Advocating Collaboration in Safe AI Management

In this contributed article, Rosanne Kincaid-Smith, Group COO at Northern Data, delves into the ethical considerations of ensuring AI safety and emphasizes the need for a collective approach to AI management – involving a mixture of technical and societal bodies who understand its far-reaching impact. The piece sheds light on the growing concerns surrounding the emergence of next-generation AI technologies and underscores the new collaborative efforts of the US and UK in addressing safety concerns linked to the integration of AI into business operations.

Unlocking the True Power of AI by Turning Conventional ML Wisdom On Its Head

In this contributed article, Iain Wallace, Director of Machine Learning and Tracking Research at Ultraleap, discusses how rethinking your approach to machine learning can drive true AI innovation.

New Global Survey Finds Enterprises Lack Direction and Training for Workers on the Use of GenAI Tools   

UiPath (NYSE: PATH), a leading enterprise automation and AI software company, published its annual Global Knowledge Worker Survey that uncovers how employees are using generative AI (GenAI), the shortcomings and risks of the technology, and the opportunity for combining GenAI with business automation. 

Harnessing Big Data for Sustainable Financial Decisions

In this contributed article, freelance writer Ainsley Lawrence suggests that in the financial sector, decision-making often comes with a higher degree of risk, but with insights provided by big data, those risks can be mitigated, leading to increased revenue and enhanced efficiency. 

Personalizing Employee Experiences with Product Analytics

In this contributed article, Vara Kumar, co-founder and head of R&D and pre-sales at Whatfix, discusses how in today’s competitive landscape, harnessing the full potential of product analytics is pivotal for companies seeking to optimize their internal and external product usage. There are multifaceted benefits of leveraging product analytics,
showcasing its ability to provide profound insights into product utilization across an organization.

Low Code/No Code

In this contributed article, Ben Kliger, CEO and co-founder, Zenity, explores the connection between AI and no/low code development and how to bring application security measures to the new world of low-code/no-code app development.

In the Era of Cloud and AI, Hard Drives are More Critical than Ever Before 

In this contributed article, Jason Feist, Seagate’s Senior Vice President of Products and Markets, believes that amidst the data center boom and growth of AI, data storage is more important than ever, and it’s high time we revisit the HDD vs. SSD debate. While flash offers latency advantages and prices dropped temporarily, SSDs haven’t – and
never will – replace HDDs,

AI+BI: Bridging Cognitive and Usability Gaps in Business Intelligence

In this contributed article, Saurabh Abhyankar, EVP and Chief Product Officer, MicroStrategy, explains the synergy between the two technologies and how they come together to revolutionize how we understand data, make decisions, and envision the future of business.

From ER Diagrams to AI-Driven Solutions

In this contributed article, Ovais Naseem from Astera, takes a look at how the journey of data modeling tools from basic ER diagrams to sophisticated AI-driven solutions showcases the continuous evolution of technology to meet the growing demands of data management. Understanding how data modeling tools have changed over time gives us important insights into why organizing and analyzing data well is so important.

How Can Data Science Accelerate Drug Discovery Processes?

In this contributed article, April Miller, senior IT and cybersecurity writer for ReHack Magazine, describes how thoughtfully applied data science principles and tools empower modern researchers to find new, viable treatment methods for various diseases and ailments. Humans will always be essential to drug discoveries, but the fascinating examples here and elsewhere show the power of using purposeful data analytics to meet shared goals.