Webinar: Can AI be leveraged for better, more actionable search results?

Given the economic realities, patent practitioners—both in-house and outside attorneys—are constantly being asked to do more within existing budgets. Meanwhile, more robust patent applications thick with technical detail are necessary to satisfy courts and patent offices around the world. Working within budgetary constraints without sacrificing quality requires the industry to think outside the box and use all available tools to streamline as much of the process as possible. This must start with more actionable search results, which allow professionals to focus on the unique innovative contributions, and to also conserve resources instead of chasing patents that likely won’t issue or couldn’t be defended against challenge.

Enter Artificial Intelligence (AI), which is taking the world by storm. Thanks to ChatGPT, it seems everyone is familiar with AI, and has an opinion as to what AI can and cannot do. But how do you use the power of AI in the innovation and patent space without compromising confidentiality? And how do you know whether what the AI finds is reliable and accurate?

It will be some time before AI search solutions can provide the end-all-be-all solution without human evaluation and input. But proprietary AI solutions can and do currently provide excellent breadth and coverage, and are playing a vital role in delivering more actionable search results that have a much higher level of reliability.

Join Gene Quinn, President and Founder of IPWatchdog, on Thursday, September 28, 2023, at 11 AM ET, for a conversation relating to best practices for using AI to achieve better search results. Joining Gene will be John Rogitz, Managing Attorney at Rogitz & Associates, Jim Burns, Senior Director, Business Development, RWS IP Services, and Costas Stephanides, Technical Manager, RWS IP Services.

Among other things, the panel will discuss:

• Using AI as a tool to ensure all search bases are covered.
• Fencing AI searches with a closed training set so the AI does not learn from any client search and technical data is not cross-pollinating other searches.
• Securing data with appropriate data security.
• How keeping a human in the loop ensures AI is appropriately leveraged and results are verified.