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SAS invests US$1B in AI over next three years

SAS invests US$1B in AI over next three years

Focus will be in three areas - software innovation, education and expert services

SAS CEO Dr Jim Goodnight

SAS CEO Dr Jim Goodnight

SAS says this commitment builds on its already strong foundation in AI which includes advanced analytics, machine learning, deep learning, natural language processing (NLP) and computer vision.

SAS says the US$1 billion investment will focus on three main areas - research and development (R&D) innovation; education programmes addressing customer needs to better understand and benefit from AI; and expert services to optimise customer return on AI projects.

"At SAS, we remain dedicated to our customers and their success, and this investment is another example of that commitment," says SAS CEO Dr Jim Goodnight.

"With our innovative capabilities in AI, SAS helps businesses deter damaging fraud, fight deadly disease, better manage risk, provide exemplary service to customers and citizens, and much more,” says Goodnight, in a statement.

SAS says the investment in R & D innovation will be in all core areas of AI, with a special focus on making it easy for users with different skill levels to benefit. These range from business experts to data engineers and data scientists.

SAS says it is embedding AI capabilities into the SAS Platform and solutions for data management, customer intelligence, fraud and security intelligence and risk management, as well as applications for industries including financial services, government, health care, manufacturing and retail.

SAS adds it is continuing its partnership with technology and services providers like Accenture, Cisco, Deloitte, Intel and NVIDIA to bring the latest AI and machine learning to customers.

One such company is SciSports, a Dutch sports-analytics startup,  applies computer vision from SAS to data streaming from soccer, or football, matches.

SAS AI technology running on NVIDIA GPUs delivers in-game insights to coaches and managers.

By capturing and analysing this and other data, football clubs can improve many aspects of game, including in-game strategy, player recruitment and the fan experience.

"The reason SAS tops the revenue list for advanced analytics for the last five years is that SAS solutions are built on a foundation of machine learning and deep knowledge of analytics. These are part of SAS' DNA," says Dave Schubmehl, research director for artificial intelligence at IDC.

"Combining SAS' knowledge and technology with its continued push to innovate in computer vision, NLP and deep learning will drive further adoption of AI across multiple industries,” says Schubmehl. “And it will help companies interested in AI – whether early in their AI and analytics life cycle or more mature."

Developing AI talent

SAS says investment in customer education includes the new AI Accelerator Programme that focuses on helping organisations and professionals get AI-ready at any level.

The programme provides tailored courses to help organisations improve their AI skills. These will include e-learning like the SAS Academy for Data Science, and in-person training in AI technologies and best practices.

There are also certification programmes that will help analytics professionals and data scientists earn the valuable credential of SAS Certified Professional in AI and Machine Learning. “This will make them even more marketable to companies seeking AI talent,” says SAS.

The SAS Analytics Center of Excellence, will support customer AI implementations – from well-established applications to first-of-a-kind innovation. The centre is a group of PhDs and advanced experts in AI, machine learning, NLP, computer vision, optimisation, simulation and related data science skills who are focused exclusively on customer implementations.

Building AI into the business

SAS says it is expanding its research into AI through the newly completed smart campus project.

The project features the 420,000 sq. ft. tower hosting the Global Education Center.

The building features thousands of IoT connected sensors – embedded in chillers, boilers and air handlers – that monitor water and energy use.

Through neural networks using SAS Event Stream Processing, the  facilities team will track sensors and systems performance in real-time to enhance predictive maintenance, such as identifying equipment problems before they become major, and optimise energy and water usage.

SAS says nearly half of the new building’s power is supplied by the adjacent SAS solar farm.

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