This article was co-authored by Gokhan Celebi, VP of Global Growth for Reengen and Goktug Ocal, data scientist, control engineer, and a technology enthusiast for Reengen.
Reflections of our learnings from Amazon (US), Relab (UK), Invest Horizon (Europewide), Oracle (Middle East) and many other programs we were selected out of 1000s applications.
Wondering why?… Keep reading
Artificial Intelligence is extremely popular with studies in different use cases and different application domains. The plentiful choice of AI competitions and challenges provided by AI communities, universities and cloud computing services are all around. The competitions can be for both individuals and start-ups, so there are different approaches to the competitions.
But what makes you unique to be successful? And how to separate from the crowd?
Absolute Teamwork: If you are a start-up company, you need to study with your team to create a concept with domain knowledge, use case and solutions.
While working for a competition, it is important to have or create a powerful use case of AI in a specific domain. That’s why studying with different team members in the company is suggested to look from a wide perspective. You can support your AI use case with the perspectives of product management, customer success, software development and sales members. After created an AI use case, it is up to the data scientist or ML/AI engineer to apply AI to the decided case and domain.
Technical (& True) Domain Knowledge: For instance, in the energy industry, there are various applications of AI such as forecasting energy consumption, root cause analysis those analyses are crucial for energy managers. Forecasting energy consumption allows managers to predict billing information and taking precautions as rescheduling operations in retails, the hospitality industry, banking, etc.
Therefore, and in this case, the most important part of the competition is building a high-performance forecasting model. There are several state-of-art solutions, of course, but it is important to apply these solutions to your use case successfully and representing the solution perfectly with pretty data visualization techniques. In the algorithm development study, there are different environments for building AI models and cloud computing services to carry the AI algorithm to the cloud such as AWS and Oracle.
To make the long story short, a solution that using well-known services and environments with a strong use case in a specific domain is going to make you achieve success in the competitions.
Claro como el agua (English: Clear, Succinct, and open) Do not try to make things up. If the question is asking your business model just saying SaaS with 24/36/48 months’ contracts should be enough. Or if you are asked to say your traction you may say 256 clients in 38 countries and serving for 16300 premises. That simple and easy going. If you are talking about the AI use cases, you may prefer (Apart from the technical explanations we touched upon earlier) saying identified 300 anomalies with utilizing TensorFlow algorithms and have helped clients to save 7 Giga Ton of CO2 and 15 Gwh of Energy.
Other’s: Do not underestimate this section. It may be somehow the most important part of your application. You may mention your AI-related awards. Or AI-related international projects (Horizon 2020, Innovate UK etc.) you have involved in and your contributions to them. You can even consider having a testimonial from one of your clients – Global ones make more sense.
Good luck with your applications!
Göktuğ Öcal is data scientist, control engineer, and a technology enthusiast currently serving for Reengen. He is currently working on state-of-art machine learning and statistical models for data analysis in the energy industry. He makes analysis, data visualizations, and dashboards.
He has graduated from ITU. During his education, he worked on intelligent control systems, time series analysis, and forecasting techniques, deep learning models in the Artificial Intelligence and Intelligent Systems (AI2S) Laboratory of ITU.
He is a cinema, philosophy, and sports enthusiast; loves to follow news about cinema and e-sports. He is an amateur visual designer.
