What If AI’s Mistakes Aren’t Bugs, but Features?
We often say AI’s mistakes are “by design,” but they’re really not. AI wasn’t built to fail in these specific…
AI
The Future of Data Engineering and AI-Driven Analytics in the Workforce
The future of data engineering and AI-driven analytics is both exciting and complex. As technology continues to evolve at a…
AI’s Newest Employee: Who Bears the Burden of Your Digital Co-Workers?
Digital co-workers are no longer hypothetical. AI-driven agents (“Agentics”) are creeping into every function, every decision process, and every interaction…
Through the Looking Glass: Technology Solutions in Search of a Problem
When I read about new technologies, I often think of the movie “Field of Dreams.” The protagonist builds a baseball…
Generative AI vs. Predictive AI: Comparing Apples and Oranges
The AI revolution is upon us, with businesses pouring billions of dollars into generative and predictive AI solutions. From crafting…
All in the Data: Too Soon for Q Governance?
Quantum computing, with its groundbreaking capabilities, is poised to redefine how organizations solve complex problems and innovate in ways previously…
The Book Look: AI & The Data Revolution
I am just going to start off by saying that I am a Laura Madsen fan. Her writing style combines…
Legal Issues for Data Professionals: In AI, Data Itself Is the Supply Chain
Data is the supply chain for AI. For generative AI, even in fine-tuned, company-specific large language models, the data that…
Through the Looking Glass: What Does Data Quality Mean for Unstructured Data?
I go to data conferences. Frequently. Almost always right here in NYC. We have lots of data conferences here. Over…
Ethical Considerations in AI-Powered Data Archiving for IT Operations
The rapid adoption of artificial intelligence (AI) in data archiving for IT operations has transformed how organizations manage vast amounts…