The challenges cloud migration and modernization solve for enterprises
With legacy systems, traditional data storage, and integration methods phasing out for many organizations, businesses are rapidly transitioning to cloud-based data to imp...
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LLMs: Can intelligence be caged?
It may depend on the level of intelligence and the perception of the strength of that cage by the captors. The cage may be strong enough that without any unknown or unexp...
Why FAIR data assets are essential to AI data management
One of the efforts our Dataworthy Collective will be ramping up in 2024 involves standardizing the building of logical knowledge graphs at the level of the document objec...
Data management implications of the AI Act
Members of the European Parliament and the Council reached provisional agreement on the Artificial Intelligence Act on December 9th, 2023 after years of debate and discus...
AI and Justice in a Brave New World: Part 3 – AI Governance
In part 1 of the series “A Different AI Scenario: AI and Justice in a Brave New World,” I outlined some requirements for the role that AI would play in enforcing our ...
Beyond LLMs and Trillion-Parameter Models
These days, it is as if AI is just about GenAI (generative AI), LLMs (large language models) and very large models. It has eclipsed computer vision, voice AI and everythi...
Maximizing marketing potential: The AI-driven revolution in outsourced digital marketing
In today’s digital marketing world, things are changing fast, and artificial intelligence (AI) is a big part of that. Companies want to stay ahead, so they’re...
Universal basic income and the gig economy: A combined policy approach to alleviate the challenges of AI
Much has been said about the economic impact of AGI, some of it is already been feltBut not much has been proposed about solutions.Specifically, what approaches should po...
An integration tax that every adult in the US pays
I live in Northern California and have a new primary care doctor now. My previous primary care doctor, who has since retired, was part of the Stanford Health Care (SHC) s...
What’s wrong with data labels
Technical Advisor and former LinkedIn knowledge graph lead Mike Dillinger recently spoke with Juan Sequeda and Tim Gasper of data.world. During a recent edition of the Ca...