working on. The second reason for joining this startup is that the technical expertise and hands-on approach of my colleagues are a good complement to my theoretical background and more conceptual way of thinking.
“As a part-time engineer at Geronimo.AI I have the opportunity to combine my academic studies with the knowledge I acquire at work. I’m a master student in Applied Mathematics at Delft University of Technology, so there is a lot of common ground to be found between my studies and AI applications. I believe both worlds can reinforce one another. Working at Geronimo.AI provides a welcome change to the more abstract side of mathematics and helps me stay in touch with the fascinating world of machine learning.”
“Ever since I have heard of artificial intelligence, I was fascinated by its effectiveness. It can offer solutions in almost every field and the groundbreaking results that are booked can be intriguing sometimes. My master gave me a solid understanding of the maths behind AI and helped me explain the magic. We are nowhere near programming robots that take over the world. To me, AI contains a bunch of algorithms that started solving everyday problems when the increase in data and computation power was realised.
At Geronimo.AI, I work with techniques that interest me and I find a great challenge in applying them in various situations in which they are useful. The aspect of a young and dynamic team is something that I really enjoy. Both the technical challenge and the social environment make me go to the office enthusiastic every day.“
Geronimo.AI maintains the solution and is available for IT support.
At some point, Minsky & Co wants to migrate to a new platform. Depending on the requirements of the solution, Geronimo.AI will either develop the interfacing in the solution to make it compatible with the new platform or guide Minsky & Co how to interface with the solution if it is developed in a sandbox environment.
Garry, an employee from another department, talks with Alice and Bob on a company event and discovers the solution is also applicable to his workflow. However, for that purpose the accuracy has to be increased to 95%. Geronimo.AI will modify the solution to incorporate new data sources and will repeat computations when necessary.
The solution with 90% accuracy is accepted and decided to be implemented. The algorithmic chain is extended and attached to the digital solution of Minsky & Co.
Geronimo.AI will setup the data pipeline to collect the required data coming from Minsky & Co API’s, databases and open data sources. Finally, the computation and required interfaces will be implemented.
Alice and Bob receive a final training on using the solution and understanding the outcomes and are now able to make decisions based on the expected sales of the next quarter.
To validate the feasibility of the business case, the core algorithmic chain is developed on a representative dataset in close cooperation between Minsky & Co and Geronimo.AI.
The result is that, using video streams and satellite data, Minsky & Co can predict the expected sales of devices in the next quarter with an accuracy of 90%. Furthermore, it is discovered that by gathering temperature data and buying commercial high-accuracy satellite data, the solution accuracy can be increased to 95% and offer insight into the next 4 quarters.
Minsky & Co owns expensive electrical devices and the corresponding data. The board of Minsky & Co have heard about big data and AI and are eager to explore these new fields.
The Geronimo.AI team will visit Minsky & Co and give presentations explaining the concepts and practicality of AI solutions, alternated by interactive sessions in which the attendees are trained to apply the newly learned techniques to their everyday challenges.
After this workshop, employees of Minsky & Co will have the required awareness and understanding of AI to be able to identify possible data driven solutions for their challenges.
The seeds of the potential of your data are planted.
Alice and Bob, an operator and manager at Minsky & Co, attended the workshop and see the possibility of a data driven solution coupling video streams and satellite data with the expected sales of devices in the next quarter.
Together with our engineers the data will be reviewed (quality, quantity and availability) and different algorithmic solutions and possible outcomes are discussed. This will result in an identification of the strength of the business case.