Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...Full Bio
Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...
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Cognizant's Chief Technology Officer Says Leveraging Artificial Intelligence and Machine Learning is About Translating Algorithmic Business into Data Science
"Artificial intelligence (AI) and machine learning (ML) have rapidly matured over the years and are already the norm in many fields, helping companies deploy smart systems of engagement to improve efficiency, enhance security, gain insights, and deliver superior customer experiences," writes Aan Chauhan. "AI and ML are expected to completely redefine operations - across the front-, middle- and back-office - creating new opportunities to bolster competitive advantage." Excerpts:
"While the ability to learn from data and make predictions, explanations, detect anomalies and make recommendations throws up substantial opportunities to unlock value, organizations are often not sure about where and how to embark upon their AI and ML journey.
To begin with, businesses should focus on the "Do, Think, Learn" continuum to identify the types of systems that need to be deployed. Systems that "do" - so you don't have to - replicate repetitive, rules-based human actions. Systems that "think" can operate more dynamically, even in situations with variances, so that you can make decisions autonomously. Systems that "learn" have the capability to adapt and make optimal adjustments when variables change, enabling a rich partnership between humans and software. Over time, organizations should transition from systems that "do" to systems that "think" and "learn".
In adopting AI and ML to future-proof themselves, businesses should carefully assess implementation opportunities - those with a short-term horizon that can give a quick return on investment (ROI), medium-term projects that are transformational in nature, and long-term moon-shot goals where AI and ML play a core role.
Making the most of AI and ML is about creating an environment for human-centric practices such as design thinking, strategic thinking, sociology, and ethnography to work in tandem with digital skills.
Alongside, businesses should focus on developing, honing and capitalizing on the capabilities that are uniquely human and cannot be replicated today by automated software. They should create new skills and roles within the organization focused on the successful adoption of AI and ML across cognitive computing technologies, data sciences, and natural interfaces.
Leveraging AI and ML is about understanding the algorithmic business (a business built around the industrialized use of complex mathematical algorithms for competitive differentiation) and translating it into data science. By tapping into the strengths of both man and machine, businesses can achieve higher productivity and superior business results." Continue Reading>>