Radhika Madhavan

Radhika Madhavan covers AI innovation at TechEmergence. Radhika previously worked in content marketing at three technology firms, and graduated from Sri Krishna College Of Engineering And Technology with a degree in Information Technology.

Articles by Radhika

8 articles

User Engagement Company Improves Lead Quality Using Predictive Analytics

Technology Provider: Ignite Technologies¬†(which acquired Infer, a Mountain View, CA-based marketing optimization and machine learning company). User Company: WalkMe simplifies user experience by providing step-by-step product usage instructions for B2B tools like SAP, Oracle, Microsoft Dynamics 365, SalesForce, etc. Industry: B2B Software Application: Sales and marketing Problem WalkMe has a broad target market, expanding across […]

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Natural Language Processing - Current Applications and Future Possibilities

Natural Language Processing – Current Applications and Future Possibilities

A 2017 Tractica report on the natural language processing (NLP) market estimates the total NLP software, hardware, and services market opportunity to be around $22.3 billion by 2025. The report also forecasts that NLP software solutions leveraging AI will see a market growth from $136 million in 2016 to $5.4 billion by 2025. In order […]

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Avoiding Common Mistakes in Applying AI to Business Problems - with Jeremy Barnes of Element AI 1

Avoiding Common Mistakes in Applying AI to Business Problems – with Jeremy Barnes of Element AI

Episode summary: This week, AI in Industry features Jeremy Barnes, Chief Architect at Element AI. Jeremy talks about the common mistakes some businesses might make while adopting AI to solve broad business problems. He also sheds light on the problem areas that could raise the market value of businesses through AI adoption, hiring the right […]

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AI in Biometrics and Security – Current Business Applications

Biometric solutions are typically used for security and access control across businesses and government organizations. The U.S. government has taken keen interest in biometric applications and has been aggressively funding advanced research programs in businesses that offer biometrics. The Intelligence Advanced Research Projects Activity (IARPA), a U.S. government organization that funds academy and industry research, […]

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AI Recommendation Engines for Big Purchases - Will You Buy Your Home or Car Using AI? 2

AI Recommendation Engines for Big Purchases – Will You Buy Your Home or Car Using AI?

Episode summary:¬†This week, AI in Industry features Dr. David Franke, Chief Scientist at Vast. David talks about how AI can work with scarce transaction data to derive meaningful analytics for big purchases, such as cars and houses. He elaborates on how the AI can glean information from user interaction and marketplace data to provide customers […]

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Building and Retaining a Data Science Team

Building and Retaining a Data Science Team

Episode summary: This week on AI in Industry, we speak with Equifax’s Dr. Rajkumar Bondugula about how the dynamics, composition and requirements of the data science team have evolved over the years. Raj also shares valuable insights on how to build a robust data science and machine learning team, use its collective intelligence to solve […]

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Machine Translation - 14 Current Applications and Services across 9 Use Cases

Machine Translation – 14 Current Applications and Services

Machine translation has significantly evolved over time, especially in terms of accuracy levels in its output. According to the below image released by Google in 2016, Google Translate performs translations in varying levels of accuracy on par with human translators, from Spanish, Chinese and French to English and vice versa. As machine translation applications are […]

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Machine Learning for IoT Security - with Dr Bob Baxley of Bastille

Machine Learning for IoT Security – with Dr Bob Baxley of Bastille

This week on AI in Industry, we explore IoT security with Bob Baxley (Chief Engineer at Bastille). This includes information on how different IoT security is compared to infosec, the unique challenges IoT security presents (for detecting and scanning wireless network traffic that runs on various protocols and for classifying types of cyberthreats), what the […]

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