{"id":21769,"date":"2022-02-14T01:23:00","date_gmt":"2022-02-14T01:23:00","guid":{"rendered":"https:\/\/sagaciousresearch.com\/blog\/?p=21769"},"modified":"2023-03-29T03:57:36","modified_gmt":"2023-03-29T03:57:36","slug":"software-machine-learning-patents-key-differences-best-practices-for-patent-drafting","status":"publish","type":"post","link":"https:\/\/sagaciousresearch.com\/blog\/software-machine-learning-patents-key-differences-best-practices-for-patent-drafting","title":{"rendered":"Software & Machine Learning Patents \u2013 Key Differences & Best Practices for Patent Drafting"},"content":{"rendered":"\n

Artificial Intelligence (AI) and its techniques such as Machine Learning (ML) and Fuzzy Logic have become an intrinsic part of our daily lives. Right from how Google Maps are being used for traffic speed prediction, the way Dynamic Pricing supports ride-sharing apps such as Uber and Lyft, and how Autopilot feature on flights controls the aircraft – advanced machine learning algorithms are thus changing how we travel, shop, and interact with each other.<\/p>\n\n\n\n

We can gauge the popularity of machine learning from the fact that 150,637<\/a> patent families concerned with AI techniques have been published until 2018. This makes machine learning the dominant technique (89% of total AI patents) that has been witnessing a rapid rise over the years. For inventors seeking a patent in this domain, it is imperative to understand the difference between software and machine learning at a fundamental level.  <\/p>\n\n\n\n

This article will discuss the main differences in filing a patent for software and machine learning and the challenges faced by the applicants. But first, let us understand the difference between software and machine learning, and then analyze the difference in patent filings and grants. <\/p>\n\n\n\n

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