A More Cost-Effective Way to Develop an AI/ML Program
Automotive and device OEMs face challenges associated with the cost and latency of cloud processing. MicroAI™ brings AI-enabled telematics to the edge.
Smart Automotive
24263
post-template-default,single,single-post,postid-24263,single-format-standard,bridge-core-1.0.4,translatepress-en_US,bridge,mega-menu-top-navigation,ajax_fade,page_not_loaded,,qode_grid_1300,qode-content-sidebar-responsive,qode-theme-ver-18.0.6,qode-theme-onetech,disabled_footer_top,wpb-js-composer js-comp-ver-5.7,vc_responsive
 

Using MicroAI Launchpad™ to Develop and Deploy AI Solutions

14 Jan 22

Using MicroAI Launchpad™ to Develop and Deploy AI Solutions

The deployment of artificial intelligence (AI) and machine learning (ML) solutions are accelerating across many industry verticals (automotive, energy, manufacturing etc.). That acceleration is being fueled, in part, by the development of new Edge AI solutions that embed intelligence and control directly onto the targeted device or machine. These solutions provide developers with increased flexibility in design of new AI solutions; however, development time, risk and cost can still be prohibitive factors.

 

The Problem

Developers are often tasked with fulfillment of AI initiatives within time frames that have been compressed due to business and/or operational imperatives. These challenges are too often exacerbated by the lack of a comprehensive, developer-friendly, platform that provides all necessary elements to design, test, integrate, and launch an AI initiative.

Typical complaints from the developer community and key business stakeholders would include:

 

Developers

  • Too much time is spent searching for AI and ML libraries that meet the requirements of an Edge-native AI solution.
  • SDK uploading/onboarding process is often cumbersome and error prone.
  • Limited ability to test and iterate designs within a self-contained, real-time, environment.
  • Cumbersome integration with external system components negatively effects ecosystem integrity.
  • All the above add time, complexity, cost and risk to the design and deployment process.

 

Business Stakeholders

  • Difficult to estimate program costs and maintain budgetary control.
  • The piecemeal design approach inhibits a consolidated managerial view of program status.
  • Program delays resulting from having to work within too many disconnected tools and applications.
  • All the above create poor stakeholder visibility, cost overruns, poor ROI, and loss of competitive momentum.

 

The Solution – MicroAI Launchpad™

In response to the needs of today’s AI development community MicroAI™ has developed MicroAI Launchpad, a self-contained AI development ecosystem that shortens development time, reduces cost, minimizes risk and provides a quicker time to market. Launchpad puts unparalleled capability and flexibility into the hands of the AI and ML developer. This new ecosystem provides developers with the means to:

  • Easily access MicroAI’s AL and ML libraries and download applicable SDKs
  • Develop solutions that leverage MCUs and MPUs embedded with Edge-native AI software
  • Test, visualize, and modify design concepts within a real-time environment
  • Seamlessly integrate with other system components or data sources
  • Conduct final testing and live training prior to launch

The Impact

The benefits provided by MicroAI Launchpad will impact the entire AI system development landscape. From developers to operational functions to business stakeholders, Launchpad will help take AI from the drawing board to functional reality.

  • Ease of design
  • Quicker design cycle
  • Enhanced reliability
  • Improved stakeholder visibility
  • Lower cost
  • Faster ROI
  • Competitive advantage