Google DeepMind Just Showed How AI Will Read – and Rank – Your Content Directly

The BlockRank Paper signals search’s next leap: From synthesis towards comprehension. Google DeepMind has published research that signals the next stage of search. The paper – Scalable In-Context Ranking with Generative Models – describes a breakthrough in what’s known as In-context Ranking (ICR). This is a system where the model reads and evaluates content directly, […]

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Google DeepMind's diagram for BlockRank (right) shows how it differs from standard models (middle). Its 'Structured Attention' component forces the model to focus on comparing each document to the query, rather than comparing every document to every other document. This change is what makes 'comprehension-based' ranking efficient and scalable

The Psychology of AI Search: How Behavioural Economics Explains the New Rules of Online Conversion

In a recent paper for my Master of Behavioural Economics at UTS, I explored a topic at the core of a seismic shift in the online economy: the intersection of AI, human decision-making, and the future of search. The findings reframe a problem causing widespread anxiety across digital marketing: the Great Decoupling – where website

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Applying Daniel Kahneman’s System 1 vs System 2: AI search pre-loads the heavy System 2 work, so users arrive in fast, intuitive System 1 mode – primed to trust, act, and convert

How AI Search Is Rewriting SEO – Insights from a Journalist and Behavioural Economist

For a long time, I didn’t feel I had much to contribute to SEO. Coming from a journalism background – writing for organisations like the ABC, The Guardian, and NPR – I was trained to value depth, originality, and clarity. But when I first began exploring digital content strategy, SEO felt like a field dominated

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Andrew Tomison (formerly known as Thompson) reporting from the field in Melbourne for ABC News TV.