Bikalpa Neupane, Head of AI at Takeda, discusses transitioning from legacy to data-centric culture in AI economy. Challenges for large enterprises with open-source AI tools. Navigating AI landscape for small firms. Importance of data sharing, talent, and industry diversity.
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Quick takeaways
Legacy firms face challenges in transitioning to an AI-driven culture due to diminishing traditional data moats.
Large firms are losing advantages as open-source AI tools become more accessible, emphasizing the importance of differentiation.
Deep dives
Challenges for Legacy Enterprises in the AI-Driven Economy
Legacy firms face challenges in transitioning to an AI-driven culture due to the diminishing advantages of traditional data moats. As open-source AI tools become more accessible, large firms are losing structural advantages. The podcast discusses the importance of differentiation and leveraging in-house data to stay relevant and accurate in a competitive market.
Strategies for Smaller Companies in AI Adoption
Small firms must focus on differentiating their data, tools, and platforms to succeed in AI adoption. With a crowded market using similar models, unique approaches like leveraging proprietary data or embedding models in complex workflows are crucial. The scalability of AI projects is emphasized, highlighting the importance of focusing on data, workflow segments, and customer value.
Scaling Considerations in AI Adoption
Scaling AI projects involves significant costs, encompassing inference, training, data center, and hosting expenses. The podcast delves into the complexities of scaling AI systems, including higher costs associated with proprietary data, model accuracy, and energy consumption. It stresses the need for experimentation, innovation, and ethical considerations in AI scaling initiatives.
Today’s guest is Bikalpa Neupane, Head of AI/GenAI and Natural Language Processing at Takeda. Bikalpa returns to the program to talk about the difference between a legacy enterprise culture and a data-based enterprise culture, showing how legacy leaders in sectors as diverse as healthcare, financial services, manufacturing, and beyond can make the transition in today’s AI-driven global economy along the way. Later, he and Emerj Senior Editor Matthew DeMello pull apart challenges for large enterprises as more open-source AI tools become available to individuals, eroding the traditional and structural advantages legacy firms have long held in the marketplace. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!
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