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Enhancing Fine-Tuning Efficiency with Low-Rank Adaptation (LoRA)


In the dynamic field of artificial intelligence (AI), fine-tuning models for specific tasks is crucial for success. However, traditional methods often encounter computational burdens and overfitting risks. This is where Low-Rank Adaptation (LoRA), a revolutionary technique redefining the paradigm, steps in.

During our live talk, we will delve into the intricacies of LoRA compared to Singular Value Decomposition (SVD), emphasizing their applications, differences, and how LoRA’s selective parameter updates can significantly enhance efficiency and model integrity.

Designed for professionals in data science and AI, this event will equip you with practical insights into advanced techniques, ensuring that your projects are not only efficient but also adaptable, and prepared to tackle the challenges of modern AI applications.

Key Takeaways:

  • Understand LoRA’s role in efficient fine-tuning of AI models.
  • Learn how LoRA minimizes overfitting while maintaining model integrity.
  • Explore the differences and applications of LoRA and SVD in data science.
Enhancing Fine-Tuning Efficiency with Low-Rank Adaptation (LoRA)
Danny Butvinik

Chief Data Scientist at NICE Actimize

Danny Butvinik is a distinguished leader in artificial intelligence and data science, with over two decades of expertise. Currently serving as Chief Data Scientist at NICE Actimize, he leads pioneering research and development initiatives, driving strategic insights for the organization and its clients. Widely recognized as an influential voice in the AI and Data Science community, his thought leadership is underscored by a prolific publication record and five patents in AI and ML, affirming his creativity, innovation, and expertise. Danny is dedicated to shaping the industry’s future with his unwavering commitment to promoting the transformative potential of data science.

We are looking for passionate people willing to cultivate and inspire the next generation of leaders in tech, business, and data science. If you are one of them get in touch with us!