PatSeer Unveils Cutting-Edge AI Semantic Search with Custom-Trained GPT Model

Leading Patent Search and Intelligence platform, PatSeer Unveils Cutting-Edge AI Semantic Search with Custom-Trained GPT Model

With this new capability, PatSeer continues to revolutionise the patent research domain by bridging the gap between Boolean and AI-based systems

PatSeer, a leading Indian AI-driven B2B SaaS platform for Intellectual Property (IP) Research and Intelligence is excited to announce a completely new and rebuilt semantic search powered by an advanced GPT-driven language model. The new semantic search replaces its older Natural Language search capabilities in the product by custom-training the underlying LLM model to understand patent semantics. PatSeer's new AI search feature brings a significant improvement in result accuracy on tests conducted across various research sectors, further solidifying their presence as a global company which caters to prominent blue chip firms in India and abroad. PatSeer is also the platform of choice for the Indian Patent Office for their day to day patent examination activities.

With this new development, patent professionals are no longer confined to the contextuality limitations of Boolean searches and can capitalise on PatSeer’s AI capabilities for comprehensive searches. As a platform that’s used by thousands of IP searchers on a daily basis, PatSeer’s complex Boolean search functionality will continue to remain crucial for certain IP projects. However now, with the integration of the new semantic search, PatSeer is offering the best of both worlds, eliminating the need for two separate systems.

Further, with a true Boolean and AI integration, users get unique capabilities that neither can provide independently. For example, one can initiate a semantic search and narrow the results iteratively with Boolean searches and vice versa. It also allows for the semantic re-ranking of Boolean results using a paragraph or a relevant patent. The system also suggests related records to existing results based on the underlying language model’s contextual understanding. For transparency purposes, users can view the closest matching snippets from full text to understand why a record scored higher in their results. The new semantic search is also immediately available as an API for integration into internal systems.

Manish Sinha

“In the many conversations with patent professionals, I’ve been told that Boolean and AI-based patent systems will always be separate tools and I could never accept that,” remarked Manish Sinha, Founder and Chief Technology Officer at PatSeer. “I’m excited to debunk that notion today. PatSeer has become the first to offer a seamless fusion of transformative AI-driven search within a professional patent search database. The days of maintaining access to two separate solutions or paying by the query are over. At PatSeer our commitment to harnessing the power of Deep Learning AI to tackle greater challenges remains stronger than ever. Following the launch of our AI Classifier last year, the advent of our new Semantic Search marks another significant milestone in this journey. We are quite excited with the possibilities here and the road ahead.”

With a commitment to remain at the forefront of AI-driven solutions, PatSeer is paving the way for the future of patent research. PatSeer offers IP experts worldwide patent search with AI technology, faceted filtering, advanced analytics for comprehensive IP business intelligence, an intuitive user experience, and optimised workspaces, and leads the charge in utilising AI within IP research and analysis tools. It aims to establish itself as the pioneer in addressing significant challenges in the field by offering customised AI solutions tailored to meet its clients' unique needs.

Intellectual property (IP) and patent research have become essential elements of today's ever-changing world of technology and innovation. Intellectual Property encompasses various forms, including patents, trademarks, copyrights, and trade secrets. Among these, patents stand out as legal documents that grant their holders exclusive rights to an invention for a specified period, typically 20 years from the filing date. This exclusivity empowers inventors to prevent others from making, using, selling, or importing their inventions without permission.

Patent research involves delving into patent databases to extract useful information about emerging innovations and industry trends. This form of research helps businesses make informed choices regarding product development, market strategies, and intellectual property protection. Beyond its corporate applications, patent research also serves the interests of policymakers, investors and the general public, by providing them with essential data that can influence technological and social advancements.

Google Brings Experimental Generative AI-powered Search in Hindi and English in India

Google is expanding the availability of Search Generative Experience (SGE) to India, aiming to enhance user search results using generative AI technology.

Google announced that its rolling out SGE as an experiment in Search Labs in India in English and Hindi.

Google is using AI innovations in India for Search that focus on bilingual users’ needs, new search capabilities with camera, and a new speech recognition model for Hinglish users.

With generative AI in Search, relevant queries will now have an AI-powered overview showing key information, with links to explore more

The search giant is introducing India-focussed features that are unique to SGE in INDIA, Such as — switch from an English result to Hindi by tapping the language toggle button, listen to the response with Text-To-Speech by tapping the ‘Listen’ button, and Google will also be rolling out an another feature wherein users will be able to tap the microphone icon in conversational mode to ask follow-up questions instead of typing them.

AI-powered Search experience in Hindi

The underlying tech of SGE are multiple large language models (LLMs) including an advanced version of Google’s MUM as well as PaLM 2.

For uninitiated, Google is developing a new technology for answering complex search queries called “MUM,” which stands for Multitask Unified Model. While, PaLM 2 is the latest Large Language Model (LLM) released by Google, in May this year, that is highly capable in advanced reasoning, coding, and mathematics. It’s also multilingual and supports more than 100 languages. PaLM 2 is a successor to the earlier Pathways Language Model (PaLM) launched in 2022.

Moreover, SGE is also available for programming languages and can be used to easily understand and debug code, with color-coded syntax highlighting that makes it easier for programmers to review. SGE currently provides AI-generated overviews to help with tasks across a number of programming languages and tools. For example, you can find answers to how-to questions, and see suggested code snippets for common tasks. Segments of code in overviews are even color-coded with syntax highlighting, so it’s faster and easier to identify elements like keywords, comments and strings, helping you better digest the code you see at a glance.