❌

Reading view

Why this month's Microsoft patch release is a doozy

Microsoft’s patch for September is a doozy, with a record number of roughly 972 vulnerabilities fixed and 112 of them meeting the high critical-severity threshold.

It was only two months ago that Microsoft patched a then-record 570 vulnerabilities. Then, last month, Microsoft patched some 620 of them. Google and other companies have also published record numbers of vulnerabilities in recent months. Two weeks ago, OpenAI, Anthropic, Amazon Web Services, Google, Microsoft, and 100 companies and organizations published an open letter warning of a narrowing window for patching vulnerabilities ahead of an expected tsunami of AI-enabled attacks that actively exploit them first. The industry is taking the threat seriously by pumping out unprecedented numbers of patches in their software.

Welcome to the new normal

Dustin Childs, a researcher at the Zero Day Initiative, calls the spikes the β€œnew normal” and also cautions that despite them, the damage that’s likely to result from AI-assisted attacks could eventually be substantial.

Read full article

Comments

Β© Getty Images

  •  

Context Windows Don’t Know What’s Still True β€” I Built a Validity Layer That Does

A context window can be technically complete and still describe a world that no longer exists. I built a deterministic benchmark to measure the cost of acting on stale context.

The post Context Windows Don’t Know What’s Still True β€” I Built a Validity Layer That Does appeared first on Towards Data Science.

  •  

Text Watermarking in Python: Catch Whoever Copies Your Writing

AI companies quietly watermark billions of words a day. Here’s how to apply the same three families of techniques to your own writingβ€”and what real experiments reveal about which watermarks survive copy-paste, editing, and paraphrasing.

The post Text Watermarking in Python: Catch Whoever Copies Your Writing appeared first on Towards Data Science.

  •  

A RAG That Says β€œNot in This Document” Has to Show Four Kinds of Evidence

Enterprise Document Intelligence [Vol.1 #B3] - A confident wrong answer is a bug. A bare β€œno answer” with no justification is almost as bad. Each of the four bricks has one piece of evidence to show

The post A RAG That Says β€œNot in This Document” Has to Show Four Kinds of Evidence appeared first on Towards Data Science.

  •  

RAG Is Not the Whole Toolkit: The NLP Techniques Real Problems Still Need

Enterprise Document Intelligence [Vol.1 #B00] - Retrieval answers one kind of question. Classifying a request, matching free text to a reference list, reading a table, cleaning OCR noise: each has a cheaper method that works, and the engineering is knowing which one to reach for

The post RAG Is Not the Whole Toolkit: The NLP Techniques Real Problems Still Need appeared first on Towards Data Science.

  •  

Parse the Folder, Not Just the PDFs: The Relational Tables RAG Needs on a Case File

Enterprise Document Intelligence [Vol.1 #14D] - The index lists what the case type demands before any folder is opened, and the two questions worth building for are not retrieval questions at all

The post Parse the Folder, Not Just the PDFs: The Relational Tables RAG Needs on a Case File appeared first on Towards Data Science.

  •  

Multi-Document RAG: A Folder of Unrelated PDFs Is One Long Document with a Nested Outline

Enterprise Document Intelligence [Vol.1 #14B] - No shared fields means no index to build. One summary line per file plus each file’s own table of contents, and retrieval routes down two levels

The post Multi-Document RAG: A Folder of Unrelated PDFs Is One Long Document with a Nested Outline appeared first on Towards Data Science.

  •  
❌