Artificial Intelligence

Explore the rapidly evolving world of artificial intelligence, machine learning, and automation. From AI ethics to real-world applications, this category delivers insights that matter for today and tomorrow.

Cyber-Insecurity in the AI Era

Cybersecurity was already under strain before AI entered the stack. Now, as AI expands the attack surface and adds new complexity, the limits of legacy approaches are becoming harder to ignore. This session from MIT Technology Review’s EmTech AI conference…

Operationalizing AI for Scale and Sovereignty

Companies are taking control of their own data to tailor AI for their needs. The challenge lies in balancing ownership with the safe, trusted flow of high‑quality data needed to power reliable insights. This conversation from MIT Technology Review’s EmTech…

This startup’s new mechanistic interpretability tool lets you debug LLMs

The San Francisco–based startup Goodfire just released a new tool, called Silico, that lets researchers and engineers peer inside an AI model and adjust its parameters—the settings that determine a model’s behavior—during training. This could give model makers more fine-grained…

Effective KV Compression with TurboQuant

TurboQuant has recently been launched by Google as a novel algorithmic suite and library for applying advanced quantization and compression to large language models (LLMs) and vector search engines — an indispensable element of RAG systems.

The missing step between hype and profit

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. In February, I picked up a flyer at an anti-AI march in London. I can’t say for…

Rebuilding the data stack for AI

Artificial intelligence may be dominating boardroom agendas, but many enterprises are discovering that the biggest obstacle to meaningful adoption is the state of their data. While consumer-facing AI tools have dazzled users with speed and ease, enterprise leaders are discovering…