Rahul Pandita

Title: Innovations by Rahul Pandita

Introduction

Rahul Pandita is an accomplished inventor based in Arvada, Colorado. He has made significant contributions to the field of technology, particularly in the areas of language models and package classification. With a total of three patents to his name, his work reflects a commitment to advancing innovation.

Latest Patents

One of Rahul's latest patents is titled "Slot extraction for intents using large language models." This invention discloses techniques for performing contextualized intent and slot extraction using a large language model (LLM). The LLM is pre-trained on a diverse corpus of language training data. A prompt is provided to the LLM, which includes a limited number of prompt phrases that share a semantic relationship. The process involves recording a spoken utterance, converting it to text, and generating a transcription. The LLM then extracts an intent and a slot from the transcription, identifying the extracted intent as related to the prompt-described intent.

Another notable patent is "Generic feature extraction for identifying malicious packages." This invention focuses on classifying packages based on generic feature extraction. A computer system identifies training packages, including subsets known to be malicious and benign. It extracts training feature vectors from these packages and trains a classification model. After training, the model can classify a subject package as malicious or benign based on its feature vector.

Career Highlights

Rahul currently works at Microsoft Technology Licensing, LLC, where he continues to innovate and develop new technologies. His work at Microsoft has allowed him to contribute to significant advancements in the tech industry.

Collaborations

Rahul collaborates with talented individuals such as Priyankar Kumar and Aneesh Bose. Their teamwork fosters an environment of creativity and innovation, leading to impactful technological advancements.

Conclusion

Rahul Pandita's contributions to technology through his patents demonstrate his expertise and commitment to innovation. His work not only enhances the capabilities of language models but also improves the security of package classification systems.