Three books unpack our infatuation with prediction, and what we lose when we outsource this task to machines. To be human is, fundamentally, to be a forecaster. Trying to see the future, whether through the lens of past experience or the logic of cause and effect, has helped us hunt, avoid hunted, plant crops, forge social bonds, and in general survive in a world that does not prioritize our survival. Indeed, as the tools of divination have changed over the centuries, from tea leaves to data sets, our conviction that the future can be known (and therefore controlled) has only grown stronger. Today, we are awash in a sea of predictions so vast and unrelenting that most of us barely even register them. As I write this sentence, algorithms on some remote server are busy trying to guess my next word based on those I have already typed.

Things to Do in L.A. Tap to enable a layout that focuses on the article. New LAFD chief won't look into who watered down Palisades fire report Deputy Chief Jaime Moore fields questions from city council members before being confirmed as the new LAFD chief after a unanimous vote by the L.A. City Council on Nov. 14. This is read by an automated voice. Please report any issues or inconsistencies here . LAFD Chief Jaime Moore said he is taking a forward-looking approach and not seeking to assign blame for changes to the report.

After the rapper's 1979 hit "Christmas Rappin'," his song "The Breaks" was the first rap single to go gold. In a rehearsal studio in the Echo Park neighborhood in Los Angeles, Kurtis Blow was limbering up and getting loose. Earlier this year, his left arm swelled up abruptly, requiring four surgeries to resolve what was eventually diagnosed as deep-vein thrombosis. Blow usually holds the mike in his right hand when he raps, but he had to get his left arm going, he said, "because it's my'Throw your hands in the air' arm." Lithe at age sixty-six, Blow was dressed in leather cargo pants, a track jacket, and a black baseball cap with the words " above its brim. He was whipping himself into shape for a "Legends of Hip-Hop" concert to be held just after Thanksgiving at the Peacock Theatre, in downtown L.A. He will be on a stage that will also feature such foundational rappers as Big Daddy Kane, Doug E. Fresh, and two members of the Furious Five, Melle Mel and Scorpio. Blow's youngest son, Michael, the studio's owner, manned the d.j. The rapper's eldest, Kurtis, Jr., nodded his do-ragged head to the beat and offered counsel alongside his mother, Kurtis, Sr.,'s wife of forty-two years, Shirley. It has been forty-five years since the release of Blow's song "The Breaks," the first rap single to be certified gold. Blow had already scored a novelty hit, "Christmas Rappin'," at the end of 1979, the watershed year in which rap transitioned from clubs in the Bronx and Harlem to singles pressed on vinyl, chief among them "Rapper's Delight," by the Sugarhill Gang. "I had a singles deal with escalating options," Blow recalled. "I had to sell thirty thousand records in order to do another single.

Researchers from Australia's national science agency CSIRO, Federation University Australia and RMIT University have developed a method to improve the detection of audio deepfakes. The new technique, Rehearsal with Auxiliary-Informed Sampling (RAIS), is designed for audio deepfake detection -- a growing threat in cybercrime risks such as bypassing voice-based biometric authentication systems, impersonation and disinformation. It determines whether an audio clip is real or artificially generated (a'deepfake') and maintains performance over time as attack types evolve. In Italy earlier this year, an AI-cloned voice of its Defence Minister requested a €1M'ransom' from prominent business leaders, convincing some to pay. This is just one of many examples, highlighting the need for audio deepfake detectors.

The Aedes aegypti mosquito that can carry dengue, yellow fever, and Zika was thought to be too reliant on a hot and wet climate to survive in the Mountain West. But now, a population is thriving in Western Colorado. Hannah Livesay, biologist at the Grand River Mosquito Control District, points out the characteristic white markings of an Aedes aegypti mosquito shown under a microscope at her lab in Grand Junction, Colo. It can carry life-threatening diseases. It's difficult to find and hard to kill.

