Analytics NEWS

Karnataka to launch centre of excellence for AI and Data Science:

NASSCOM, through its partner ecosystem will work towards accelerating innovation, enabling industry-oriented research, promoting adoption of data-driven decision making by enterprises and enabling appropriate skills and talent development.

This proposal has evinced great interest for the industry to collaborate and build collective capabilities for the industry and country in the cutting-edge area of Data Science and Artificial Intelligence. The Centre of Excellence will provide high-end technology capabilities, data, expertise, thought leadership, and curated programs to augment capabilities across academia, enterprises, government, and innovators / advanced start-ups.

 

Analytics market to keep growing with digital transformation:

From enterprises to power stations, hospitals and public transportation, the volume of real-time data generated is unprecedented today. Data has become a crucial part of the smooth functioning of business operations. With the generation of more and more data, the opportunity of analytics to derive profitable outcomes for businesses is growing rapidly.

In such a context of rapid transformation, data and analytics cannot be considered separate from each other. In order to adapt to disruption and benefit from the digital transformation, organizations are leveraging analytics tools and taking a focused approach to developing the true value of information.

The presence of large complex data sets is why technologies like deep learning and machine learning have risen to become one of the biggest trends in analytics, with large tech organizations heavily indulging in open AI hardware and software.

The SPARC program uses analytics to bring about societal transformation:

SPARC is an initiative by TATA Trusts, the Constitution Club of India (CCI) and Swaniti to leverage big data and analytics to bring about societal transformation. SPARC stands for “Supporting Parliamentarians on Analysis and Research in the Constituency.

SPARC is a grassroots level program that pairs youth leaders with Members of Parliament for a period of one year. Twenty young leaders will be working with twenty MPs across India to support development programs in the constituency. SPARC is a fellowship program that started in 2016, which ensures the continued engagement of the MPs with the development programs in the constituencies, builds the capacity of the fellows on a leadership front, and also effectively uses government networks at the same time.

Sentenai Delivers Automated Data Engineering for Data Science and Machine Learning Applications

Sentenai, an emerging sensor data technology company, announced the availability of its flagship product, the Sentenai Sensor Data Cloud. By going beyond the initial harnessing of machine-based data and understanding the information that data provides, organizations can streamline their operational processes and develop predictive maintenance solutions that decrease unplanned downtime.

With its Sensor Data Cloud, Sentenai is empowering businesses and their data scientists to build on sensor-based applications by allowing them to access historical data in the tools they already use, without requiring any data engineering work.

Enterprise IoT devices, or the Industrial Internet of Things (IIoT), is gaining momentum at an exponential rate. Industrial sensor devices are fundamentally transforming the way organizations do business with other companies, with recent data indicating enterprise IoT spending could hit $1.477 trillion by 2020 with more than 7 billion enterprise IoT devices in use.

Algorithmia Launches AI Layer for the Enterprise

Algorithmia announces the availability of the Algorithmia AI Layer, a software platform that dramatically accelerates the process by which companies can deploy Artificial Intelligence (AI) and Machine Learning (ML) models into applications.

Designed for companies building AI/ML algorithm portfolios, Algorithmia AI Layer allows data scientists to automate the DevOps and deployment of AI/ML models in the language of their choice with a simple API in a matter of minutes.

Billions of dollars are spent annually by data scientists and the companies they work for developing AI/ML models, however, organizing and implementing these models is a manual and expensive process requiring years of highly experienced engineers’ development time, and requiring the team to keep the layer up-to-date with the latest AI/ML technologies. The lack of AI infrastructure has become a “last mile” problem for companies, which keeps most AI/ML investments from ever reaching production.

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