Petah Tikva, Israel

Yakov Gazman


Average Co-Inventor Count = 1.0


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Yakov Gazman: Innovator in Language Model Improvement

Introduction

Yakov Gazman is a notable inventor based in Petah Tikva, Israel. He has made significant contributions to the field of language models, particularly through his innovative approach to automated prompt engineering. His work focuses on enhancing the performance and alignment of language models, which is crucial in the ever-evolving landscape of artificial intelligence.

Latest Patents

Yakov Gazman holds a patent for a method titled "Language model improvement through automated prompt engineering." This patent describes a process where an alignment score is generated for a test language model using input data that includes various triplet data structures. If the alignment score does not meet a specified threshold, the method identifies a fail triplet data structure. A judge language model is then executed on this fail triplet to determine the type of misalignment produced by the test language model. The judge language model is re-executed to identify the cause of the fail response, leading to the generation of an enhanced prompt.

Career Highlights

Yakov Gazman is currently employed at Intuit, Inc., where he continues to develop and refine his innovative ideas. His work at Intuit has allowed him to apply his expertise in language models to real-world applications, contributing to the company's advancements in technology.

Collaborations

Yakov collaborates with talented coworkers, including Linoy Cohen and Udi Menkes. Their combined efforts in research and development have fostered a creative environment that encourages innovation and problem-solving.

Conclusion

Yakov Gazman's contributions to language model improvement through automated prompt engineering exemplify the impact of innovative thinking in technology. His work not only advances the field of artificial intelligence but also sets a foundation for future developments in language processing.

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