Knowledge Graphs as the essential truth layer for Pragmatic AI

Knowledge Graphs as the essential truth layer for Pragmatic AI

Organizations are facing a critical challenge to AI adoption: how to leverage their domain-specific knowledge to use AI in a way that delivers trustworthy results. Knowledge graphs provide the missing “truth layer” for AI that transforms probabilistic outputs into real world business acceleration. By George Anadiotis • 🚀 AI adoption is accelerating, but most implementations fail […]

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The Six Pillars of AI Literacy: From Regulatory Compliance to Hands-on AI

The Six Pillars of AI Literacy: From Regulatory Compliance to Hands-on AI

The clock for AI Literacy is ticking. Why should you act now, what are the six pillars of AI Literacy, and how can you build on those? • 📜 AI literacy is a legal requirement as of February 2025 • 🎯 Six core competencies define AI literacy: Recognition, Understanding, Application, Evaluation, Ethics, and Creation • […]

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Are we entering the era of Peer to Peer AI? Long views on AI, Part 3

Are we entering the era of Peer to Peer AI? Long views on AI, Part 3

“Please consider the advent of DeepSeek as a historical pivot to the era of ‘Peer to Peer AI’”. This quote is from Michel Bauwens’ essay “AI and the Advent of the Age of the Brahmin Workers“. Bauwens is the Founder of the P2P Foundation, a network investigating the impact of peer to peer and commons dynamics in our […]

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AI Chips in 2025: The end of “more GPUs is all you need”?

AI Chips in 2025: The end of “more GPUs is all you need”?

It’s early 2025, and we may already be witnessing a redefining moment for AI as we’ve come to know it in the last couple of years. Is the canon of “more GPUs is all you need” about to change? By George Anadiotis What an unusual turn of events. First, the Stargate Project. The joint venture […]

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Reviewing 2024, Previewing 2025: Technology, Data, AI, Media, Interconnectedness, Graphs, and Cosmo-localism

Reviewing 2024, Previewing 2025: Technology, Data, AI, Media, Interconnectedness, Graphs, and Cosmo-localism

As the year draws to an end, it’s a good time to take stock of how it started vs. how it’s going on the micro and the macro level. It’s also a good opportunity to try and answer the top two questions I get: What is it that you do, exactly? Where do you think […]

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Democratizing data with Graph RAG: What it is, What it can do, How to evaluate it

Democratizing data with Graph RAG: What it is, What it can do, How to evaluate it

What is Graph RAG, what can it do, and how do you evaluate it? By George Anadiotis Are you interested in making your data more accessible? A rhetorical question indeed. Even if you are well-versed in dark arts such as databases, data modeling, data science and information retrieval, why would you not want to make data […]

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Universal semantic layer: Going meta on data, functionality, governance, and semantics

Universal semantic layer: Going meta on data, functionality, governance, and semantics

What is a universal semantic layer, and how is it different from a semantic layer? Is there actual semantics involved? Who uses that, how, and what for? By George Anadiotis When Cube Co-founder Artyom Keydunov started hacking away a Slack chatbot back in 2017, he probably didn’t have answers to those questions. All he wanted to […]

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Neo4j partners with Microsoft, unfolds strategy to power Generative AI applications with cloud platforms and Graph RAG

Neo4j partners with Microsoft, unfolds strategy to power Generative AI applications with cloud platforms and Graph RAG

From better together to full native integration, Neo4j is creating an ecosystem around all major cloud platforms to enable provide graph-powered features for Generative AI and beyond. Here’s how this aligns with cloud platform AI strategies and what’s next. Hint: Databricks and Snowflake. By George Anadiotis For many organizations today, data management comes down to handing […]

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Evaluating and building applications on open source large language models

Evaluating, customizing and building applications on open source large language models

How do you choose the most appropriate model for your application? An analysis on evaluating and building applications on open source large language models. By George Anadiotis The computational complexity of AI models is growing exponentially, while the compute capability provided by hardware is growing linearly. Therefore, there is a growing gap between those two numbers, […]

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The future of AI chips: Leaders, dark horses and rising stars

The future of AI chips: Leaders, dark horses and rising stars

The future of AI chips is about more than NVIDIA: AMD, Intel, chiplets, upstarts, analog AI, optical computing, and AI chips designed by AI. By George Anadiotis The interest and investment in AI is skyrocketing, and generative AI is fueling it. Over one-third of CxOs have reportedly already embraced GenAI in their operations, with nearly half […]

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