William J. Frawley, Gregory Piatetsky-Shapiro, and Christopher J. Matheus After a decade of fundamental interdisciplinary research in machine learning, the spadework in this field has been done; the 1990s should see the widespread exploitation of knowledge discovery as an aid to assembling knowledge bases. The contributors to the AAAI Press book Knowledge Discovery in Databases were excited at the potential benefits of this research. The editors hope that some of this excitement will communicate itself to AI Magazine readers of this article. Computers have promised us a fountain of wisdom but delivered a flood of data. The size and number of databases probably increases even faster.

Recent advances in enterprise web-based software have created a need for sophisticated yet user-friendly data-quality solutions. A new category of data-quality solutions that fill this need using intelligent matching and retrieval algorithms is discussed. Solutions are focused on customer and sales data and include realtime inexact search, batch processing, and data migration. Users are empowered to maintain higher quality data resulting in more efficient sales and marketing operations. Sales managers spend more time with customers and less time managing data.

I am honored by the appointment and look forward to the opportunity to guide the magazine as it begins its third decade of publication. AI Magazine serves the artificial intelligence community in many ways. It is a medium for disseminating information about AI areas and methods to readers across the entire field of AI, as well as to a broad multidisciplinary audience. It is a journal of record for articles on important research and applications advances as well as for meeting reports, reviews, and discussions that illuminate the state of the art and emerging areas. Equally important, it is a forum for sharing visions for the field--perspectives on issues, priorities, and challenges for moving forward.

XML, web services, and the semantic web have opened the door for new and exciting information-integration applications. Information sources on the web are controlled by different organizations or people, utilize different text formats, and have varying inconsistencies. Therefore, any system that integrates information from different data sources must identify common entities from these sources. Data from many data sources on the web does not contain enough information to link the records accurately using state-of-the-art record-linkage systems. However, it is possible to exploit secondary data sources on the web to improve the record-linkage process.

A serious issue with the voice assistant's touch panel meant a "small number" of them went rogue, and kept monitoring their users even when they weren't supposed to. The Google Home Mini had originally been programmed to record you when you either said "Okay Google" or "Hey Google", or tapped and held a touch panel on it. "We've decided to permanently remove all top touch functionality on Google Home Mini," said Google. The Home Mini, a miniature version of Google Home, the company's smart voice assistant, will come out on 19 October, costing £49.

The team has developed an app called PupilScreen that uses video and a smartphone's camera flash to record and calculate how the pupils respond to light. Assessing head trauma due to, for example, sports injuries or a car crash is typically done with either a pupilometer -- rarely found outside of hospitals -- or a mix of subjective evaluations like balancing, repeating a list of words or visually examining a pupil's response with a flashlight. To create PupilScreen and provide an objective assessment of potential head trauma, the researchers used deep learning tools to train a neural network how to find the pupil of the eye and track how it responds to a flash of light over the course of three seconds. A smartphone camera records the three second video and the light is provided by the camera's flash.