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PatentPT: Patent search with LLM-powered solutions

Explore PatentPT, a patent search with advanced language models. Unveiled at YOLO VISION 2023, dive into insights by Davit Buniatyan and explore DeepLake's transformative capabilities.

NUNuvola Ladi
2 min read
PatentPT patent search powered by large language models

Get ready to dive into the world of cutting-edge AI solutions with us as we unpack another insight from the YOLO VISION 2023 (YV23) event, powered by Ultralytics and held at Google for Startups Campus in Madrid.

In this blog we’ll explore the talk given by the founder of Activeloop, Davit Buniatyan, as he takes us through the genesis of PatentPT, an advanced language model reshaping patent search capabilities.

Link to this sectionUnveiling PatentPT#

Ever felt overwhelmed by the sheer volume of patent data and the tedious search process? Let’s discover the genesis of PatentPT, an innovative language model driving change in patent search capabilities.

Led by Davit Buniatyan, this talk will unravel actionable insights into fine-tuning and deploying Large Language Models (LLMs) for patent autocompletion, abstract and claim generation, and advanced search functions within a rich patent corpus.

Link to this sectionActiveloop and DeepLake: A Unified Data Storage Layer for AI#

Before we dive into the nitty-gritty of PatentPT, let's take a look at Activeloop's creation: DeepLake, the Database for AI. With the AI data stack fragmented across various storage systems, DeepLake emerges as a game-changer, offering a unified data storage layer that streamlines AI workflows.

From storing metadata to unstructured data and embeddings, DeepLake simplifies the process, empowering data scientists to focus on training ML models without the hassle of data management.

Link to this sectionExploring DeepLake's architecture and features#

Now, let's delve into DeepLake's architecture and features. With its open-source components and server-less design, DeepLake enables seamless data storage and versioning on object storage while effortlessly connecting to ML models. It also features Deep Memory, a feature which enhances search accuracy without altering embeddings.

Davit allowed us to delve deeper into this workflow with a live demo showcasing Deep Memory's prowess in patent search. We got a firsthand insight into how Deep Memory delivers up to 22% accuracy improvement with sub-second queries at a fraction of the cost compared to traditional solutions.

Say goodbye to endless scrolling through patent databases and hello to lightning-fast, precise search results!

Link to this sectionThe genesis of PatentPT: From concept to reality#

Ever wondered how PatentPT came into existence? Let's rewind the clock and take a closer look at the comprehensive steps taken to create this solution. From LLM model training and fine-tuning to crafting custom features and deploying search APIs, Davit Buniatyan and the Activeloop team leave no stone unturned in their quest for AI innovation.

Link to this sectionUnleashing the power of LLMs: The future of AI solutions#

Overall, PatentPT exemplifies the potential of LLM-powered solutions in specialized fields like patent search. Activeloop's commitment to innovation, coupled with DeepLake's transformative capabilities, pave the way for a future where AI solutions unlock the true potential of unstructured data, faster and cheaper than ever before.

Link to this sectionWrapping up#

As we continue to push the boundaries of AI innovation, it's essential to remember that the true innovation lies not just in the technology itself, but in how it empowers us to solve real-world challenges and drive meaningful change. Join our community, check out our docs and our GitHub repository to stay updated on the latest advancements!

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