Latest Articles & Insights

Say Hello to Ask NLPatent: Your AI Patent Sidekick

Ask NLPatent lets you chat with any patent document, while Bulk Ask runs one natural-language question across your entire result set at once.

How NLPatent Was Used to Patent NLPatent

The story of how Potter Clarkson attorney Angus Gledhill used NLPatent itself to run prior art and draft the claims for NLPatent's own patent application.

AI, Data, and the Enlightenment Era of IP Strategy

IP strategy is shifting from filing volume to AI-driven analysis, and the quality of those insights depends on how complete and structured the underlying data is.

The End of the Keyword Era (Kinda)

Why keyword search still wins in some cases but breaks on patent language, and why true semantic search must be built from the ground up.

Reinventing IP Workflow Without Reinventing the Wheel

Automation fails in patent work when it ignores how professionals actually work. Where AI adds value, and where domain expertise separates real tools from noise.

The AI Terminology Mistakes Everyone Needs to Stop Making

A crash course on the real hierarchy between AI, ML, neural networks, deep learning, NLP, and LLMs, and why using the terms correctly matters.

Changemakers: Meet 20 emerging leaders reinventing how Canada does business

Charging Ahead or Slowing Progress? The Patent Battles Shaping EV Infrastructure

The lawsuits, standard-essential patents, and licensing strategies from Tesla, ChargePoint, and WiTricity that are shaping the EV charging network race.

Legaltech Hub Product Briefing - NLPatent

Why Size Matters in Large Language Models

What parameter count actually buys you in an LLM, plus the compute cost, water use, and environmental tradeoffs behind training GPT-scale models.

How Self-Supervised Learning has "Transformed" Natural Language Processing

How transformer-based LLMs learn language context through token masking, and why the shift is often called NLP's ImageNet moment.

Tracing the (Surprisingly) Long History of Language-Based AI

A timeline from 1883 semantics through Turing, ELIZA, RNNs, and transformers, showing that today's language AI builds on over a century of ideas.