Things to Do in L.A. Tap to enable a layout that focuses on the article. Former Vice President Kamala Harris addresses delegates with the Democratic National Committee at their winter meeting in downtown Los Angeles on Friday. This is read by an automated voice. Please report any issues or inconsistencies here . California's two most prominent Democrats, former Vice President Kamala Harris and Gov. Gavin Newsom, addressed national Democratic leaders in L.A.

Modeling complex human behavior, such as voter decisions in national elections, is a long-standing challenge for computational social science. Traditional agent-based models (ABMs) are limited by oversimplified rules, while large-scale statistical models often lack interpretability. We introduce FlockVote, a novel framework that uses Large Language Models (LLMs) to build a "computational laboratory" of LLM agents for political simulation. Each agent is instantiated with a high-fidelity demographic profile and dynamic contextual information (e.g. candidate policies), enabling it to perform nuanced, generative reasoning to simulate a voting decision. We deploy this framework as a testbed on the 2024 U.S. Presidential Election, focusing on seven key swing states. Our simulation's macro-level results successfully replicate the real-world outcome, demonstrating the high fidelity of our "virtual society". The primary contribution is not only the prediction, but also the framework's utility as an interpretable research tool. FlockVote moves beyond black-box outputs, allowing researchers to probe agent-level rationale and analyze the stability and sensitivity of LLM-driven social simulations.

There is some knowledge from anatomy (Harris, et al, 2019).

Next-gen networking tech, sometimes powered by light instead of electricity, is emerging as a critical piece of AI infrastructure. The new era of Silicon Valley runs on networking--and not the kind you find on LinkedIn. As the tech industry funnels billions into AI data centers, chip makers both big and small are ramping up innovation around the technology that connects chips to other chips, and server racks to other server racks. Networking technology has been around since the dawn of the computer, critically connecting mainframes so they can share data. In the world of semiconductors, networking plays a part at almost every level of the stack--from the interconnect between transistors on the chip itself, to the external connections made between boxes or racks of chips.

There is some knowledge from anatomy (Harris, et al, 2019).

Things to Do in L.A. Tap to enable a layout that focuses on the article. Did Kamala Harris just destroy her 2028 chances? Is Gavin Newsom glad she did? One pointed passage in Kamala Harris' new book refers to her longtime frenemy, Gavin Newsom, and his response to her elevation atop the Democratic ticket. This is read by an automated voice.

Lon Harris, executive producer of the This Week in Startups podcast, stoked the conversation this week when he posted: "Dipping below like 5% on Rotten Tomatoes has basically the same appeal to me as breaking 90%. "That's some[thing] I need to experience right there." A film with a rock bottom rating is bound to be interesting, Harris tells BBC News. "A very low score indicates universal agreement. Now I want to know more... Why does everyone agree?

Former Vice President Kamala Harris closed a big door when she announced Wednesday that she would not run for California governor. But she left open a heap of others. Departing presidents, vice presidents, first ladies and failed presidential candidates have pursued a wide variety of paths in the past. Empowered with name recognition and influence but with no official role to fill, they possess the freedom to choose their next adventure. Al Gore took up a cause in global warming, while George W. Bush took up painting.

Stance detection identifies the viewpoint expressed in text toward a specific target, such as a political figure. While previous datasets have focused primarily on tweet-level stances from established platforms, user-level stance resources, especially on emerging platforms like Bluesky remain scarce. User-level stance detection provides a more holistic view by considering a user's complete posting history rather than isolated posts. We present the first stance detection dataset for the 2024 U.S. presidential election, collected from Bluesky and centered on Kamala Harris and Donald Trump. The dataset comprises 16,044 user-target stance pairs enriched with engagement metadata, interaction graphs, and user posting histories. PolitiSky24 was created using a carefully evaluated pipeline combining advanced information retrieval and large language models, which generates stance labels with supporting rationales and text spans for transparency. The labeling approach achieves 81\% accuracy with scalable LLMs. This resource addresses gaps in political stance analysis through its timeliness, open-data nature, and user-level perspective. The dataset is available at https://doi.org/10.5281/zenodo.15616911

We present a critical discourse analysis of the 2024 U.S. presidential debates, examining Donald Trump's rhetorical strategies in his interactions with Joe Biden and Kamala Harris. We introduce a novel annotation framework, BEADS (Bias Enriched Annotation for Dialogue Structure), which systematically extends the DAMSL framework to capture bias driven and adversarial discourse features in political communication. BEADS includes a domain and language agnostic set of tags that model ideological framing, emotional appeals, and confrontational tactics. Our methodology compares detailed human annotation with zero shot ChatGPT assisted tagging on verified transcripts from the Trump and Biden (19,219 words) and Trump and Harris (18,123 words) debates. Our analysis shows that Trump consistently dominated in key categories: Challenge and Adversarial Exchanges, Selective Emphasis, Appeal to Fear, Political Bias, and Perceived Dismissiveness. These findings underscore his use of emotionally charged and adversarial rhetoric to control the narrative and influence audience perception. In this work, we establish BEADS as a scalable and reproducible framework for critical discourse analysis across languages, domains, and political contexts.