Part 11/12:
However, challenges like compute costs and infrastructure remain. The advent of cloud computing has been instrumental in making large-scale models feasible for a range of organizations, enabling innovations that were previously impossible due to computational limitations.
The Broader Perspective and Conclusion
Throughout his career, the speaker observes that the adoption of data science has ebbed and flowed with technological advances, market needs, and industry regulations. While classic analytics for insights have plateaued in some areas, the frontier now extends to responsible AI, model deployment pipelines, and large language models.