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Secrets of Data Analytics Leaders

The Data Leader’s Guide to Generative AI, Part I: Models, Applications, and Pipelines - Audio Blog

Dec 15, 2023
This podcast explores the introduction of Generative AI and its impact on early adopters, covering the benefits and challenges faced. It discusses the process of fine-tuning a pre-trained Language Model on domain-specific language and facts. It also explores the application of Gen AI in industries such as travel booking, software development, and healthcare. Additionally, it discusses the responsibilities of data teams in managing data pipelines for Generative AI and the importance of preparing teams for successful Gen AI initiatives.
09:13

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Quick takeaways

  • Data leaders should modernize their environments, extend governance programs, and collaborate with data science teams to ensure the success of Gen AI initiatives.
  • Companies aiming to gain a competitive advantage with Gen AI should focus on feeding domain-specific data to Language Models and implement options such as building a model from scratch, fine-tuning a pre-trained model, or injecting domain-specific data into prompts.

Deep dives

Key Point 1: Benefits and Risks of Generative AI

Generative AI, also known as Gen AI, offers both upsides and downsides to early adopters. The upsides include rich digital interactions and increased productivity. However, the downsides can range from confusion among customers to operational errors and privacy breaches. The key to achieving positive outcomes lies in having timely, accurate, and trustworthy data. Chief data officers (CDOs) and their teams play a crucial role in making Gen AI initiatives successful by modernizing their environments, extending governance programs, and collaborating closely with data science colleagues.

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