The impact of AI and ML on digital assets in driving innovation, enhancing efficiency, and improving the user experience for digital assets is widely acknowledged. But unlocking the full potential of AI and ML requires connecting advances in ML to end-user applications, for example, promotional tools. Join Meenakshi Jindal, Technical Lead, Content Infrastructure and Solutions at Netflix Inc. as she explores how to make the leap.
Challenges to be overcome include:
- Complexity of AI and ML algorithms, different output formats, and a deficiency of transparency in their decision-making process.
- A lack of standard methods for linking digital assets with ML-generated content insight.
- Uncertain timelines for defining and adopting ML to match user requirements.
Meenakshi Jindal discusses:
- Establishing an efficient data pipeline to manage large data volumes and deliver timely ML-generated end-user applications.
- User-friendly Search APIs that enable end-users to interpret and interact with the output of a wide range of ML algorithms.
- The adoption of agile development methodologies to power rapid experimentation, iteration and closed feedback loops.
