AI-Driven Innovation: Enhancing patent drafting and monetization with LLMs - ON-903

Genre de projet: Innovation
Discipline(s) souhaitée(s): Génie - informatique / électrique, Génie, Informatique, Sciences mathématiques
Entreprise: XLSCOUT LTD.
Durée du projet: 6 mois à 1 an
Date souhaitée de début: Dès que possible
Langue exigée: Anglais
Emplacement(s): ON, Canada
Nombre de postes: 5
Niveau de scolarité désiré: Études de premier cycle/baccalauréat
Ouvert aux candidatures de personnes inscrites à un établissement à l’extérieur du Canada: Yes

Au sujet de l’entreprise: 

XLSCOUT is the World’s Largest AI-enabled Technology Database & IP Analytics Platform with 150+ Million Patents & 200+ Million Research Publications. We use the best data patent, NLP, and other data sources available in the market and further improve, standardise, and enrich the data by using a combination of machine learning algorithms, and manual validation. We are one of the only platforms that provide both an advanced search option for IP professionals and an NLP-based interface that is intuitive and easy to use regardless of IP skill level.

Veuillez décrire le projet.: 

What is the innovation project about? This project, spearheaded by XLSCOUT, focuses on the application of Large Language Models (LLMs) in the realm of patent-related processes, specifically targeting patent drafting and monetization. The primary objective is to develop an AI-powered system that significantly enhances the efficiency, accuracy, and innovation in these areas.

What is the main goal of the company (a final product, software, knowledge in a specific area, etc)? At the core of this project is the integration of advanced AI, particularly LLMs, into the patent drafting process. The aim is to create a system that can assist in generating comprehensive, legally sound patent documents with minimal human intervention. This system will leverage the vast database of patents and legal texts, utilizing LLMs to understand and mimic the complex language and structure inherent in patent documentation.

What is the innovation or incremental innovation to be developed (i.e. business model, product or process development/improvement, service delivery, etc.)? The second major facet of this project is the application of LLMs in patent monetization. Here, the goal is to develop an AI-driven framework capable of identifying and evaluating potential commercial opportunities for patented technologies. This involves analyzing market trends, competitor activities, and technological advancements to provide strategic insights for effective patent monetization.

What methodology/techniques are to be used? Methodologically, the project will employ a combination of natural language processing (NLP), machine learning (ML), and data analytics. These techniques will be utilized to process and analyze large datasets, train the LLMs, and continuously refine their performance.

Expertise ou compétences exigées: 

The ideal candidate for this MITACS internship should possess a strong background in Computer Science, Artificial Intelligence, or a related field, preferably at the graduate level.

Key required skills include: 

1. Proficiency in NLP and ML, with a specific focus on LLMs. 
2. Experience with AI and ML algorithms, particularly those relevant to text analysis and generation. 
3. Strong programming skills, particularly in Python and relevant AI/ML frameworks. 
4. Ability to work with large datasets and conduct data-driven research. 
5. Excellent analytical and problem-solving skills. Assets include experience in working with big data, a proven track record in AI-related research, and publications in relevant fields.
6. The intern should be capable of working independently as well as collaboratively in a team, demonstrating initiative and innovation in their approach.