AI, Data, and the Future with Sadie St. Lawrence

Description

In this episode, Sadie, Chief AI Officer at SSL Innovations, talks about how AI has evolved. She covers the move from discriminative models to embracing Gen AI models, the need for a robust data strategy before adopting AI projects, and opportunities for career growth in the AI field. Join us for valuable insights into the changing AI landscape and its strategic aspects.

Speakers

Tarush Aggarwal

Sadie St. Lawrence

Key takeaways

Evolution from discriminative models to generative models

‍Discriminative models have dominated the AI landscape for long. The rise of generative models, like Gen AI, marked a shift, enabling a broader audience to leverage AI tools.

Impact on employment

While AI may automate and replace certain roles, it is expected to create new roles, requiring a focus on upskilling, and re-skilling. The World Economic Forum's estimate suggests that AI will create more jobs (96 million) than it replaces (83 million).

Data's role in AI strategy

Having a strong data strategy is crucial for using AI effectively. When we look at traditional AI applications and generative models, it becomes clear that the quality of data directly influences how well AI works.

Human Machine collaboration

The next phase in AI development is the seamless collaboration between humans and AI. The key focus is on application of generative AI to improve efficiency of business.

Challenges in AI evolution

The societal and psychological aspects of AI adoption and collaboration are deemed more challenging than technical advancements.

AI's impact on robotics and future developments

AI and robotics coming together, especially in companies like Tesla, is a big deal. It's exciting to think about the future when advanced AI models like GPT keep getting better.

Episode Highlights

“Women In Data started in 2015 and truly originated from a personal need. While pursuing my master's degree, I suddenly realized there weren't many women working around me. I told myself that if I was going to survive, I would need a community of people”

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Sadie

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“There are many roles that build up to being in AI. It's just not one; uncover the layers of what it means to be in AI. There still is a high demand for the analyst roles, data engineering, and data product management or AI product management side of things. ”

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Sadie

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“The Human Machine Collaboration Institute is doing research on how individuals can best work alongside AI. The way I see it, for the next 5 years, humans will work alongside AI. In the next 10 years, AI will handle between 60% to 80% of human knowledge work. Then, in around 10 years, we will really start to merge with the machine.”

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Sadie

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Discover how data management is evolving from the Modern Data Stack (MDS) to Intelligent Data Platforms. Our guest, Sanjeev Mohan, sheds light on the reasons behind this shift and its impact on businesses. Tune in to learn about the challenges with MDS, the rise of Intelligent Data Platforms, and what it means for organizations.