You are about to hear a lot more about Claude Code. Over the holidays, Alex Lieberman had an idea: What if he could create Spotify "Wrapped" for his text messages? Without writing a single line of code, Lieberman, a co-founder of the media outlet, created "iMessage Wrapped"--a web app that analyzed statistical trends across nearly 1 million of his texts. One chart that he showed me compared his use of,,, and --he's an guy. Another listed people he had ghosted.

Moral panic Mortal Kombat sparked widespread controversy on its release. Moral panic Mortal Kombat sparked widespread controversy on its release. On its release in 1993, Midway's gore-filled fighting game ushered in a new era of hyperviolent gaming that continues to influence the industry to this day O n 9 December 1993, Democratic senator Joe Lieberman sat before a congressional hearing on video game violence and told attendees that the video game industry had crossed a line. The focus of his ire was Mortal Kombat, Midway's bloody fighting game, recently released on the Sega Genesis and Super Nintendo Entertainment System after a successful run in the arcades. "Blood splatters from the contestants' heads," he told the room. "The game narrator instructs the player to finish his opponent.

About the author: Michael D. Lieberman has more than 29 years of experience as a researcher, statistician, and strategist in the marketing, advertising, and political research fields. He has worked extensively with clients in advertising attribution and advertising testing, data translation, financial services, information technology, food service, telecommunications, human resource, political polling, and public relations. He founded Multivariate Solutions in 1998 and now works with an international clientele including advertising firms, political strategy groups, and full service market research companies. Michael Lieberman is an Amazon featured author and has written more than 90 professional articles.

Perhaps befitting a full-time techie, his work has a more positive spin than that of some others working with A.I. His Artechouse piece "Expression Mirror," originally created for the 2018 London Design Biennale, reads the facial expressions of a user, tracking muscle movements at 68 points on the face. But when people look at the "mirror," they do not see themselves. "Your face is replaced with someone's face who has used it before," Mr. Lieberman said. "It matches your expressions, like a smile or frown, and it learns as it interacts." He calls this a "face action coding system," a version of a "fingerprint."

This is the next post of a series of Trends & Perspectives blog posts. The Track Chairs will reflect on each of this years' presentation tracks, analyze and discuss some of the trends that you can expect to hear about at OLC Accelerate this year, and also get the perspectives of the Best-in-Track winners. This blog post features the presenters for the Best In Track selection for the Teaching and Learning Effectiveness Track at the upcoming OLC Accelerate Conference. Their express workshop, Show it Off! Showcase Your Artificial Intelligence, will be held on Wednesday, November 20th from 1:15-2:00pm in Southern Hemisphere 1.

The Open Geospatial Consortium's (OGC) Innovation Program is testing ways to increase public safety by sharing data that smart cities collect. The project, called the Smart City Interoperability Reference Architecture (SCIRA), is part of a long-running partnership with the Homeland Security Department's Science and Technology Directorate. The program aims to develop standards and practices to improve first responders' awareness and communication by studying how shared data can drive decisions and make disaster response more effective. "That really rests on being able to build a framework of systems that work together," Innovation Program Director Josh Lieberman said. The plan is to bring together data from sensors and other sources along with insights from people.

This is an opinion piece about the relationship between the fields of human-computer interaction (HCI) and artificial intelligence (AI). The ultimate goal of both fields is to make user interfaces more effective and easier for people to use. But historically, researchers have disagreed about whether "intelligence" or "direct manipulation" is the better route to achieving this. There is an unjustified perception in HCI that AI is unreliable. There is an unjustified perception in AI that interfaces are merely cosmetic.

A longstanding dream of artificial intelligence has been to put commonsense knowledge into computers--enabling machines to reason about everyday life. Some projects, such as Cyc, have begun to amass large collections of such knowledge. However, it is widely assumed that the use of common sense in interactive applications will remain impractical for years, until these collections can be considered sufficiently complete and commonsense reasoning sufficiently robust. Recently, at the Massachusetts Institute of Technology's Media Laboratory, we have had some success in applying commonsense knowledge in a number of intelligent interface agents, despite the admittedly spotty coverage and unreliable inference of today's commonsense knowledge systems. This article surveys several of these applications and reflects on interface design principles that enable successful use of commonsense knowledge.

Computers soon could deliver smarter healthcare to patients at Massachusetts General Hospital (MGH). The two Boston-based institutions in May announced a 10-year collaboration to develop and integrate artificial intelligence throughout Partners' clinical operations. Partners hopes A.I. can improve patient outcomes and increase clinician productivity. The nonprofit healthcare system plans to first use A.I. to enhance diagnostic imaging, with intelligent systems being developed to detect, for example, even minute changes in tumors and then use data analysis to determine optimal treatments tailored to each case. This is the future of medicine, but it's been a long time in the making.

SACRAMENTO - Thousands of employees work at the 1 million-square-foot Amazon fulfillment center in Tracy. But there are many more, who don't get paid for the work they do. Hundreds of automated machines roving around the fulfillment center can transport a vertical shelf of items up to 750 pounds. They roam the gigantic building on a pre-calculated route, using floor sensors. It's artificial assistance, that has drastically changed how much product Amazon can bring in and ship out.