Building Chipset Differentiation with AI Optimization across the Distributed Compute Continuum

Price: Starting at USD 1,950
Publish Date: 18 Apr 2024
Code: AN-6140
Research Type: Research Report
Pages: 12
Building Chipset Differentiation with AI Optimization across the Distributed Compute Continuum
RELATED SERVICE: AI & Machine Learning
Actionable Benefits

Actionable Benefits

  • Understand competitor approaches to Artificial Intelligence (AI) optimization.
  • Develop understanding of market opportunity across cloud, edge, and device with Total Addressable Market (TAM) assessment.
  • Explore opportunities to develop software proposition and build developer engagement.
Critical Questions Answered

Critical Questions Answered

  • How quickly will AI optimization revenue grow across the cloud, edge, and device?
  • Which chip vendors have built leading AI optimization solutions?
  • Which emerging areas should chip vendors invest in to build their developer value proposition?
  • Should chip vendors partner or acquire to build their software ecosystem?
Research Highlights

Research Highlights

  • Analysis of chipset vendor software strategies across distributed compute continuum.
  • Overview of key players in market and strategic approach to optimization.
  • Examination of key trends and recommendations about what to focus on.
Who Should Read This?

Who Should Read This?

  • AI chip industry strategists across mature incumbents and new entrants looking to build developer engagement.
  • Software ecosystem executives evaluating partnerships with chip vendors.
  • Chip vendor software leaders looking to redefine product and commercial strategies.

Table of Contents

Key Findings

Key Forecasts

Key Companies and Ecosystems


Comparing Approaches across the Cloud, Edge, and Device

Expanding Chipset Developer Value Proposition

Technical and Commercial Opportunities to Explore
On-Device Commercialization Opportunity Requires SDKs

Partnerships, Integration, and Acquisition Can Support Chipset Differentiation