President and Strategic Digital Conductor
Wentech
Interview Date: October 21, 2025 | 4:00 PM - 4:40 PM
Through my interview with Mr. Cuman, I gained powerful insights about green AI and its impact on the tech industry and environment. He explained how AI is currently using massive amounts of energy, which is a major issue for tech companies that must solve it themselves.
Mr. Cuman has been in technology business for almost 40 years and provided unique perspectives on combining various ideas to form better solutions. He also introduced me to the concept of Marketech - marketing with emphasis on technology.
AI Research Scientist
Google DeepMind (Previously OpenAI, Apple)
Interview Date: October-November 2025
In my interview with Mr. Goodfellow, I learned how he creates AI simulations of fusion reactors for Google DeepMind. These simulations allow technical parts of the fusion reactor to be tested, like temperature and structure, for clean, renewable energy creation.
Mr. Goodfellow provided multiple research articles and courses to help me learn more about building AI models, along with additional contacts for future interviews.
PhD Student
University of Texas at Dallas
Interview Date: October-November 2025
Mr. Vasireddy proposed a different approach to reducing AI energy consumption. He explained that the amount of computations a model uses is the main energy consumer, so researchers are currently trying to solve this through new coding architecture.
He provided valuable resources and additional professional contacts to continue my research journey.
Data Scientist for Environmentally Sustainable AI
Interview Date: December 2025
Through my interview with Mr. Huang, I learned about how workers at Google are trying to lessen their energy consumption through various new techniques. I gained better understanding of how AI is growing to use more energy per day because of its unsustainable usage and creation.
He emphasized an important point: if we can change people's lifestyle and usage of AI, consumption can inherently be increased or reduced depending on the effects of the change.