AI
The AI arms race is shaping up like a three-way tug-of-war — and it’s not yet clear who’s going to fall in the mud first. The US, the Middle East, and China each bring something essential to the table. But none of them hold all the
Blog
The data warehouse is no longer the centre of gravity. It’s just one node in a growing constellation. Modern data strategies aren’t about centralising everything in one place. They’re about composability—the ability to mix and match components, adapt to change, and build around the edges. At
Blog
In financial markets, fairness is easy to believe in but hard to define — especially when you're dealing with electronic trading systems that operate faster than the blink of an eye. For most of history, fairness in trading meant access: If you could make it to the floor of
Blog
The data lakehouse is no longer an experiment. It’s fast becoming the blueprint for enterprise data architecture. At the center of this shift are two open technologies: Apache Parquet and Apache Iceberg. Understanding their role today — and where they’re headed — is critical for sizing the opportunity. Parquet: The
AI
I've often found explainability in AI to be an elusive concept—essential, yet difficult to pin down. It underpins trust, adoption, and regulatory compliance, but how does it actually work? A recent paper, Explainable Artificial Intelligence (XAI): From Inherent Explainability to Large Language Models by Fuseini Mumuni and
Quantum
The world of quantum computing is experiencing a surge of momentum, with recent announcements from tech giants Amazon and Microsoft adding fuel to the already rapid pace of innovation. These developments, alongside ongoing research breakthroughs, signal a potential transformation in how we approach computation. One of the most significant trends
Crypto
President Trump's recent announcement of a "Crypto Strategic Reserve" has set the cryptocurrency world alight. This initiative outlines plans for the U.S. government to actively engage in the purchase and sale of cryptocurrencies, aiming to establish the nation as a global leader in the digital
AI
ByteDance's release of AIBrix appears to be a significant advancement in the practical application of Large Language Models (LLMs), particularly within enterprise environments. This Kubernetes-based serving stack, specifically designed to augment vLLM, leverages ByteDance's extensive experience deploying LLMs at scale. The project addresses the critical
AI
Recent discourse within the AI community has centered on model distillation, notably fueled by speculation surrounding DeepSeek's R1 model. Distillation, in essence, is a technique whereby the outputs of a large, high-performing model are utilized to train a smaller, more efficient model. This process, exemplified by the
Weekly 3x3
From Solana futures and fragile payments infrastructure to negative power prices and soaring data-center energy demand, markets are testing new edges. AI research pushes into finance and long-context reliability as real-world constraints bite.
AI
Think about how we learn. We absorb facts, connect them, remember key details, and build a bigger picture over time. Current AI struggles with this. LLMs are good at processing information in front of them, but they have a hard time remembering things from earlier in a long text or
AI
A recent paper from China introduces Sundial, a family of time series models that appears to represent a significant leap forward in time series forecasting. To understand Sundial's potential impact, it's helpful to trace the evolution of this field, which has deep roots stretching back centuries.
