AU2020102743A4 - Method and a system for artificial intelligence platform which enables it operations to deliver quality, seamless and reliable digital experience - Google Patents

Method and a system for artificial intelligence platform which enables it operations to deliver quality, seamless and reliable digital experience Download PDF

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Publication number
AU2020102743A4
AU2020102743A4 AU2020102743A AU2020102743A AU2020102743A4 AU 2020102743 A4 AU2020102743 A4 AU 2020102743A4 AU 2020102743 A AU2020102743 A AU 2020102743A AU 2020102743 A AU2020102743 A AU 2020102743A AU 2020102743 A4 AU2020102743 A4 AU 2020102743A4
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enterprises
models
data
built
enables
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AU2020102743A
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Brajendra Gouda
Prem Naraindas
Pandi Thurai
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Katonic Pty Ltd
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Katonic Pty Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3003—Monitoring arrangements specially adapted to the computing system or computing system component being monitored
    • G06F11/3006—Monitoring arrangements specially adapted to the computing system or computing system component being monitored where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Medical Informatics (AREA)
  • Evolutionary Computation (AREA)
  • Data Mining & Analysis (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Quality & Reliability (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

: Disclosed are a method and a system for artificial intelligence platform which enables IT Operations to deliver Quality, Seamless and Reliable digital experience. The system comes with pre-built Al models for use cases across the IT service management spanning the life cycle of IT applications. The system has the ability to connect and ingest data from a wide range of IT applications. The system can automatically train the pre-built Al models for the enterprise data and choose the right algorithm. The system provides a neural architecture search (NAS) feature which enables design artificial neural network, with a goal of maximizing the predictive accuracy and performance of the Al models. -li-t AOR FATSM AllNA -0 a: DA E W ol~liioces I ~AWS La~L #Iiro Mote oat kafa sak QFlak MSnge

Description

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Editorial Note 2020102743 There is only one page of the description
Description
In order to drive digital transformation, enterprises are rapidly evolving their IT stack to become more agile, scalable and cost-effective. They are adopting new tools and platforms, such as public cloud, microservices, containers, and serverless technologies. Enterprises are also adopting DevOps and CI/CD practices to allow them to move faster. At the same time, enterprises continue to retain many of their legacy and homegrown technologies that are accumulated over many decades.
Unfortunately, for most enterprises, these changes have dramatically increased the scale, fragmentation and complexity of their IT stack. The results have been disastrous for enterprises in terms of high costs, poor performance, and risk to new digital initiatives. In response, IT teams are growing in size and using more monitoring tools. But timely outage detection, investigation and resolution remain a significant challenge. Use of Al in IT operations has been driven by the adoption of digital transformation, but the majority of the current solutions are focused on one domain (for example, network, endpoint systems or APM) and have restricted set of use cases. Most of these solutions are focused on IT Monitoring and are limited to "alert suppressing" or "incident management".
Embodiments of the present invention address these and/or other needs by providing an innovative domain agnostic Al platform which enables IT Operations to deliver Quality, Seamless and Reliable digital experience. This platform will allow enterprises to use Al across the IT service management to help enterprises manage risk, strengthen customer relations, establish cost-effective practices, and build a stable IT environment that allows for growth, scale and change. Embodiments of the present invention will provide enterprises open and Integrated Platform Built using proven Al Methodologies allowing Data Scientists to build their own ML Models with unprecedented transparency, testability and control

Claims (9)

  1. Editorial Note 2020102743 There is only one page of the claim
    CLAIMS 1 Embodiments of the present invention address these and/or other needs by providing an innovative domain agnostic Al platform which enables IT Operations to deliver Quality, Seamless and Reliable digital experience.
  2. 2 The system of claim 1 will enable enterprises to use Al across the IT service management to help enterprises manage risk, strengthen customer relations, establish cost-effective practices, and build a stable IT environment that allows for growth, scale and change.
  3. 3 The system of claim 1 will provide enterprises Open and Integrated Platform allowing Data Scientists to build their own ML Models with unprecedented transparency, testability and control.
  4. 4 The system of claim 1 will reduce the reliance of enterprises on Data/ML Engineers and Data Scientist, as it comes packaged with a ready enterprise-grade Al and analytics platform with pre-built models. This means that enterprises can now focus on creating truly innovative applications that demonstrate the potential of Al and analytics and spend less time and resources on integration tasks that are required to experiment or build an Al application.
  5. 5 The system of claim 1 will provide pre-built connectors to connect to a t wide range of IT applications quickly while being responsive to changes happening at the underlying data sources. The connectors will feed data from various data such as IT Service Management (ITSM), Application Performance Management (APM), IT Information Management (ITIM), Planning, and DevOps.
  6. 6 The system of Claim 1 provides a neural architecture search (NAS) feature which used to design artificial neural network, with a goal of maximizing the predictive accuracy and performance of the Al model.
  7. 7 The system of Claim 1 can automatically train the pre-built Al models for the enterprise data and choose the right algorithm.
  8. 8 The system of claim 1 will enable enterprises to Deploy models and APIs from a Jupyter notebook or IDE to production in just a few clicks and continuously monitor model performance.
  9. 9 The system of claim 1 will allow enterprises to deploy the machine learning applications seamlessly and naturally to the cloud, multi-cloud, on-premises, edge, or anywhere your business lives.
    Editorial Note 2020102743 There is only one page of the drawing
AU2020102743A 2020-10-15 2020-10-15 Method and a system for artificial intelligence platform which enables it operations to deliver quality, seamless and reliable digital experience Ceased AU2020102743A4 (en)

Priority Applications (1)

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AU2020102743A AU2020102743A4 (en) 2020-10-15 2020-10-15 Method and a system for artificial intelligence platform which enables it operations to deliver quality, seamless and reliable digital experience

Applications Claiming Priority (1)

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AU2020102743A AU2020102743A4 (en) 2020-10-15 2020-10-15 Method and a system for artificial intelligence platform which enables it operations to deliver quality, seamless and reliable digital experience

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AU2020102743A4 true AU2020102743A4 (en) 2020-12-03

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112381215A (en) * 2020-12-17 2021-02-19 之江实验室 Self-adaptive search space generation method and device for automatic machine learning
CN113176947A (en) * 2021-05-08 2021-07-27 武汉理工大学 Dynamic task placement method based on delay and cost balance in serverless computing

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112381215A (en) * 2020-12-17 2021-02-19 之江实验室 Self-adaptive search space generation method and device for automatic machine learning
CN112381215B (en) * 2020-12-17 2023-08-11 之江实验室 Self-adaptive search space generation method and device oriented to automatic machine learning
CN113176947A (en) * 2021-05-08 2021-07-27 武汉理工大学 Dynamic task placement method based on delay and cost balance in serverless computing
CN113176947B (en) * 2021-05-08 2024-05-24 武汉理工大学 Dynamic task placement method based on delay and cost balance in server-free calculation

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