This election cycle will be the first exposed to generative artificial intelligence--the technology behind popular apps like ChatGPT that enables even non-experts to create fake, but realistic-looking text, video, and audio perfectly suited for political manipulation. At the same time, a number of the major social-media companies have retreated from some of their prior commitments to promote "election integrity." The November election is also the first that will register the impact of the enormous popularity of TikTok, which uses a recommendation algorithm that some experts believe is particularly suited to spreading misinformation. Let's start with the rise of generative AI, which allows virtually anyone to produce persuasive text, imagery, or sound based on relatively simple natural-language prompts. In January, Facebook circulated a fake AI-generated image of Donald Trump sitting next to Jeffrey Epstein on the disgraced financier and sex offender's private jet.

Multiple hypothesis testing is a significant problem in nearly all neuroimaging studies. In order to correct for this phenomena, we require a reliable estimate of the Family-Wise Error Rate (FWER). The well known Bonferroni correction method, while simple to implement, is quite conservative, and can substantially under-power a study because it ignores dependencies between test statistics. Permutation testing, on the other hand, is an exact, non-parametric method of estimating the FWER for a given α-threshold, but for acceptably low thresholds the computational burden can be prohibitive. In this paper, we show that permutation testing in fact amounts to populating the columns of a very large matrix P. By analyzing the spectrum of this matrix, under certain conditions, we see that P has a low-rank plus a low-variance residual decomposition which makes it suitable for highly sub-sampled -- on the order of 0.5% -- matrix completion methods. Based on this observation, we propose a novel permutation testing methodology which offers a large speedup, without sacrificing the fidelity of the estimated FWER. Our evaluations on four different neuroimaging datasets show that a computational speedup factor of roughly 50 can be achieved while recovering the FWER distribution up to very high accuracy. Further, we show that the estimated α-threshold is also recovered faithfully, and is stable.

Knowledge bases are an important resource for question answering and other tasks but often suffer from incompleteness and lack of ability to reason over their discrete entities and relationships. In this paper we introduce an expressive neural tensor network suitable for reasoning over relationships between two entities. Previous work represented entities as either discrete atomic units or with a single entity vector representation. We show that performance can be improved when entities are represented as an average of their constituting word vectors. This allows sharing of statistical strength between, for instance, facts involving the "Sumatran tiger" and "Bengal tiger." Lastly, we demonstrate that all models improve when these word vectors are initialized with vectors learned from unsupervised large corpora. We assess the model by considering the problem of predicting additional true relations between entities given a subset of the knowledge base. Our model outperforms previous models and can classify unseen relationships in WordNet and FreeBase with an accuracy of 86.2% and 90.0%, respectively.

The European Parliament has approved sweeping legislation to regulate artificial intelligence, nearly three years after the draft rules were first proposed. Officials reached an agreement on AI development in December. On Wednesday, members of the parliament approved the AI Act with 523 votes in favor and 46 against, There were 49 abstentions. The EU says the regulations seek to "protect fundamental rights, democracy, the rule of law and environmental sustainability from high-risk AI, while boosting innovation and establishing Europe as a leader in the field." The act defines obligations for AI applications based on potential risks and impact.

These problems involve Vandermonde matrices which arise naturally in various statistical modeling settings, including classical polynomial fitting problems, additive models and approximations to recently developed randomized techniques for scalable kernel methods. We show that this structure can be exploited to further accelerate the solution of the regression problem, achieving running times that are faster than "input sparsity".

Measuring similarity is crucial to many learning tasks. To this end, metric learning has been the dominant paradigm. However, similarity is a richer and broader notion than what metrics entail. For example, similarity can arise from the process of aggregating the decisions of multiple latent components, where each latent component compares data in its own way by focusing on a different subset of features. In this paper, we propose Similarity Component Analysis (SCA), a probabilistic graphical model that discovers those latent components from data.

AI-generated deepfake pictures, video or audio of existing people, places or events must be labeled as artificially manipulated. European lawmakers voted on the Artificial Intelligence Act which will lead the world in regulating artificial technology.

An Israeli drone strike has killed a member of Hamas and one other person in southwestern Lebanon near a refugee camp housing displaced Palestinians. It comes amid increased cross-border attacks between Israel and Lebanon.

EXCLUSIVE: House GOP Conference Chair Elise Stefanik, R-N.Y., is criticizing former Attorney General Loretta Lynch for reportedly lobbying the Pentagon on behalf of a company known as DJI, which makes Chinese military tech. "It is disgraceful but unsurprising that Barack Obama's former Attorney General Loretta Lynch is now working on behalf of a Communist Chinese drone company that the Department of Defense has identified as a Chinese military company," Stefanik told Fox News Digital. "Former Attorney General Loretta Lynch is lobbying the DOD to request they remove DJI from this list so the Communist Chinese company can operate with impunity in America. U.S. government officials, both past and present, should be working to ban these Communist Chinese spy drones and bolster the domestic drone industry, not advocating on behalf of a Chinese military company and the Chinese Communist Party." House GOP Conference Chair Elise Stefanik is going after ex-Attorney General Loretta Lynch for a report that links her to a Chinese military firm.

The driver in the Chevy Suburban seemed bent on testing the Waymo robotaxi on the streets of downtown L.A. this week. Playing chicken against Silicon Valley's wheeled robot, he sharply swung into the next lane toward the Waymo. The white driverless Jaguar swerved to avoid the bigger car crossing the line and striking it. The human driver sped then ahead of the robotaxi and braked abruptly in front of it. The machine slowed in time to avoid a collision, shifted into the next lane and the Chevy moved on, ending a brief yet anxiety inducing interaction for a Los Angeles Times reporter and photographer riding in the Waymo vehicle.