A Deep Dive into Meta’s Latest AI Breakthrough

Introduction The integration of artificial intelligence into healthcare represents one of the most transformative technological shifts in modern medicine. As AI applications proliferate across medical specialities, healthcare practitioners face an increasingly complex landscape of tools, technologies, and approaches.

How to create a functional documentation assistant without writing code

Understanding How the Research Organisation Registry is Used Across the Web

Hands-On with Gemini 2.5 Pro: Exploring Google’s New Frontier in AI

This article summarises research from “Generated Knowledge Prompting for Commonsense Reasoning” by Jiacheng Liu and colleagues from the University of Washington

Introduction Imagine a world where every piece of research—every article, dataset, researcher, and institution—is seamlessly connected, no matter where it resides or how the digital landscape shifts. This isn’t a distant dream; it’s the reality being forged by persistent identifiers (PIDs). These unassuming strings of characters are revolutionizing how we create, share, and build upon knowledge.

This blog post is based on and summarises the paper Connected Research: The Potential of the PID Graph” by Helena Cousijn, Ricarda Braukmann, Martin Fenner, Christine Ferguson, René van Horik, Rachael Lammey, Alice Meadows, and Simon Lambert, published in 2021.

This article summarises research from "Tree of Thoughts: Deliberate Problem Solving with Large Language Models" by Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L. Griffiths, Yuan Cao, and Karthik Narasimhan.

This article explores and analyses the paper 'Active Prompting with Chain-of-Thought for Large Language Models' by Shizhe Diao, Pengcheng Wang, Yong Lin, Rui Pan, Xiang Liu, Tong Zhang.

A New Way to Teach AI How to Think, Not Just Respond. This article is based on the paper Meta Prompting for AI Systems, published by Tsinghua University and Shanghai Qi Zhi Institute.