The utilization of advanced artificial intelligence (AI) technology holds significant promise for revolutionizing education. AI has the capacity to enhance learning experiences and deliver tailored instruction, thereby affording educators and students access to highly efficient and impactful learning tools.

• Yuliya Melnik

Not long ago, ordering food from a restaurant would have involved rummaging through a stack of menus and making a phone call. Now, in the age of online food delivery platforms, ordering food is just a few taps on your smartphone. While online food delivery platforms have caught on among consumers and continue to experience double-digit growth, these platforms have upended the decades-old business model of restaurants globally.

• Soumyadeep Kundu
• Ashutosh Sarkar

We are fortunate to be living in an exhilarating era witnessing the birth and flourishing of an extraordinary scientific discipline: data science. Much like a dazzling celestial spectacle, data science has risen to prominence, captivating both academia and business with its profound interdisciplinary impact and limitless possibilities. As data science propels forward with the rapid unfolding of the artificial intelligence (AI)-driven Fourth Industrial Revolution, now is a moment ripe for historical reflection. Understanding the factors that distinguish data science from other analytics-intensive contenders is crucial for comprehending its ascent to the forefront of the scientific frontier.

• Zhiwei Zhu

According to the 2023 Gartner Magic Quadrant for Data Integration Tools, the data integration tools market is thriving because of upcoming requirements for data fabric architectures, data product delivery and the need for integrated data to support generative artificial intelligence (GenAI). One thing is clear for this year, though: If data-centric organizations want to succeed in 2024, they will need to prepare for an environment in which data is increasingly distributed.

• Angel Viña

Today’s business leaders increasingly use artificial intelligence (AI) tools to analyze company trends and make critical decisions. However, AI algorithms often make biased suggestions that could be misleading. Moreover, people intending to use AI in business analytics must ensure they only do so ethically. Following best practices can keep company decision-makers, data scientists and others on the right track. Here are seven ways to ensure ethical and bias-free AI in business analytics.

• April Miller

Large language models (LLMs) are an exciting new frontier for delivering services but also require a new kind of tech stack that supports app development, deployment and maintenance, with a focus on quality and accuracy. We’ve learned that the three essential elements of the LLMOps tech stack are (1) observability, (2) compute and (3) storage.

• Anupam Datta