Osha Attorneys
Osha Attorneys
Osha Attorneys
Osha Attorneys
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The collective expertise of our global team distinguishes OBWB in the field of Intellectual Property Law. We align our best resources to meet each client's specific needs and we treat each matter with the highest degree of attention and care.

Big Data, Machine Learning, & IoT

Today’s world is data-driven. Big Data is dynamic and powerful; voluminous amounts of data of all types and formats are being stored and analyzed.  Machine Learning (ML) algorithms and neural networks allowing machines to not only analyze that data but also to learn, improve from experience, and predict outcomes are becoming more sophisticated.  Everyday objects are becoming learning machines, and the Internet of Things (IoT) facilitates communications between those objects.  This technology creates numerous and complex IP issues ranging from rights arising in the creation of the algorithms and machines to possible rights in IP created by the machines themselves.  Due diligence in formulating patent portfolios and strategies, and infringement, validity, and freedom to operate opinions should be considered when developing a comprehensive business plan.   Data protection and privacy, and information that may be viable and valuable trade secrets also are important considerations.  

Many of OBWB’s lawyers, patent agents, and engineers have advanced degrees and experience in computer engineering, electrical engineering, and computer science.  We help our clients to understand how and when to seek IP protection, when certain aspects of the business may be covered by trade secrets, and how to maintain a strong IP portfolio.  Much of this Big Data industry is new and may force changes in certain areas of IP law, creating conflicts and disputes between industry competitors that are unseen.  We help clients resolve disputes through licensing, dispute resolution, and aggressive litigation when warranted.

Specific areas of our expertise in this industry include:

  • Data Protection
  • Protection of Architecture
  • Protection of Classification Systems
  • Protection of Training Set Generation
  • Protection of the ML System
  • Protection of Software Implementing ML Functionality
  • Protection of Training and Model Parameters
  • Anti-competitive Behavior in the ML Context
  • Watermarking in the ML Context