OpenAI's President Gave Millions to Trump. He Says It's for Humanity In an interview with WIRED, Greg Brockman says his political donations support OpenAI's mission--even if some employees at the company disagree. OpenAI's president and cofounder Greg Brockman doesn't consider himself political, which is surprising, because he was one of President Trump's biggest individual donors of 2025. Greg and his wife, Anna Brockman, gave $25 million to MAGA Inc--a super PAC that supports President Trump--in September of last year. The pair also gave $25 million to a bipartisan AI super PAC, Leading the Future, which says it plans to oppose politicians that jeopardize Americans' "ability to benefit from AI."

A "QuitGPT" campaign is urging people to cancel their ChatGPT subscriptions Backlash against ICE is fueling a broader movement against AI companies' ties to President Trump. In September, Alfred Stephen, a freelance software developer in Singapore, purchased a ChatGPT Plus subscription, which costs $20 a month and offers more access to advanced models, to speed up his work. But he grew frustrated with the chatbot's coding abilities and its gushing, meandering replies. Then he came across a post on Reddit about a campaign called QuitGPT . The campaign urged ChatGPT users to cancel their subscriptions, flagging a substantial contribution by OpenAI president Greg Brockman to President Donald Trump's super PAC MAGA Inc. It also pointed out that the US Immigration and Customs Enforcement, or ICE, uses a résumé screening tool powered by ChatGPT-4.

Silicon Valley's top CEOs have been noticeably silent after the Minneapolis shooting. Hours after Alex Pretti was killed by federal agents in Minneapolis on Saturday, Apple CEO Tim Cook and Amazon CEO Andy Jassy showed up for a movie night at the White House. Along with other business executives and several prominent Donald Trump supporters, they attended a private screening of, a new documentary about the president's wife. The moviegoers were treated to buckets of popcorn and sugar cookies frosted with the first lady's name. Silicon Valley's top executives have seemingly taken every opportunity to cozy up to Trump.

Specially commissioned drones will be used to fly blood donations as part of a new trial. Currently, blood donations are processed in south Wales then transported by road, a journey that can take hours. The ultimate ambition of the Dragon's Heart project is to fly life-saving blood samples to the scenes of accidents using drones weighing about 55lb (25kg) and 5.5ft wide (1.7m). The pilot, which is due to start in early 2026, was described as significant and exciting by the Welsh Blood Service. A hatch in the top means the blood sits in the body of the drone, helping to control the temperature of the blood and minimise vibrations.

Transformer-based models have shown promising performance on tabular data compared to their classical counterparts such as neural networks and Gradient Boosted Decision Trees (GBDTs) in scenarios with limited training data. They utilize their pre-trained knowledge to adapt to new domains, achieving commendable performance with only a few training examples, also called the few-shot regime. However, the performance gain in the few-shot regime comes at the expense of significantly increased complexity and number of parameters. To circumvent this trade-off, we introduce TabDistill, a new strategy to distill the pre-trained knowledge in complex transformer-based models into simpler neural networks for effectively classifying tabular data. Our framework yields the best of both worlds: being parameter-efficient while performing well with limited training data. The distilled neural networks surpass classical baselines such as regular neural networks, XGBoost and logistic regression under equal training data, and in some cases, even the original transformer-based models that they were distilled from.

Cultural Heritage texts contain rich knowledge that is difficult to query systematically due to the challenges of converting unstructured discourse into structured Knowledge Graphs (KGs). This paper introduces ATR4CH (Adaptive Text-to-RDF for Cultural Heritage), a systematic five-step methodology for Large Language Model-based Knowledge Extraction from Cultural Heritage documents. We validate the methodology through a case study on authenticity assessment debates. Methodology - ATR4CH combines annotation models, ontological frameworks, and LLM-based extraction through iterative development: foundational analysis, annotation schema development, pipeline architecture, integration refinement, and comprehensive evaluation. We demonstrate the approach using Wikipedia articles about disputed items (documents, artifacts...), implementing a sequential pipeline with three LLMs (Claude Sonnet 3.7, Llama 3.3 70B, GPT-4o-mini). Findings - The methodology successfully extracts complex Cultural Heritage knowledge: 0.96-0.99 F1 for metadata extraction, 0.7-0.8 F1 for entity recognition, 0.65-0.75 F1 for hypothesis extraction, 0.95-0.97 for evidence extraction, and 0.62 G-EVAL for discourse representation. Smaller models performed competitively, enabling cost-effective deployment. Originality - This is the first systematic methodology for coordinating LLM-based extraction with Cultural Heritage ontologies. ATR4CH provides a replicable framework adaptable across CH domains and institutional resources. Research Limitations - The produced KG is limited to Wikipedia articles. While the results are encouraging, human oversight is necessary during post-processing. Practical Implications - ATR4CH enables Cultural Heritage institutions to systematically convert textual knowledge into queryable KGs, supporting automated metadata enrichment and knowledge discovery.

Thousands of patients worldwide are waiting for a potentially life-saving donor. Thousands of patients worldwide are waiting for a potentially life-saving donor. Doctors have developed an AI tool that could reduce wasted efforts to transplant organs by 60%. Thousands of patients worldwide are waiting for a potentially life-saving donor, and more candidates are stuck on waiting lists than there are available organs. Recently, in cases where people need a liver transplant, access has been expanded by using donors who die after cardiac arrest.

An analysis of nearly $70 billion in donations showed feline lovers contributed slightly more. Breakthroughs, discoveries, and DIY tips sent every weekday. Or at least as old as about 26 to 35 million years ago when felines and canines first evolved . Cats and dogs duking it out for who is the best human companion . That debate has spilled over to humans, with research showing that dog owners are more often considered more social and community-oriented, while cat owners are believed to be more introverted and open-minded .

Dialogue agents based on large language models (LLMs) have shown promising performance in proactive dialogue, which requires effective strategy planning. However, existing approaches to strategy planning for proactive dialogue face several limitations: limited strategy coverage, preference bias in planning, and reliance on costly additional training. To address these, we propose PRINCIPLES: a synthetic strategy memory for proactive dialogue agents. PRINCIPLES is derived through offline self-play simulations and serves as reusable knowledge that guides strategy planning during inference, eliminating the need for additional training and data annotation. We evaluate PRINCIPLES in both emotional support and persuasion domains, demonstrating consistent improvements over strong baselines. Furthermore, PRINCIPLES maintains its robustness across extended and more diverse evaluation settings. See our project page at https://huggingface.co/spaces/kimnamssya/Principles.

Things to Do in L.A. Tap to enable a layout that focuses on the article. 'I just wanted to help.' Father turns to 9-year-old son for lifesaving stem cell donation Stephen Mondek became what Cedars-Sinai Medical Center believes is its youngest known stem cell donor. His father was dying of acute myeloid leukemia, a cancer that affects blood-forming cells in the bone marrow, and needed a donation to rebuild his immune system. This is read by an automated voice. Please report any issues or inconsistencies here .