Fast-growing digital native companies are balancing a complex set of challenges. The need to optimise cost structures and accelerate revenue growth remains critical in an environment where funding rounds are starting to tighten.
Leveraging automation and accelerating the pace of innovation to create a clear path to profitability is key. Increasingly, digital natives are looking to deliver insights at scale and automate routine tasks to make the best use of their resources.
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Only 1% of a company’s data is actually used by its applications. One of the main reasons for this is the difficulty of finding and providing the relevant information from the masses of unstructured and structured data residing in most enterprises.
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AI in manufacturing is a hot topic around the industry, with multiple potential use cases, vendors, and methodologies.
The challenge for manufacturers is that the path from concept to deployment to ROI is very resource- and time-consuming. And in many cases, the ROI is never actually achieved.
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We will provide an overview of the requirements for patenting AI/machine learning (ML) inventions in Europe.
The discussion will review the European Patent Office’s (EPO’s) guidelines, provide an overview of recent EPO case law related to AI/ML, and cover the EPO’s requirements for technical effects and enablement as they apply to AI/ML inventions.
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