2019 Report on Advancements in AI on Edge - Challenges, Participants and Highlights of the Market - ResearchAndMarkets.com

DUBLIN--()--The "Advancements in AI on Edge - Emerging Applications and Innovations" report has been added to ResearchAndMarkets.com's offering.

This research provides the following:

  • A brief snapshot of convergence of edge computing with AI
  • The challenges of existing cloud AI models and how edge can solve
  • Key participants delivering intelligent edge AI solutions for different industries
  • Highlights of innovative future applications through convergence models
  • Roadmap and key milestones to achieve in the near, medium and long term to make devices, machines and things more intelligent.

Traditional cloud computing models send data from the device to the cloud for data analysis and the decision is sent back to the device for implementation. The agility of cloud computing is great but not enough to overcome certain challenges such as latency, bandwidth, processing the data for real-time decision making, costs associated with data transfer between cloud and edge.

Cloud AI models often needed to be trained with data collected from devices, making it difficult and time-consuming to apply AI and generate insights. AI with edge computing will solve the challenges faced in the cloud, as the inference and training are totally moved towards the devices.

Companies to Watch

  • Google
  • Gorilla Technology
  • Horizon Robotics
  • IBM
  • Imagimob
  • Intel
  • LGN.ai
  • NVIDIA
  • Qualcomm
  • Xnor.ai

Key Topics Covered:

1. Executive Summary

1.1 Research Scope

1.2 Research Methodology

1.3 Research Methodology Explained

1.4 Key Findings

2. Introduction to Edge AI

2.1 Overview of AI on Edge

2.2 Benefits of AI at the Edge

2.3 Distributed AI Improves Operational Timeliness and Reduces Privacy Risks

2.4 Specific Example: Distributed AI at the Edge

3. AI on Edge Market Overview

3.1 Rapid Migration of AI Inference Workloads to the Edge is Driving the Edge AI Chipsets Market

3.2 AI on Edge helps to Overcome the Challenges Associated with Cloud Computing

4. Areas of Edge AI Implementation

4.1 The Transformative Impact of Edge AI Cuts down Latency across Domains, Helping Companies take Faster Decisions

4.2 Automotive Participants are Making Efforts to Unlock Higher Levels of Autonomy using Edge AI Technology

4.3 With the Advent of Edge AI, Brick and Mortar Stores Now have Advanced Tools to Stay Ahead against Online Shopping

4.4 Edge AI in Supply Chains is Being Utilized to Predict Consumer Demand and Reduce Inventory Costs

4.5 Case Example 1: Edge AI-based Analytics for Business Management

4.6 Case Example 2: Edge AI-based Analytics for Predictive Maintenance

5. Companies to Watch: List of Companies Offering Edge AI Technology

6. Partnerships and Collaboration

6.1 Participants in the Ecosystem are Partnering to Accelerate the Adoption of AI on the Edge

6.2 Venture Capitalists are Investing Aggressively in Promising start-ups Offering AI capabilities at the Edge

7. Future Roadmap

7.1 Will Edge Computing Replace Cloud: Business Perspective

7.2 Edge Computing is a Promising Solution to Support Computation-intensive AI Applications in Resource-Constrained Environments

8. Industry Contacts

8.1 Key Contacts

8.2 Legal Disclaimer

For more information about this report visit https://www.researchandmarkets.com/r/je6sss

Contacts

ResearchAndMarkets.com
Laura Wood, Senior Press Manager
press@researchandmarkets.com

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Contacts

ResearchAndMarkets.com
Laura Wood, Senior Press Manager
press@researchandmarkets.com

For E.S.T Office Hours Call 1-917-300-0470
For U.S./CAN Toll Free Call 1-800-526-8630
For GMT Office Hours Call +353-1-416-8900