Delving into the complexities of machine learning patents? Discover Neil Kardos' expert strategies for crafting applications that surpass the ordinary. Our latest Practical Patents blog provides a nuanced approach to ensuring your machine learning innovations stand out in a crowded field. 🔗 To the full blog: https://ow.ly/M6Th50Qi5iM #MachineLearning #PatentInnovation #StrategicPatenting #PatentTips
Harrity & Harrity, LLP’s Post
More Relevant Posts
-
Join Neil Chapman and Rachael McNaughton today at #GIRO where they will discuss new techniques and enhancements within machine learning and practical guidance on how they can be implemented as part of streamlined pricing processes. #WTW #ICT #technology #machinelearning
To view or add a comment, sign in
-
-
Join us for a series of insightful webinars that will empower you with the knowledge and tools you need to navigate the world of Intellectual Property and Patents. Do not miss out on our upcoming November sessions! November Webinars: 1. Machine Learning and Artificial Intelligence (date: 10 November 2023). 2. IP in Space Tech, Territorial Rights in an Extra-Terrestrial World (date: 24 November 2023). These sessions are packed with valuable information. Mark your calendars, and sign up for the webinars here: https://lnkd.in/eNgMh2E9 #IntellectualProperty #Patents #Webinar
To view or add a comment, sign in
-
-
🚀 Enhancing Your ML Patent Application 🚀 Maximize the impact of your machine learning patent application with two key strategies: → Unique Inputs: Leverage unconventional data inputs to create new predictive insights. For instance, an ML model that predicts consumer behavior from commute times can enhance patentability. → Outputs and Actions: Focus on how ML model outputs dictate real-world actions. A navigation system adjusting routes based on model confidence introduces novel functionality. Incorporate these strategies into your patent claims to strengthen your application against prior art and boost non-obviousness. With expert guidance, ensure your ML innovation stands out in the competitive patent landscape. https://lnkd.in/eSiS_jcv #MachineLearning #PatentStrategy #Patents
To view or add a comment, sign in
-
LVMs are domain-specific foundational models that are trained using your proprietary large dataset of images. Use them to gain intelligence from your unlabeled images to enable faster development for downstream computer vision tasks. https://bit.ly/3Dq6r8o #ComputerVision #QualityControl #Manufacturing
Homepage
https://landing.ai
To view or add a comment, sign in
-
Senior Project Manager|Infosys|B.E(Hons) BITS, Pilani & PGD in ML & AI at IIITB & Master of Science in ML & AI at LJMU, UK | (Building AI for World & Create AICX)(Learn, Unlearn, Relearn)
This Machine Learning Research Introduces Premier-TACO: A Robust and Highly Generalizable Representation Pretraining Framework for Few-Shot Policy Learning Quick read: https://lnkd.in/gRxhDgf5 Paper: arxiv.org/abs/2402.06187 #ArtificialIntelligence #DataScience #computerscience
To view or add a comment, sign in
-
-
Safeguard your schools with advanced vision analytics from #HPE and NVIDIA! 🦺 Check out this solution brief to discover how you can unlock the edge computing power needed for automated AI and advanced vision analytics. To learn more, contact Abrahams Consulting LLC.
Safeguard Your School with Advanced Vision Analytics
abrahams73.lll-ll.com
To view or add a comment, sign in
-
Safeguard your schools with advanced vision analytics from #HPE and NVIDIA! 🦺 Check out this solution brief to discover how you can unlock the edge computing power needed for automated AI and advanced vision analytics. To learn more, contact Abrahams Consulting LLC.
Safeguard Your School with Advanced Vision Analytics
abrahams73.lll-ll.com
To view or add a comment, sign in
Associate @ Morgan Lewis
8moGreat content, thanks for sharing! To the second point, those structural limitations (e.g., 50% confident this, 75% confident do that) can be a great differentiators, and prevent being rejected by "throwaway statements" in the prior art referencing possibilities that were likely obscure or peripheral to the reference anyway.