STEMROBO aims to establish tinkering and innovation labs and provide proper training for teachers in STEM, robotics, coding and AI.

STEMROBO aims to collaborate with more than 10,000 schools by FY24. Ed-tech start-up, STEMROBO Technologies, has announced to set up ‘Showcase Schools’, an end-to-end ecosystem with the aim to ensure the holistic development of students. The announcement comes amid National Education Policy (NEP) 2020 mandate for K12 students to get indulged in experiential learning

Artificial Intelligence (AI) is one area considered by many executives to enable Automation and steer positive growth.  A couple of years ago, most executives thought that deployment of Artificial Intelligence isn’t a big deal.  However, revamping traditional systems, implementing AI, and scaling it, in reality, is not as simple as it seems.

A survey by PwC Research in 2020, which gathered responses of 1062 business leaders, validates that scaling and industrializing AI is not straightforward at

In this week's blog post, we're sharing insights on our interview with Terisa Roberts. She is a Director and Global Solution lead for Risk Modeling and Decisioning at SAS. She has extensive experience in quantitative risk management, and advanced analytics. She has worked in a variety of industries, including financial services, telecommunications, energy, retail and government. She advises banks and regulators around the world on best practices, topics in risk Modeling, Decisioning, and the r

This is a transcription of our interview with Terisa Roberts, Director and Global Solution lead for Risk Modeling and Decisioning at SAS about the role of AI/ML in Risk Management.

You can watch the original video interview here or tune in to this episode on our Risk Management Show podcast here https://globalriskcommunity.libsyn.com/terisa or via iTunes, Spotify and other podcast apps by searching "Risk Management Show"

Boris: Welcome to our interview with Terisa Roberts. She is a Director and

Identity fraud is becoming an increasing problem day after day for businesses. Criminals create new mechanisms for fraud as identity theft tends to raise problems for customers. According to the 2019 Javelin Plan and Analysis Identity Fraud Report, in 2018, there were 14.4 million users who had become victims of identity fraud, down from 16.7 million in 2017, the record figure. Identity theft in 2018 was nevertheless more burdensome: 3.3 million individuals were liable, about three times as many

It’s no wonder many third-party risk management (TPRM) professionals are skeptical about the hype surrounding AI. Their very careers require them to be risk averse, and the technology has been associated with spectacular failures as well as successes, such as Tay, the chat bot that adopted racial slurs and inappropriate language from users.

The early failure of Tay underscores the most important success factor in deploying AI technologies such as machine learning and natural language processing.

AI in Asset Management is trending and making a Wave in the Industry. Here is what You Need to Know About artificial intelligence and its application in asset management. The artificial intelligence finds its applications in various fields of industries. Presently, the main areas where AI is gaining more attraction is financial assets management that include investment banking, personal financial management, and fraud detection. With the advancement in technology, application of machine learning

Survival of a business in this digital age largely depends on its ability to timely embrace Digital Transformation. Digital Transformation entails using Digital Technologies to streamline business processes, culture, and customer experiences.

In order to compete today—and in future—and to enable Digital Transformation, organizations should work towards fostering a culture of continuous learning, since Digital Transformation depends on learning and innovation.  The organizations that holistically

Transformation of an organization into a Next-generation Learning Organization (NLO) is a challenging endeavor.  The main hurdles include convoluted hierarchies, bureaucratic red tape, delayed decision making, and complicated organizational systems and processes.

To develop a learning organization, leadership needs to trim down bureaucracy and complexities.  They should make the best use of technology to gather holistic real-time data, deploy Artificial Intelligence at scale, and develop data-dri

Since the advent of wearable technology in healthcare, data collection and the leverage of predictive health analytics to improve patient service has been increasingly easy for healthcare companies. By using data generated by wearable devices, companies can monitor the exact problem areas and offer treatment as required. Wearable healthcare technology is helpful to both professionals and patients and a technical change of the healthcare industry is said to be initiating.

The year 2020 has already

Healthcare supply chain management can be a daunting job due to its fragmented nature. It is where control of the supply chain of healthcare is essential for organizations. Supply chain management in healthcare includes planning, designing, implementing, monitoring and tracking the movement of products and services.

This allows greater net value to be generated, supply to be matched with demand, sustainability to be achieved with efficient logistic force and performance measurement. Healthcare su

The AI software segment currently holds the highest share of the global AI in the energy market (by product offering). AI software providers are responsible for maintaining and storing the application data of the customers. However, AI-as-a-service (AIaaS), also known as platform as platform-as-a-service, is one of the emerging AI product offerings, which allow the end users to access AI-enabled platform using cloud computing. AI-as-a-service is dependent on the purpose and application of the en

The global artificial intelligence in agriculture market (on the basis of product offering) is segmented into software, hardware, AI-as-a-Service, and support services. The software segment dominated the global artificial intelligence in agriculture market in 2018 and is anticipated to maintain its dominance in market size throughout the forecast period (2019-2024) with hardware and AI-as-a-Service experiencing higher growth rates.

Browse the Complete Report: "Artificial Intelligence in Agricultu