Actors from the world of gaming went on strike last week, in a row about the use of artificial intelligence (AI) and the threat it poses to their livelihoods. It has reignited the debate about how the entertainment industry is adapting to new technology. When actor Jennifer Hale talks, you listen. Her delivery is measured and surgically precise, yet her tone has a warmth that most ASMR creators would envy. She could read the phone book and you'd pay attention.

Despite differing from the human language processing mechanism in implementation and algorithms, current language models demonstrate remarkable human-like or surpassing language capabilities. Should computational language models be employed in studying the brain, and if so, when and how? To delve into this topic, this paper reviews efforts in using computational models for brain research, highlighting emerging trends. To ensure a fair comparison, the paper evaluates various computational models using consistent metrics on the same dataset. Our analysis reveals that no single model outperforms others on all datasets, underscoring the need for rich testing datasets and rigid experimental control to draw robust conclusions in studies involving computational models.

Humans understand sentences word-by-word, in the order that they hear them. This incrementality entails resolving temporary ambiguities about syntactic relationships. We investigate how humans process these syntactic ambiguities by correlating predictions from incremental generative dependency parsers with timecourse data from people undergoing functional neuroimaging while listening to an audiobook. In particular, we compare competing hypotheses regarding the number of developing syntactic analyses in play during word-by-word comprehension: one vs more than one. This comparison involves evaluating syntactic surprisal from a state-of-the-art dependency parser with LLM-adapted encodings against an existing fMRI dataset. In both English and Chinese data, we find evidence for multipath parsing. Brain regions associated with this multipath effect include bilateral superior temporal gyrus.

Misinformation and disinformation are growing threats in the digital age, spreading rapidly across languages and borders. This paper investigates the prevalence and dynamics of multilingual misinformation through an analysis of over 250,000 unique fact-checks spanning 95 languages. First, we find that while the majority of misinformation claims are only fact-checked once, 11.7%, corresponding to more than 21,000 claims, are checked multiple times. Using fact-checks as a proxy for the spread of misinformation, we find 33% of repeated claims cross linguistic boundaries, suggesting that some misinformation permeates language barriers. However, spreading patterns exhibit strong homophily, with misinformation more likely to spread within the same language. To study the evolution of claims over time and mutations across languages, we represent fact-checks with multilingual sentence embeddings and cluster semantically similar claims. We analyze the connected components and shortest paths connecting different versions of a claim finding that claims gradually drift over time and undergo greater alteration when traversing languages. Overall, this novel investigation of multilingual misinformation provides key insights. It quantifies redundant fact-checking efforts, establishes that some claims diffuse across languages, measures linguistic homophily, and models the temporal and cross-lingual evolution of claims. The findings advocate for expanded information sharing between fact-checkers globally while underscoring the importance of localized verification.

To model behavioral and neural correlates of language comprehension in naturalistic environments researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFG), yet such formalisms are not sufficiently expressive for human languages. Combinatory Categorial Grammars (CCGs) are sufficiently expressive directly compositional models of grammar with flexible constituency that affords incremental interpretation. In this work we evaluate whether a more expressive CCG provides a better model than a CFG for human neural signals collected with fMRI while participants listen to an audiobook story. We further test between variants of CCG that differ in how they handle optional adjuncts. These evaluations are carried out against a baseline that includes estimates of next-word predictability from a Transformer neural network language model. Such a comparison reveals unique contributions of CCG structure-building predominantly in the left posterior temporal lobe: CCG-derived measures offer a superior fit to neural signals compared to those derived from a CFG. These effects are spatially distinct from bilateral superior temporal effects that are unique to predictability. Neural effects for structure-building are thus separable from predictability during naturalistic listening, and those effects are best characterized by a grammar whose expressive power is motivated on independent linguistic grounds.

The English actor who stars in the hit Bayonetta video game series has asked fans not to buy the latest release in the franchise, after revealing that she was offered just $4,000 (£3,500) to reprise the role. In an emotional series of videos posted to social media, Hellena Taylor, who voiced the title character of Bayonetta,said she had been replaced in the forthcoming third game in the series because she the proposed fee was an "insult". "The Bayonetta franchise made an approximated $450m," Taylor said, "and that's not including merchandise. As an actor I trained for a total of seven and a half years – three years at the London Academy of Music and Dramatic Arts with voice coach Barbara Berkery, and four and a half years with the legendary Larry Moss in Los Angeles. "And what did they think this was worth?

This panel discussion brings focuses the attention of AI researchers and other cognitive scientists on natural language. How can language be studied using integrated cognitive architectures? What do such architectures have to say about traditional questions in language and language processing?

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A Tennessee man was sentenced Tuesday to 45 months in prison for leaking classified information about the U.S. drone program in Afghanistan while he was working as an Air Force intelligence analyst. Daniel Hale, 33, pleaded guilty in March to violating the Espionage Act by leaking top-secret documents to a reporter. Hale, who was sentenced in U.S. District Court in Alexandria, said his guilt over participating in lethal drone strikes in Afghanistan led him to leak government secrets.

Now that Mass Effect Legendary Edition, the remaster of BioWare's groundbreaking space trilogy, is out, the video game series likely to reach a whole lot of first-time players--especially considering the current drought in new game releases. You're in for an incredible RPG experience packed with adventure, gunfights, telekinesis, ethical quandaries, space politics, and romanceable aliens. In Mass Effect, your choices have real consequences on the story, and you should feel free to experiment accordingly. But here's one choice you absolutely shouldn't make: Do not, under any circumstances, play the protagonist as a guy. Look, there's nothing wrong with men. It's totally okay to be a man, and in most circumstances, it's perfectly okay to choose to play a male character in a video game when given multiple gender options.

A team of researchers has completed the understanding of the Keller Conjecture, first proposed in 1930, about the packing of squares, cubes, and their higher-dimensional analogues. The conjecture states that any tiling of identical hypercubes that fills space must contain a pair of neighbors that share an entire face. You might convince yourself it is true for two or three dimensions by toying with squares or blocks. Mathematicians later established the status of the conjecture for all dimensions except seven. The new result, which shared the best paper award at the 2020 International Joint Conference on Automated Reasoning (IJCAR 2020), fills that gap.