In this episode of Leading with Data, we have Aleksa Gordić with us. He is a self-taught enthusiast who transitioned from electrical engineering to a key player at tech giants Microsoft and DeepMind. Aleksa shares invaluable insights on persistence, personalized learning, and the transformative power of internships. Explore his strategic approach to content creation on YouTube and his current venture, Ortus AI, aiming to bring multilingual AI systems to the forefront. Join us as we delve into the rapidly evolving landscape of AI, touching on hardware, software, metaverse integration, and the unpredictable nature of this groundbreaking field.
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Key Insights from our Conversation with Aleksa Gordić
- Aleksa’s AI journey highlights the significance of persistence and self-learning.
- Crafting a personalized AI learning path is crucial for success, surpassing generic courses.
- Internships and a competitive drive play a transformative role in personal and career growth.
- Aleksa’s YouTube strategy emphasizes technical depth for building a knowledgeable community.
- The move towards multilingual AI systems holds potential for global impact, especially in non-English-speaking regions.
- AI development is dynamic, focusing on hardware innovation, software optimization, and integration with emerging technologies like the metaverse.
- Continuous learning from diverse sources, including biographies, classics, and business books, adds substantial value to an AI professional’s journey.
Now, let’s look into Aleksa Gordić’s responses to some of the essential AI questions!
How did your Journey into Data Science Begin?
As an electrical engineering student, I was initially focused on hardware, but I realized the vast opportunities in software. I pivoted towards software engineering towards the end of my studies, self-taught Android development, and immersed myself in hackathons and datathons. My friend, who interned at big tech companies, inspired me to delve into algorithms and data structures, which led me to prepare for big tech interviews. Despite rejections from Facebook and Microsoft, I persevered, eventually landing a job at Microsoft, working on the HoloLens project. This experience piqued my interest in machine learning, leading me to self-study, read papers, create YouTube videos, and ultimately work at DeepMind as a research engineer.
What Inspired you to Create your own Learning Path in AI?
I believe that no one knows better than you what the optimal curriculum for your personal development is. I’ve always been a self-learner, whether it was transforming my body through sports or learning new languages. I’ve found that I learn more efficiently on my own. While there are many generic curriculums like Fast AI or Coursera courses, I wanted to craft a path that was tailored to my interests and strengths.
Can you Share a Pivotal Moment from your Internship in Germany?
My time in Germany was transformative. I realized I needed to channel my energy into a specific field rather than being a “renaissance man” with broad interests. I was inspired by my peers and became competitive, not against a single person but against the progress of the industry. This drive led me to focus on machine learning, particularly the visual component, which I found more satisfying than text analysis.
What Led you to Start your YouTube Channel, AI Epiphany?
Influenced by Gary Vaynerchuk’s approach to documenting his journey, I wanted to create a public presence and teach others as a way to learn more myself. The pandemic provided the perfect opportunity to start my channel. Although I was camera shy at first, I pushed through and focused on creating super technical content. I aimed to build a strong technical community rather than chase views with beginner-friendly content.
Tell us About your Current Startup, Ortus AI, and its Focus
Ortus AI’s initial product was YouTube AI Buddy, a Chrome extension for querying YouTube videos. However, I’ve shifted focus to building multilingual AI systems, starting with a replication of Meta’s “No Language Left Behind” project. I’m currently working on machine translation models for Croatian, Serbian, and Bosnian languages, aiming to open-source these models for commercial use. My goal is to address the industry’s English-centric focus and support businesses in non-English speaking regions.
How do you See the Development of Generative AI and Transformers in the Near Future?
The AI field is unpredictable, as seen with the sudden impact of ChatGPT. I’m excited about innovations across the entire stack, from hardware advancements challenging Nvidia’s monopoly to software developments like OpenAI’s Triton. I’m also intrigued by the progress in large language models, efficient attention mechanisms, and the potential for AI to run on personal computers in the near future.
Summing Up
Aleksa Gordić unfolds the narrative of his AI journey, emphasizing the significance of personalization, a competitive spirit, and continuous learning. From crafting a tailored learning path to founding Ortus AI, he exemplifies the resilience needed in AI.
For more engaging sessions on AI, data science, and GenAI, stay tuned with us on Leading with Data.
