In this paper, we introduce MASQRAD (Multi-Agent Strategic Query Resolution and Diagnostic tool), a transformative framework for query resolution based on the actor-critic model, which utilizes multiple generative AI agents. MASQRAD is excellent at translating imprecise or ambiguous user inquiries into precise and actionable requests. This framework generates pertinent visualizations and responses to these focused queries, as well as thorough analyses and insightful interpretations for users. MASQRAD addresses the common shortcomings of existing solutions in domains that demand fast and precise data interpretation, such as their incapacity to successfully apply AI for generating actionable insights and their challenges with the inherent ambiguity of user queries. MASQRAD functions as a sophisticated multi-agent system but "masquerades" to users as a single AI entity, which lowers errors and enhances data interaction. This approach makes use of three primary AI agents: Actor Generative AI, Critic Generative AI, and Expert Analysis Generative AI. Each is crucial for creating, enhancing, and evaluating data interactions. The Actor AI generates Python scripts to generate data visualizations from large datasets within operational constraints, and the Critic AI rigorously refines these scripts through multi-agent debate. Finally, the Expert Analysis AI contextualizes the outcomes to aid in decision-making. With an accuracy rate of 87\% when handling tasks related to natural language visualization, MASQRAD establishes new benchmarks for automated data interpretation and showcases a noteworthy advancement that has the potential to revolutionize AI-driven applications.

Leading the company's vision to disrupt the knowledge management market. Often described as the emotional connection between a customer and a brand, customer engagement is far more than a transactional relationship. It's no longer limited to sales, services and support and is an ongoing process where a company anticipates a customer's needs and gains their loyalty. As the CEO of a company that offers call center, self-service and virtual assistant technology, I've found that most brands understand customer engagement plays a crucial role in customer experience and business outcomes. For those looking to gain a competitive advantage, AI as a driving force in engagement can be one of the best ways to build gratifying experiences.

We conducted a survey in the months of August, September and until Mid Oct 2019. The idea was to explore the top 10 data science programs/institutes in India: Ranking 2019-2020. We circulated a Google form with all the visitors on our jobs portal, Analytics Jobs. While ranking the programs, we kept in mind the ROI. So, the biggest factor for Ranking is based upon return on investment and the skills delivery to the students.

While ranking the programs, we kept in mind the ROI. So, the biggest factor for Ranking is based upon return on investment and the skills delivery to the students. DataTrained is one of the companies working in the Retail Analytics domain. It was founded in 2012. They also impart training in data science and management space.

Expedia Group has announced a collaboration with AI Singapore (AISG) – an inter-agency unit tasked to catalyse and grow the country's artificial intelligence (AI) capabilities – under its flagship 100 Experiments (100E) programme to develop an AI solution to transform the online search experience for Asian travellers. The first online travel platform to collaborate with AISG for 100E, Expedia Group will provide a team of experienced engineers, data scientists and marketers to work with the AISG's project lead, project managers and AI apprentices to enhance travel search query understanding and improve the accuracy of search query resolution in Asian languages. Today's search engines are efficient in understanding travel search queries and providing query resolutions in English, as English is the dominant language used online by 25 per cent of all Internet users. However, when dealing with travel search queries conducted in Asian languages such as Japanese, Korean, simplified Chinese and traditional Chinese, the performance of the search engines declines significantly and the accuracy of query resolution dips. For a start, the Expedia Group and AI Singapore project team will leverage natural language processing and machine learning to develop an AI-based model to enhance search query understanding and resolution in the Japanese language, before extending the model to other Asian languages to enhance online search efficiency.