PTAB

IPR2013-00304

Oracle Corp v. Clouding IP LLC

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Key Events
Petition
petition

1. Case Identification

2. Patent Overview

  • Title: System and Method for Automatically Maintaining a Computer System
  • Brief Description: The ’839 patent relates to a system for the automated maintenance of a computer system. The disclosed technology utilizes a set of sensors to monitor system operations and an artificial intelligence (AI) engine, which leverages a knowledge database of "cases," to diagnose detected problems and determine appropriate solutions.

3. Grounds for Unpatentability

This petition, a second filing against the ’839 patent, was submitted to address a deficiency noted by the Board in a prior proceeding (IPR2013-00095). The central argument across both grounds is that adding the teachings of the Allen ’664 patent remedies the prior art's failure to explicitly teach the key claim limitation of saving a new case when a likely solution cannot be determined.

Ground 1: Claims 1-2, 6, 8, 14-15, and 17 are obvious over Gürer in view of Allen ’664.

  • Prior Art Relied Upon: Gürer (a 1996 publication titled "An Artificial Intelligence Approach to Network Fault Management") and Allen ’664 (Patent 5,581,664).
  • Core Argument for this Ground:
    • Prior Art Mapping: Petitioner argued that Gürer disclosed a case-based reasoning (CBR) system for network fault management that met most limitations of the challenged claims. Gürer’s system used "alarms" (sensors) to detect problems and an AI engine with a "case library" (knowledge database) to diagnose faults and propose corrective actions. However, Petitioner acknowledged that Gürer only suggested that unsuccessful correction steps would be “remembered and noted,” falling short of explicitly teaching the critical limitation of saving the gathered data as a new case when no solution is found. To supply this missing element, Petitioner relied on Allen ’664, which expressly taught an inference engine that adds new cases to its case base when it determines there is no good match for a current problem template.
    • Motivation to Combine: A POSITA would combine these references to improve the learning capability of the Gürer system. Incorporating the explicit teaching from Allen ’664 would allow Gürer’s AI engine to learn from unsolved problems, a well-known and substantial advantage for improving the robustness of AI systems. Petitioner asserted that this type of iterative improvement was routine and commonplace in the field of AI.
    • Expectation of Success: A POSITA would have had a high expectation of success in combining the references. Both Gürer and Allen ’664 operated within the predictable field of case-based reasoning, and integrating a known method for handling unsolved cases into Gürer’s diagnostic framework was a straightforward application of established AI principles.

Ground 2: Claims 1-2, 6, 8, 14-15, and 17 are obvious over Allen ’218 in view of Allen ’664.

  • Prior Art Relied Upon: Allen ’218 (Patent 5,586,218) and Allen ’664 (Patent 5,581,664).
  • Core Argument for this Ground:
    • Prior Art Mapping: Petitioner asserted that Allen ’218 disclosed an autonomous software agent using a CBR system that performed many of the claimed steps. The agent in Allen ’218 used a "reward message" to measure its success in responding to a problem and could generate "new cases" to add to its case base. Petitioner argued that while Allen ’218 suggested a new case would be created upon failure (i.e., a negative reward message), it did not explicitly state this. As in the first ground, Allen ’664 was used to supply the express teaching of creating a new case when no good match or likely solution is found in the existing case database.
    • Motivation to Combine: A POSITA would be motivated to combine the explicit teachings of Allen ’664 with the autonomous agent of Allen ’218 to create a more effective and predictable learning system. Petitioner emphasized that this combination was particularly obvious because both the Allen ’218 and Allen ’664 patents were from the same patent family and related to the same type of autonomous learning and reasoning agents, making their teachings readily combinable.
    • Expectation of Success: The combination was presented as a predictable integration of complementary teachings within the same technical field. A POSITA would have reasonably expected to successfully modify the Allen ’218 system with the specific case-creation logic from Allen ’664 to enhance its learning capabilities.

4. Key Claim Construction Positions

  • Petitioner adopted the claim constructions set forth by the Board in its decision to institute trial in the related, prior proceeding (IPR2013-00095) for the following key terms:
    • "Sensors": Construed as "software programs that gather information from a computer system."
    • "Artificial Intelligence (AI) Engine": Construed as "a computer program used for decision making or problem solving, based on reasoning or inferences."

5. Relief Requested

  • Petitioner requests institution of an inter partes review and cancellation of claims 1-2, 6, 8, 14-15, and 17 of Patent 5,944,839 as unpatentable.