In this contributed article, Shobhit Khandelwal, CEO and founder of Carter, points out that as competition grows in the retail media space, brands and retailers feel pressured to meet consumer needs. The opportunity to provide unique advertising experiences to consumers increases as AI develops. These rapid developments in AI put us on the precipice of a great revolution in the retail media landscape.
Predictive Analytics: A Glimpse into Your Health’s Tomorrow!
September 3, 2024 by
In this contributed article, Sanket Patel, co-founder of Digicorp, discusses how in the healthcare industry, predictive analytics aims to foresee patient health trends, treatment outcomes, and potential risks by analyzing vast amounts of medical data.
Shining a Light on Dark Data: The Path to Responsible AI Integration
August 30, 2024 by
In this contributed article, Soniya Bopache, vice president and general manager, data compliance and governance at Veritas Technologies, discusses how integrating AI into business operations requires addressing the challenge of dark data—unstructured and unused information that can lead to biased or compromised AI outputs. Organizations must prioritize comprehensive data management and governance to ensure AI systems are powered by high-quality data, meeting both operational goals and regulatory compliance.
Data Sovereignty in the AI Era
August 27, 2024 by
In this contributed article, Yoram Novick, President and CEO of Zadara, discusses how enterprises are in search of and implementing their own AI powered clouds, and the benefits and challenges they face in the effort to keep their data available and secure.
How AI Enhances Government Payment Processes – Survey Reveals Critical Inefficiencies
August 23, 2024 by
In this contributed article, Niko Spyridonos, CEO and Founder of Autoagent Data Solutions, discusses local governments and their use of AI and automation technologies. Niko is a strong proponent of such systems and he has some government survey data that shows we need to move deeper in this area.
It Takes More than Prompt Engineering to Achieve GenAI Accuracy
August 19, 2024 by
In this contributed article, Liran Hason, Co-Founder and CEO of Aporia, addresses the limitations of prompt engineering, outlining his argument for more comprehensive protection – namely, the implementation of guardrails between the LLM and end-user – to keep AI accurate while preventing unwanted behavior.
Synthetic Data Solves AI’s Biggest Problem
August 13, 2024 by
In this contributed article, Kalyan Veeramachaneni, co-founder and CEO of DataCebo, discusses how synthetic data is a useful application of AI technology that is already delivering real, tangible value to customers. More than mere fake data, synthetic data supports data-driven business systems throughout their lifecycle, particularly where ongoing access to production data is impractical or ill-advised.
Data Due Diligence is Critical to Maintaining Compliance and Mitigating Breaches During and After M&As
August 8, 2024 by
In this contributed article, Fredrik Forslund, Vice President and General Manager of International Sales for Blancco Technology Group, emphasizes the importance of adhering to cybersecurity and data governance best practices prior to an M&A to prevent a data breach and ensure the protection of an organization’s customer and corporate data.
Transforming AI’s Memory Constraints: The Evolution with CXL Technology
August 2, 2024 by
In this contributed article, Jianping (JP) Jiang, VP of Business, Operation and Product at Xconn Technologies, discusses how the integration of CXL technology is a pivotal moment in overcoming the memory barriers faced by AI and HPC applications. By significantly enhancing memory bandwidth, capacity, and interoperability, CXL not only optimizes current workloads but also sets the stage for future advancements.
Unlocking AI’s Potential: How to Build High-quality Data Foundations
July 29, 2024 by
In this contributed article, Chris Round, Senior Product Manager at Lakeside Software, suggests that AI’s critical flaw is that it doesn’t know good data from bad – it just knows data. So your AI is only as good as its underlying foundations.
