Reinforcement Learning: Teaching AI to Make Better Decisions

Artificial intelligence (AI) systems do not automatically know what constitutes a good answer. They must learn. One of the most powerful approaches for teaching AI how to improve its behavior is reinforcement learning. Reinforcement learning is a machine learning technique in which an AI system learns through trial and error. Rather than being explicitly told…

Read More

Data Science is Shaping the Future of Data Management in the Age of AI

Artificial intelligence (AI) is transforming nearly every industry, but rather than eliminating careers in data science, it is making them more important than ever. As organizations increasingly rely on AI-driven insights and automation, the demand for professionals who can understand, manage and govern data continues to grow. This interesting topic came to us from Brandeis…

Read More

Why Explainable AI Matters

Modern artificial intelligence (AI) systems such as ChatGPT, Gemini and other large language models (LLMs) are powerful technologies. They can write essays, summarize research, generate code, answer complex questions and perform tasks that once required significant human expertise. Yet despite their impressive capabilities, these systems share a common challenge: explaining how they got at their…

Read More

Quality is Key for Responsible AI

Generative artificial intelligence (GenAI) is a subset of artificial intelligence (AI). It has moved quickly from experimentation to everyday use, reshaping how organizations create, analyze and communicate. At the center of this shift is data. The quality and oversight of that data now directly influence how reliable and responsible AI outputs can be. This makes…

Read More

The More Technology Changes, the More Findability Matters

Over the past decade, emerging technologies have transformed nearly every aspect of how we create, manage and access information. Artificial intelligence (AI), machine learning, cloud computing, automation and natural language processing have shifted from futuristic concepts to everyday business tools. Entire industries have been rebuilt around predictive analytics, generative AI and massive-scale data processing. Information…

Read More

Trust in the Age of AI: Academic Publishing at a Crossroads

Artificial intelligence (AI) is rapidly reshaping academic publishing, raising both opportunity and concern around one critical issue: trust. For decades, scholarly communication has relied on peer review, editorial oversight and citation networks to ensure credibility. Now, with AI capable of generating convincing research summaries, abstracts and even full papers, the line between verified knowledge and…

Read More

Peer Review in the Age of AI: Still Necessary, Increasingly Complicated

Peer Review Week is right around the corner, which feels like excellent timing to talk about the quiet identity crisis happening inside scholarly publishing. This interesting and timely topic came to us from Nature.com in their article, “Peer review in the time of artificial intelligence.” Peer review has always been imperfect. It relies on human…

Read More

Garbage In, Genius Out? Not Without Data Governance

Generative artificial intelligence (GenAI) is having a moment. It writes, summarizes, predicts, designs and occasionally makes you question your own job security before your coffee kicks in. But beneath all the flash and promise is something far less glamorous and far more important: data governance. Because no matter how sophisticated your AI tools are, they…

Read More

Stronger Together

Generative artificial intelligence (GenAI), data centers and cloud computing are often discussed as separate technologies, each with its own role and evolution. In practice, however, they are deeply interconnected and increasingly dependent on one another to deliver real value. This topic was inspired by the podcast episode from W. Media titled, “The Intersection of Gen…

Read More