The Quality Imperative: Why Leading Organizations Proactively Evaluate Software and AI Systems, And How You Can Too
As enterprise systems shift from deterministic software to probabilistic AI, forward-thinking organizations leverage proactive quality assessment to maximize value, minimize risk and ensure regulatory compliance. By George Anadiotis In today’s rapidly evolving technological landscape, ensuring the quality of both traditional software and AI systems has become more critical than ever. Organizations are increasingly relying on complex […]
Read More →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 […]
Read More →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 • […]
Read More →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 […]
Read More →You.com raises $50M to lead AI for Knowledge Workers
You.com showcases the state of AI today By George Anadiotis The story of you.com is multi-faceted and telling in many ways. You.com was founded in 2020 by Richard Socher, one of the leading NLP (Natural Language Processing) researchers in the world, to offer a better search experience to users and compete with Google. With a startup […]
Read More →Evaluating 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, […]
Read More →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 […]
Read More →AI Chips in 2024: NVIDIA, MLPerf benchmarks, Huang’s law, and competition
What we learned on AI Chips in 2024 by keeping track of NVIDIA’s latest announcements, talking to industry experts, and scanning news and analyses By George Anadiotis Exploring AI chips has been a pastime, as a well as a popular theme in Orchestrate all the Things articles. In 2023, we felt like we fell somewhat […]
Read More →Aerospike Graph: A new entry in the graph database market, aiming to tackle complex problems at scale
“Graph database growth is going strong through the Trough of Disillusionment.” And “Graph Analytics go big and real-time.” These were two of the headlines of the Spring 2023 update of the Year of the Graph newsletter. In combination, they seem like an appropriate summary of the reasoning behind a new entry in the graph database […]
Read More →LinkedIn’s feed evolution: more granular and powerful machine learning, humans still in the loop
LinkedIn’s feed has come a long way since the early days of assembling the machine learning infrastructure that powers it. Recently, a major update to this infrastructure was released. We caught up with the people behind it to discuss how the principle of being people-centric translates to technical terms and implementation. How do data and […]
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