Monthly Archives: December 2023

In the intricate and often bewildering terrain of patent applications, achieving clarity is both an art and a science. This is particularly true for software or process-based inventions, where conveying complex ideas in a comprehensible manner is crucial. Neil Kardos offers his expert advice, sharing pivotal strategies to demystify these often perplexing documents. In this blog post, we’ll delve into two of Neil’s key tips, which promise to bring much-needed lucidity to your patent applications.

Tip #1: The Power of Descriptive Naming

Neil’s first tip revolves around the strategic use of descriptive names for devices in patent applications. This approach goes beyond mere labeling; it’s about creating an intuitive understanding of each device’s role. For example, naming a device that handles user verification as an “Authentication Device” instantly reveals its function. This practice ensures that every mention of the device within the document not only identifies it but also reminds the reader of its purpose, thus maintaining a clear focus on the invention’s core functionalities.

Tip #2: Artful Separation of Function and Form

In his second tip, Neil highlights the importance of distinguishing between what devices do and what they are. He recommends that the narrative in the “Invention Detail Figures” should concentrate on the devices’ roles in the invention’s process. For example, describing a user device transmitting credentials to an authentication device should be about this process, not about the possible physical forms of the user device. The comprehensive description of the devices’ physical forms and variations should be allocated to the “Device Environment Figure.” This methodical separation ensures the patent application remains streamlined and focused, facilitating a smoother reading experience.

By implementing these tips, inventors and patent drafters can significantly enhance the readability and clarity of their patent applications. Neil’s guidance is not just about simplifying content; it’s about structuring it in a way that guides the reader through the invention’s narrative with ease and understanding.

Don’t forget to come back for more tips in the next installment of the Practical Patents Series. Until next time, happy patenting!

The world of patent applications is intricate and demanding. Among the numerous challenges faced by inventors and patent practitioners, one that stands paramount is the art of drafting a clear and engaging patent specification. Neil Kardos offers profound insights into enhancing the readability of patent applications.

The heart of Neil’s advice lies in the organization of the patent specification. The traditional approach of hopping between figures can be disorienting, leading to confusion. Neil advocates for a more linear, structured approach. This entails starting with an introductory paragraph for each figure, detailing its contents thoroughly, and concluding with a summary. Such an approach doesn’t just enhance readability; it builds a narrative, making the invention’s journey through its various stages more comprehensible and compelling.

Neil delves into two scenarios frequently encountered in patent drafting:

1. Sequential Storytelling with Figures: Often, a series of figures (e.g., Figs. 1a to 1c) is used to unfold the invention step-by-step. Neil suggests employing a single introductory and concluding paragraph for the entire series. This technique ensures a seamless narrative flow, making the progression of the invention easier to follow and understand.
2. Balancing Overview and Detail: When one figure presents an overarching view (e.g., Fig. 1) and another dives into granular details (e.g., Fig. 2), Neil recommends a delicate balancing act. Mention Fig. 2 while discussing Fig. 1, but save the in-depth discussion for later. This approach keeps the reader anchored in the broader context before delving into specifics, thereby maintaining engagement and understanding.

Neil’s methodology extends beyond mere structural organization. It embraces the art of storytelling within the technical confines of patent law. By treating each figure not just as a visual representation but as a chapter in the story of the invention, the drafter can create a more immersive and understandable narrative. This approach resonates with examiners and potential licensees, making the invention not just a list of technical features but a compelling innovation journey.

In the realm of patents, clarity is not just about compliance; it’s about captivating the reader, be it an examiner, a judge, or a potential investor. By adopting these strategies, patent practitioners can transform their applications from mere technical documents to engaging narratives that effectively communicate the essence of their inventions.

In the realm of patent applications, the art of storytelling is often overshadowed by the complexity of technical details. However, Neil Kardos brings a refreshing approach to structuring patent applications, emphasizing not just the technicalities but the story of the invention itself. His method improves readability and enhances the experience for inventors and in-house counsel alike.

1. Setting the Stage with Background
Neil begins by advising the inclusion of a background section. This part introduces the technology behind the invention. Depending on the familiarity and complexity of the technology, this section can vary in length. For well-known concepts, a few sentences suffice, but for more intricate technologies, a detailed exposition might be necessary.

2. Identifying the Technical Problem
Following the background, Neil emphasizes the importance of clearly outlining the technical problem addressed by the invention. This step is crucial as it sets the stage for the solution and helps the reader understand the necessity of the invention.

3. Introducing the Technical Solution
Next, a high-level explanation of the technical solution is presented. This part showcases how the invention solves the identified problem. It’s a strategic move to keep this explanation at a high level, ensuring clarity and engagement.

4. Highlighting the Technical Benefits
Neil suggests elucidating the technical benefits of the invention. This section reinforces the value of the invention and its contribution to the field.

5. Diving into the Details
The fifth part of the structure delves into the specifics of the invention, including various options, alternatives, and detailed benefits. This comprehensive exploration allows for a deeper understanding of the invention’s potential.

6. Standardized Figures and Descriptions
Finally, standardized figures and descriptive language, particularly important for hardware supporting process-based inventions, are placed towards the end of the application. Neil’s rationale for this arrangement is to captivate the reader’s interest with the most significant elements upfront, avoiding boredom or confusion.

Neil’s recommended structure is not just about organizing content; it’s about crafting a narrative that makes patent applications more accessible and engaging. By following this structure, patent professionals can effectively communicate the essence of an invention, making the complex world of patents a bit more approachable and relatable.

In the ever-evolving domain of machine learning, securing patents for novel inventions is a complex challenge. Neil Kardos shares his expert strategies in this week’s Practical Patents series. His focus is on the intricacies of drafting machine learning patent applications that stand out, avoiding the common trap of obviousness.

Neil stresses the significance of meticulously detailing machine learning patents. Building on the insights shared in last week’s blog post, which highlighted the importance of delineating the inputs to the model, the outputs generated, and the resultant actions, he now introduces three advanced strategies to further distance machine learning models from the risk of being deemed obvious.

Strategy 1: Novel Inputs

Neil’s first strategy centers on the unique choice of inputs in machine learning models. He advocates for leveraging unconventional inputs with significant predictive power to strengthen the non-obviousness of a patent application. For example, he cites the intriguing correlation between an individual’s time spent in a car and their smartphone purchasing preferences as a potential differentiator in a patent application.

Strategy 2: Diverse Outputs and Actions

The second strategy Neil suggests relates to the outputs of the models and the corresponding actions. He points out that beyond the typical binary actions, incorporating a range of responses based on different levels of probability can impart a unique edge to a patent. This could involve varying marketing tactics depending on the predicted likelihood of a customer making a purchase.

Strategy 3: Continual Model Refinement

Neil’s final strategy emphasizes the ongoing improvement and adaptation of machine learning models, especially through feedback mechanisms for re-training. Such adaptive features are often viewed positively by patent examiners and can be crucial in either the independent or dependent claims of a patent application.

Neil offers these strategies as a guide for those seeking to navigate the intricate world of machine learning patents. His insights shed light on effective approaches to elevate machine learning patent applications above the standard threshold of obviousness.

In the dynamic and ever-changing world of machine learning (ML), creating a standout patent application is akin to solving a complex puzzle. It’s a landscape where innovation meets the challenge of differentiation. Neil Kardos offers insightful strategies to navigate this complexity, ensuring your ML patents are not just innovative but distinctively non-obvious.