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SAP advances blockchain adoption

Provider also seeks to expand its reach in freight and transportation management through BiTA membership

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SAP seeks to integrate blockchain into IoT, manufacturing and digital supply chain solutions
SAP seeks to integrate blockchain into IoT, manufacturing and digital supply chain solutions

SAP will join Spain’s Alastria consortium and the blockchain-in-trucking alliance BiTA to help expand the adoption of blockchain to customers in a wide range of industries and geographies. It made the announcement at the SAP Tech Ed event being held in Barcelona.

 

According to SAP, participation in Alastria, which brings together banks, telecom providers, energy companies, universities, smart city organisations and developers, will allow it to strengthen its blockchain ecosystem and network in Europe.

 

The enterprise solutions provider also seeks to expand its reach in freight and transportation management through BiTA membership which promotes the development of blockchain standards and education.

 

SAP also announced that 27 customers and partners have signed up to its blockchain co-innovation initiative which aims to integrate the digital ledger system into Internet of Things (IoT), manufacturing and digital supply chain solutions using its cloud platform blockchain service.

 

Participating companies include Deutsche Telekom and Benjamin Moore and come from 11 countries, representing consumer products, telecom, retail, logistics, agriculture, high-tech, aerospace and defense, industrial machinery, energy and utilities, and public services industries with a total market value of $819

 

Meanwhile, SAP has updated its Leonardo Machine Learning Foundation with three new features, delivering machine learning offerings that are easy to use and have the most impact on companies.

 

The new features are: optical character recognition (OCR); “retrainable” services, where customers and partners can train generic models with custom data -- these two new features require only minimal machine learning experience.

 

The third is bring-your-own model, where users can deploy and run their custom models based on TensorFlow on its Leonardo Machine Learning Foundation.

 

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