A few weeks ago, I witnessed Google Search make what could have been the most expensive error in its history. In response to a query about cheating in chess, Google's new AI Overview told me that the young American player Hans Niemann had "admitted to using an engine," or a chess-playing AI, after defeating Magnus Carlsen in 2022--implying that Niemann had confessed to cheating against the world's top-ranked player. Suspicion about the American's play against Carlsen that September indeed sparked controversy, one that reverberated even beyond the world of professional chess, garnering mainstream news coverage and the attention of Elon Musk. Except, Niemann admitted no such thing. Quite the opposite: He has vigorously defended himself against the allegations, going so far as to file a 100 million defamation lawsuit against Carlsen and several others who had accused him of cheating or punished him for the unproven allegation--Chess.com, for example, had banned Niemann from its website and tournaments.

This article was co-published with Understanding AI, a newsletter that explores how A.I. works and how it's changing our world. When Silicon Valley executives testify before Congress, they normally get raked over the coals. But OpenAI CEO Sam Altman's Tuesday appearance before the Senate Judiciary Committee went differently. Senators asked Altman probing questions and listened respectfully to his answers. Afterward, the committee's chairman, Sen. Richard Blumenthal of Connecticut praised Altman.

Description Logic (DL) based ontologies and non-monotonic rules provide complementary features whose combination is crucial in many applications. In hybrid knowledge bases (KBs), which combine both formalisms, for large real-world applications, often integrating knowledge originating from different sources, inconsistencies can easily occur. These commonly trivialize standard reasoning and prevent us from drawing any meaningful conclusions. When restoring consistency by changing the KB is not possible, paraconsistent reasoning offers an alternative by allowing us to obtain meaningful conclusions from its consistent part. In this paper, we address the problem of efficiently obtaining meaningful conclusions from (possibly inconsistent) hybrid KBs. To this end, we define two paraconsistent semantics for hybrid KBs which, beyond their differentiating properties, are faithful to well-known paraconsistent semantics as well as the non-paraconsistent logic they extend, and tractable if reasoning in the DL component is.

We study the problem of rewriting an ontology O1 expressed in a DL L1 into an ontology O2 in a Horn DL L2 such that O1 and O2 are equisatisfiable when extended with an arbitrary dataset. Ontologies that admit such rewritings are amenable to reasoning techniques ensuring tractability in data complexity. After showing undecidability whenever L1 extends ALCF, we focus on devising efficiently checkable conditions that ensure existence of a Horn rewriting. By lifting existing techniques for rewriting Disjunctive Datalog programs into plain Datalog to the case of arbitrary first-order programs with function symbols, we identify a class of ontologies that admit Horn rewritings of polynomial size. Our experiments indicate that many real-world ontologies satisfy our sufficient conditions and thus admit polynomial Horn rewritings.

Dogs have evolved muscles around their eyes to look cute to humans, scientific research has shown for the first time. The muscles allow dogs to raise a quizzical eyebrow and to look sad - giving them facial expressions similar to our own. The authors say that the eyebrow raising movement triggers a nurturing response in humans. They makes the dogs' eyes appear larger and more child-like. The authors say that the eyebrow raising movement triggers a nurturing response in humans.

Dogs change their facial expressions when they know people are looking at them--perhaps in an effort to communicate. For instance, canines in the study would make the classic "sad puppy face"--raising their inner eyebrows to make their eyes look larger and more infant-like--when looking into a human's eyes. The discovery adds to scientists' ever-growing understanding of man's best friend, one of our species's longest companions. Humans and dogs have lived side by side by some 30,000 years, and along the way, evolution seems to have sculpted dogs' behavior. Research has shown that dogs constantly monitor humans, intently watch our gestures, and in comparison to hand-reared wolf puppies, tend to look up at human faces more often.

Dog owners swear that their furry best friend is in tune with their emotions. Now it seems this feeling of interspecies connection is real: dogs can smell your emotional state, and adopt your emotions as their own. Science had already shown that dogs can see and hear the signs of human emotions, says Biagio D'Aniello of the University of Naples "Federico II", Italy. But nobody had studied whether dogs could pick up on olfactory cues from humans. "The role of the olfactory system has been largely underestimated, maybe because our own species is more focused on the visual system," says D'Aniello.

When Artificial Intelligence (AI) was just science fiction, nobody thought it would become a real force in the business world. But nearly 50 years after Hal in "2001: A Space Odyssey," fantasy has morphed into a positive reality, and AI is now a business game-changer. While AI is not yet the omniscient (or ominous) presence it was in "2001," the facts are that IT management can help business partners in sales and marketing be more successful by implementing AI solutions, and here is an example of one that is easy to slot right in and show immediate value: Conversica. Conversica is the leader in conversational AI for business, because we are truly at the vanguard of deploying AI to help businesses find customers and drive revenue. Friendly, persistent, conversation-based AI is the perfect tool for following up on sales leads that would otherwise be left to die, with the true value of AI-enabled sales being that it drives greater ROI from marketing and sales programs.

Imagine talking to a tiger, chatting to a cheetah, as Dr Doolittle once sang – what a neat achievement that would be. Well, Amazon has revealed that the animal-loving doctor's ambition might not be entirely fantasy. Pet translators that can turn woofs into words and make sense of miaows, might really be on the horizon, according to a report backed by the internet retailer. Futurologist William Higham of Next Big Thing, who co-authored the report for Amazon, says he believes devices that can talk dog could be less than 10 years away. "Innovative products that succeed are based around a genuine and major consumer needs. The amount of money now spent on pets – they are becoming fur babies to so many people – means there is huge consumer demand for this. Somebody is going to put this together," he says.

Former Enron executive Vincent Kaminski is a modest, semi-retired business school professor from Houston who recently wrote a 960-page book explaining the fundamentals of energy markets. His most lasting legacy, however, may involve thousands of e-mails he wrote more than a decade ago at the energy-services company. Kaminski, a former managing director for research who warned repeatedly about concerning practices he saw at Enron, is among more than 150 senior executives whose e-mail boxes were dumped onto the Internet by the Federal Energy Regulatory Commission (FERC) on March 26, 2003. In the name of serving the public's interest during its investigation of Enron, the federal agency made the controversial decision to post online more than 1.6 million e-mails that Enron executives sent and received from 2000 through 2002. FERC eventually culled the trove to remove the most sensitive and personal data, after receiving complaints (see PDF).