AIMMO Aims to Re-Set Autonomous Vehicle Development with Data Breakthrough

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  • AIMMO’s Autonomous Driving Data-as-a-Service (ADaaS) drastically reduces AV development cost and time by providing high-fidelity results from minimal datasets
  • New but proven approach drastically reduces algorithm training data needs through AIMMO’s approach to scenario and domain definition, highly targeted data collection and synthetic data augmentation provided as an integrated service
  • Approach offers one-stop data operations for autonomous vehicle companies to fast-track AV deployment and commercialisation

05 January 2022, Las Vegas, Nevada. AIMMO, a global leader in data operations powering the automation of smart cities, industry 4.0, robotics, defense and security today launched a breakthrough new service to transform the speed and cost of autonomous vehicle development.

At the CES Show in Las Vegas, AIMMO presented the world’s first end-to-end data operations service – ADaaS, or Autonomous Driving  Data-as-a-Service – and explained how the technology has been designed to overcome the industry-wide problem of excessive data collection that has constrained the progression and commercialization of AV technologies.

The use-case complexity of autonomous vehicles, or AVs, has seen the industry use large volumes of data to train self-driving algorithms; however, this approach demands significant data collection which in turn reduces data quality and thus the overall time and efficiency of data operations.  AIMMO’s ADaaS approach to solving  this problem is distinctly different and marks a paradigm shift; ADaaS focuses on automotive standards of definition, high-quality baseline (or ground-truth data) and AI-powered synthetic augmentation. This ‘data-centric’ approach based on quality and accuracy exponentially reduces time and the associated cost of the most significant bottleneck in AV development – the training of self-driving algorithms.

Moreover, AIMMO’s ADaaS service provides all of these gains for customers in a single, integrated, end-to-end workflow.

With the potential to exponentially reduce the time and cost of DataOps, while significantly enhancing data accuracy, the toolset offers customers the potential to leapfrog the competition to accelerate their AV deployment to commercial viability.

AIMMO has prioritised wholesale changes to the DataOps process in the automotive and mobility sector as it is a leading vertical undergoing rapid and significant transformation. As a consequence, AIMMO has invested extensively in sector-leading expertise from the AV and automotive domains with personnel experienced in complementary disciplines from Operational Design Domains (ODD) to Functional Safety as well as Machine Learning. The Korean-headquartered company, with offices in Europe and the US, works across the global automotive supply chain with vehicle manufacturers, tier suppliers and new autonomous vehicle developers.

SeungTaek Oh, Founder and CEO of AIMMO, said, “Over the years, we have seen a huge amount of anticipation around when we will see autonomous vehicles commercialized but with standards and regulations ever-changing across the world, it is an extremely complex market to navigate. However, we believe that the arrival of AIMMO ADaaS is a game-changer for many companies operating in this space. With the roll-out of our new service, we hope to make a valuable contribution to the progression of the market.

AIMMO welcome visitors and enquiries at their CES stand 9641.

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AIMMO keeps customer AI solutions on mission by removing the challenges of data operations for sectors including: smart cities, industry 4.0, robotics, e-commerce, text detection,  autonomous vehicles, optical character recognition software, and  defense, surveillance & security applications. Our proprietary deep-learning assisted data services vastly reduce manual operations to provide speed and accuracy across data collection, curation, labeling and inspection. With breakthrough approaches to the supply of structured datasets, AIMMO provides quality, warranted 99.9% accuracy and speed for machine learning operations.

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