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Earlier this year, the EPO introduced new guidelines for examination relating to inventions concerning artificial intelligence (See G-II-3.3.1). The last paragraph of these guidelines suggest that applications to AI-related inventions may require specific disclosure surrounding any algorithms used by an AI invention, as well as any training data used to train the AI, where such training data is required to achieve the technical effect of the invention. 

A change in the Guidelines usually reflects a change in thinking or application of the law by the EPO. Indeed, it’s always interesting to see how such changes are actually implemented in practice.  

The recently issued decision T1669/21 of the EPO Board of Appeal provides useful insight into exactly what sorts of specific disclosure may be required to satisfy the sufficiency requirements for patent applications relating to AI inventions. 

The unprecedented scale of content generated by AI presents an interesting challenge, in terms of prior art, to established patent law practice. With AI capable of autonomously producing technical content, future patent applications may face an unprecedented wave of AI-generated prior art disclosures that could be relevant in the assessment of novelty and nonobviousness (or inventive step). This article explores how AI-generated content may reshape how we consider prior art, and what might need to be done, as we navigate a new era of innovation influenced by machine-generated insights.

Recent comparative testing reveals that Solve Intelligence's Patent Drafting Copilot consistently outperforms GPT-4o in European patent claim drafting. Here we explore the technical and practical limitations of using GPT-4o for drafting claims suitable for European practice, and how using Solve’s Patent Drafting Copilot can deliver substantial improvements.

The American Intellectual Property Law Association (AIPLA) has long been a leading force in advancing the practice of intellectual property law and is one of the most popular IP conferences. Numerous AI Patent Drafting Tools were present at AIPLA this year, showcasing a technological breakthrough that promises to reshape the way patent attorneys and intellectual property professionals work. As artificial intelligence (AI) finds applications in almost every industry, patent professionals are discovering how it can simplify the complexities of drafting patents and accelerate AI patent prosecution processes.

In this article, we explore how drafting patents with AI is transforming the field, the tools available to attorneys, the benefits of AI-powered drafting solutions, and what the future might hold for intellectual property law.

In artificial intelligence (AI) development, particularly in domains like generative AI (Gen AI), running structured evaluations - known as evals - is an incredibly useful tool. Evals test models and algorithms in development against real-world tasks to measure performance, detect errors, and improve reliability. In fields such as intellectual property (IP) law, these evals ensure that AI tools meet the high standards of accuracy and compliance required for professional use.

As artificial intelligence (AI) becomes more integrated into professional workflows, the need for transparency in AI-assisted tasks is increasingly important. One key area where this applies is the patent industry, where accuracy and traceability are critical. To support this, we are introducing a new feature: AI Track Changes, designed to provide clear insights into how AI-generated suggestions and edits are being made to your patent applications, Office action responses, and other patent documents.