During his studies, Petar's interest in math, physics, and computer science guided him to earn a PhD in machine learning from Cambridge. Originally aiming to be a software engineer, he joined Deepmind after internships in AI sparked a love for research.
@whats_ai
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DeepMind Scientist on Graph Neural Networks and AI Research
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I had the pleasure to interview @PetarV_93
, a research scientist at Deepmind and lecturer at Cambridge University, specializing in graph neural networks. He discusses his early interest in programming and transition into AI research. Some insights… -
What’s AI: Simplified AI Education on YouTube and Podcast
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Want AI simplified? Dive in with 'What's AI' on YouTube/podcast. Follow now for AI, demystified! 🙂
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Building Successful AI Careers: PhDs, Projects, and Insights
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PhDs matter, but unique projects and quality insights make you stand out. Building a successful AI career needs proactive learning and effective use of resources. Watch the insightful interview here: https://
youtu.be/KdyAE1vhLmY -
AI Competition Success: Skills, Preparedness, Career Opportunities
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Aleksa's success illustrates the importance of preparedness, competition and critical thinking. His experience shows engaging in AI contests, continual skill enhancement, and aiming for practical outcomes lead to AI opportunities.
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Developer Streams 30-Day NLLB Model Replication Project
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He is still constantly learning and sharing. Aleksa even recently did a 30-day coding live streaming working on replicating Meta's NLLB (No Language Left Behind approach)
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ML Research and Computer Vision Advances in AI Infrastructure
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Primarily focused on ML research and implementation, he also shows a clear passion for AI infrastructures, evident in his work with Microsoft HoloLens. His talks highlight the recent advancements in computer vision, offering new insights into AI's potential for unstructured data.
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From Microsoft to DeepMind: Building a Unique AI Research Career
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Ever considered a unique career in AI? @gordic_aleksa
's journey from research engineer at Microsoft and DeepMind exemplifies how curiosity, determination, and practical learning create AI opportunities. -
Aleksa’s ML Journey: From Electronics to AI Epiphany
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Aleksa's transition from digital electronics to Machine Learning demonstrates continuous learning and practical projects. Notably, his YouTube channel "AI Epiphany" reflects his vision for beneficial AI advancements.
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What’s AI: YouTube and Podcast Guide to Demystifying AI
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Want AI simplified? Dive in with 'What's AI' on YouTube/podcast. Follow now for AI, demystified! 🙂