As large language models become more capable, users are tempted to delegate knowledge tasks where models process documents on their behalf and provide the finished results. But how far can you trust the model to stay faithful to the content of your documents when it has to iterate over them across multiple rounds?A new study by researchers at Microsoft shows that large language models silently corrupt documents that they work on by introducing errors. The researchers developed a benchmark that simulates multi-step autonomous workflows across 52 professional domains, using a method that automatically measures how much content degrades over time.Their findings show that even top-tier frontier models corrupt an average of 25% of document content by the end of these workflows. And providing mo [...]
For three years, Microsoft's artificial intelligence story has been inseparable from OpenAI. The partnership — cemented by a cumulative investment exceeding $13 billion — gave Microsoft early [...]
Mistral AI on Tuesday released OCR 4, a document intelligence model that moves beyond raw text extraction to return structured representations of entire documents — complete with bounding boxes, blo [...]
Amazon Web Services on Tuesday announced a new class of artificial intelligence systems called "frontier agents" that can work autonomously for hours or even days without human intervention, [...]
Agent skills have become an important part of real-world AI applications, providing a mechanism — a set of instructions saved in a folder of text-based markdown (.md) files, usually — for models t [...]
If you thought Anthropic was about to run away with the enterprise AI business...you're not totally off the mark, actually.This morning, Microsoft announced "Copilot Cowork" a new cloud [...]