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Efficient GPU infrastructure at LinkedIn // Animesh Singh // MLOps Podcast #299
Mar 28, 2025
Animesh Singh, Executive Director of AI and ML Platform at LinkedIn, leads the charge in evolving AI technologies. He dives into the transformative impact of large language models on recruitment, highlighting LinkedIn's Hiring Assistant. Animesh also discusses the financial challenges of GPU infrastructure, emphasizing the need for optimization strategies. The conversation touches on real-time training and the intricate balance between scaling AI advancements and managing costs, offering insights into the future of AI and infrastructure innovations.
59:13
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Quick takeaways
- Animesh discusses the practical applications of LLMs at LinkedIn, highlighting their role in profile summarization and enhancing candidate experiences.
- The significant increase in LinkedIn's GPU fleets underlines the escalating infrastructure costs tied to training and deploying LLMs effectively.
Deep dives
The Impact of LLMs on Industry
The rise of Large Language Models (LLMs) has significantly altered the landscape of various industries, moving beyond the initial hype to showcase practical use cases. The seamless interaction seen with applications like ChatGPT has led to increased adoption, enabling new functionalities like automated profile summarization and personalized outreach strategies for recruiters. LLMs have proven effective in enhancing productivity through diverse applications, from generating code to automating tasks. LinkedIn, for instance, has incorporated these technologies to improve candidate experiences and personalize communications effectively.
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