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Practical AI: Machine Learning, Data Science, LLM
Towards stability and robustness
Jul 20, 2021
48:32
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Quick takeaways
- Implementing stable AI models is crucial for successful deployment in production.
- Active engagement from both business and technical personnel is necessary to overcome AI implementation challenges.
Deep dives
The Importance of Transitioning from Research to Practical AI Applications
Developing practical AI solutions requires bridging the gap between academic research and real-world application. Academic research constitutes only a small percentage of AI discourse, yet enterprises often struggle with a high failure rate in AI implementation. To address this, focusing on practical elements essential for production success is crucial.
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Discover
highlights
Listen to the best highlights from the podcasts you love and dive into the full episode