Global Artificial Intelligence/Machine Learning Platforms Growth Opportunities

reogma|Global Artificial Intelligence/Machine Learning Platforms Growth Opportunities

AI has already shown to be a major game-changer in the approaching digital world which can alter the face of the industry as it could significantly leverage the outputs generated across all sectors such as BFSI, Retail and eCommerce, IT and Telecommunication, Healthcare, Automotive and Industrial Automation and could generate interesting equations in terms of revenue generation and offer significant turnaround in terms of growth.

Surging investments to leverage the AI technology and Cloud Computing & Big Data offer lucrative opportunities to the Market Players.

  • Definition / Scope
  • Market Overview
  • Top Market Opportunities
  • Market Risks
  • Market Drivers
  • Market Restraints
  • Industry Challenges
  • Technology Trends
  • Pricing Trends
  • Post COVID-19 Recovery
  • Market Size and Forecast
  • Market Outlook
  • Technology Roadmap
  • Competitive Landscape
  • Competitive Factors
  • Key Market Players
  • Strategic Conclusion
  • References
  • Further Reading
  • Appendix

Definition / Scope

An AI Platform is a framework that is supposed to work faster and smarter than traditional frameworks. It enables enterprises to collaborate with Data Scientists and personnel in a faster, more efficient, and effective manner. It can assist cut expenses in a variety of ways, including avoiding duplication of labor, automating simple procedures, and eliminating some high-cost activities like data copying and extraction. An AI Platform may also provide Data Governance, ensuring that a team of AI scientists and ML programmers follows best practices. It can also help to ensure that work is divided more equitably and completed faster.

An Artificial Intelligence Platform generally has its elements organized into five layers of logic:

  1. The Data and Integration Layer provides access to the data.
  2. The Experimentation Layer allows Data Scientists to develop, test, and prove a hypothesis.
  3. The Operations and Deployment Layer provides model governance and deployment.
  4. The Intelligence Layer supports the AI when it’s working (training activities take place in the Experimentation Layer).
  5. The Experience Layer interacts with users through technologies such as augmented reality, conversational UI, and gesture control.

reogma|Global Artificial Intelligence/Machine Learning Platforms Growth Opportunities


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AI has already shown to be a major game-changer in the approaching digital world which can alter the face of the industry as it could significantly leverage the outputs generated across all sectors such as BFSI, Retail and eCommerce, IT and Telecommunication, Healthcare, Automotive and Industrial Automation and could generate […]
reogma|Global Artificial Intelligence/Machine Learning Platforms Growth Opportunitiesreogma|Global Artificial Intelligence/Machine Learning Platforms Growth Opportunities

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