Akridata ™ Launches World’s First Edge Data Platform for Data-Centric AI
Decentralized software accelerates access to relevant AI data, manages the ingestion, cataloging and mining of complex AI data, and enables traceability of AI across industries
– Advanced AI and autonomy depend on curating and filtering massive amounts of data generated at the edge to fuel continuous deep learning. This is an Exascale class data challenge.
– Akridata created the industry’s only Edge data platform for data-centric AI, a new IT category that focuses on the structure and quality of AI data versus repetitive refinement of AI models. Complex AI. Akridata provides a decentralized software layer that enables data-centric AI through intelligent data pipelines, automated workflows, on-demand access, and rapid data mining.
– The Akridata platform is available today and has proven to deliver ten times faster access time to the right data, four times the efficient use of compute and storage, and twice the productivity for business users. data scientists and machine learning engineers.
– Toyota Motor Company North America is a customer base of Akridata, along with other global industrial partners.
SILICON VALLEY, California, October 5, 2021 / PRNewswire / – Category builder and data-centric AI pioneer Akridata today announced the launch of Akridata Edge Data Platform ™, which builds and manages intelligent data pipelines and workflows for AI spanning Edge-Core-Cloud resources – an industry first. Akridata software solves problems that arise when rich data streams from physically dispersed Edge devices create an avalanche of data that cannot be organized, filtered, accessed, and processed. It’s now common for organizations to collect tens of terabytes of data per day from a single stand-alone device.
With the first AI infrastructure platform in the Data-centric AI category, Akridata provides a decentralized structure and scalable process to deliver organized, cohesive, and relevant AI datasets. Akridata was created in 2018 for solve the AI data problem. Solving this Exascale class problem is a requirement for moving AI from experimentation to production in the real world. From automobiles to transportation, retail and healthcare, this need is a major barrier preventing AI-enabled products from reaching the market.
“The diverse requirements of ADAS / AV (Advanced Driver Assistance Systems / Autonomous Vehicle) require many elements, including deep learning, cloud deployment and in-vehicle services, among others. What ties it all together is data and a huge data challenge, ”said Kishore Jonnalagedda, Director of Engineering, Toyota Motor Company North America. “Akridata brings us a complete and innovative solution that improves efficiency, reduces costs and accelerates our team’s work towards our goals. We will immediately gain influence by automating data pipelines from edge locations to the cloud, enabling our data science and product development teams to focus on what matters most: delivering the best ADAS / AV solutions and ensuring mobility for everyone. “
Akridata’s solution is optimized for advanced AI workloads, providing built-in capabilities for AI-driven data organization, transformation and filtering tasks. It enables data tracing and tracking from creation to inference, it enables traceable AI and largely complements industry efforts towards explanation. IA (XAI). This makes it possible to track the evolution of AI models and to link the behavior of AI models in the field to the datasets that have contributed to the specific model used by a specific device or service.
“Akridata makes the autonomous world possible by providing the final piece of the puzzle: an integrated Edge-Core-Cloud data platform that solves the data problem at the heart of all real-world AI systems,” said Kumar Ganapathy, co-founder and CEO of Akridata. “The future of AI is all about data, and our focus on AI data since its inception gives Akridata a leading edge. We are excited to launch the first infrastructure product in the Data-Centric AI category, and to work with a range of customers, including industry leaders like Toyota Motor Company North America. “
“To thrive in the emerging global IT infrastructure, businesses and other organizations will need to leverage heterogeneous data from highly distributed sources ranging from edge devices to powerful computers in clouds and data centers,” said Steve conway, Senior Advisor at Hyperion Research. “Akridata is well positioned to benefit from the strong growth that Hyperion Research expects in this emerging data-driven market.
Akridata’s innovative new solution enables the integration of deep learning with inference, edge commerce, data governance and enterprise applications. It was specially developed to address the Exascale-class data challenges of delivering advanced AI, autonomous devices, and unattended services.
“Advanced AI models are increasingly created and run in the cloud, but require good quality data from edge devices,” said Jon jones, Director – Go-to-Market for AI / ML, EC2 and Autonomous Vehicles, AWS. “The high volume and complex nature of this data has created a new exascale class problem. Akridata solves the problem by managing smart pipelines for AI data ingestion, filtering, curation, tracking, and staging.
AI data complexity
The autonomous world depends on continuous deep learning using large volumes of complex AI data sets. Rich data streams – such as video and lidar data – generated by fixed or mobile edge devices must be organized, filtered, tracked, and processed on Edge-Core-Cloud resources. Massive amounts of data are being generated at the edge by these devices. For example, an autonomous car in the test phase can generate several terabytes of data in a single day. By 2025, 75% of the 175 zettabytes of new data generated will come from the Edge, according to industry experts.
“Particularly for newer workloads such as AD / ADAS development, HPC / IA workflows are increasingly facing an Exascale-class data challenge. AI and software development and validation pipelines, ”said Kurt Niebuhr, Senior Program Manager, HPC / AI Ecosystem and Workload Incubation, at Microsoft Azure. “Data-centric AI solutions like Akridata’s Edge data platform address this need and help customers match the sophistication of their analytics and models with relevant, high-quality data.
The Akridata Edge intelligent data platform is distributed and helps optimize the processing, storage and movement of data across the Edge, Core and Cloud. The Akridata platform is available today and has proven to deliver ten times faster access time to the right data, four times the efficient use of compute and storage, and twice the productivity for scientists. data and machine learning engineers. With Akridata’s solution, real-world AI-powered products can come to life.
Also today, Akridata announced that it has lifted $ 15 million in series A led by TeleSoft Partners, Accel and Mobile Foundation Ventures (MFV) Partners. The Silicon Valley-based company has over 50 team members and is actively recruiting for a range of engineering and customer success roles. Learn more about Akridata’s career site.
Click to Tweet: Category builder @Akridata launches the world’s first Edge data platform for data-driven AI. Solves the Exascale data problem at Edge-Core cloud level, drives AI innovations. https://www.akridata.com/akridata-launches-worlds-first-edge-data-platform-for-data-centric-ai
Akridata will celebrate the National day of exascales future October 18.
Akridata enables data-centric AI by solving the Exascale class data problem of AI. Akridata Edge Data Platform is the premier solution spanning Edge-Core-Cloud resources. It provides a decentralized structure and a scalable process to deliver organized, consistent, and relevant AI datasets. Akridata was founded in 2018 by some of Silicon Valley’s most respected entrepreneurs, data scientists and product engineers, who collectively hold nearly 200 patents and are used to solving some of the world’s most complex data problems. Akri means “Edge” in Greek. Learn more about akridata.com.
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SOURCE Akridata, Inc.