Adapting large-scale foundation models in multi-task scenarios often suffers from task conflict and oblivion. To mitigate such issues, we propose a novel ''model MoE-ization'' strategy that leads to a conflict- and oblivion-resistant multi-task adaptation method. Given a weight matrix of a pre-trained model, our method applies SVD to it and introduces a learnable router to adjust its singular values based on tasks and samples. Accordingly, the weight matrix becomes a Mixture of Orthogonal Rank-one Experts (MoORE), in which each expert corresponds to the outer product of a left singular vector and the corresponding right one. We can improve the model capacity by imposing a learnable orthogonal transform on the right singular vectors. Unlike low-rank adaptation (LoRA) and its MoE-driven variants, MoORE guarantees the experts' orthogonality and maintains the column space of the original weight matrix. These two properties make the adapted model resistant to the conflicts among the new tasks and the oblivion of its original tasks, respectively. Experiments on various datasets demonstrate that MoORE outperforms existing multi-task adaptation methods consistently, showing its superiority in terms of conflict- and oblivion-resistance. The code of the experiments is available at https://github.com/DaShenZi721/MoORE.

Contemporary language models are fluent yet routinely mis-handle the types of meaning their outputs entail. We argue that hallucination, brittle moderation, and opaque compliance outcomes are symptoms of missing type-theoretic semantics rather than data or scale limitations. Building on Montague's view of language as typed, compositional algebra, we recast alignment as a parsing problem: natural-language inputs must be compiled into structures that make explicit their descriptive, normative, and legal dimensions under context. We present Savassan, a neuro-symbolic architecture that compiles utterances into Montague-style logical forms and maps them to typed ontologies extended with deontic operators and jurisdictional contexts. Neural components extract candidate structures from unstructured inputs; symbolic components perform type checking, constraint reasoning, and cross-jurisdiction mapping to produce compliance-aware guidance rather than binary censorship. In cross-border scenarios, the system "parses once" (e.g., defect claim(product x, company y)) and projects the result into multiple legal ontologies (e.g., defamation risk in KR/JP, protected opinion in US, GDPR checks in EU), composing outcomes into a single, explainable decision. This paper contributes: (i) a diagnosis of hallucination as a type error; (ii) a formal Montague-ontology bridge for business/legal reasoning; and (iii) a production-oriented design that embeds typed interfaces across the pipeline. We outline an evaluation plan using legal reasoning benchmarks and synthetic multi-jurisdiction suites. Our position is that trustworthy autonomy requires compositional typing of meaning, enabling systems to reason about what is described, what is prescribed, and what incurs liability within a unified algebra of meaning.

Estimating the governing equation parameter values is essential for integrating experimental data with scientific theory to understand, validate, and predict the dynamics of complex systems. In this work, we propose a new method for structural system identification (SI), uncertainty quantification, and validation directly from data. Inspired by generative modeling frameworks, a neural network maps random noise to physically meaningful parameters. These parameters are then used in the known equation of motion to obtain fake accelerations, which are compared to real training data via a mean square error loss. To simultaneously validate the learned parameters, we use independent validation datasets. The generated accelerations from these datasets are evaluated by a discriminator network, which determines whether the output is real or fake, and guides the parameter-generator network. Analytical and real experiments show the parameter estimation accuracy and model validation for different nonlinear structural systems.

The semiconductor industry is experiencing a significant transformation, raising questions about the advantages traditionally associated with Moore's Law and Dennard scaling. This shift highlights four key trends that intersect with technology, economics, and society. The first trend is the perceived end of Moore's Law. Analysis indicates that the benefits of advances in semiconductor technology--specifically in terms of cost, energy efficiency, and density--are diminishing (see Table 1). This suggests a departure from the era where technological advances consistently delivered substantial economic and performance improvements.

But can the struggling industry make a comeback? EXCLUSIVE: The House Energy and Commerce Committee is set to revive the National Coal Council and "reinvigorate America's beautiful clean coal industry," as President Donald Trump put it. Committee Chairman Brett Guthrie, R-Ky., told Fox News Digital the National Coal Council legislation will successfully pass out of his committee Wednesday and have a good chance of passing the full House. Michael Rulli, R-Ohio, and Riley Moore, R-W.V., are leading the legislation to reestablish the council, effectively canceled by former President Joe Biden, and support the clean coal industry for a multitude of reasons, including energy security at a time of Middle East uncertainty. Rulli told Fox News Digital the Biden administration's endeavors against the council and the coal industry writ-large were a "deliberate" effort to "wipe out coal, kill jobs, and make America dependent on foreign energy."