The robust training built upon the loose guarantees limits the improvement of model robustness.

The right to be forgotten calls for efficient machine unlearning techniques that make trained machine learning models forget a cohort of data.

License Multi-LexSum is distributed under the Open Data Commons Attribution License (ODC-By).

The original questions are in bold . The subtext to each question is in italics. The answers are in plain text with no formatting. The questions in this section are primarily intended to encourage dataset creators to clearly articulate their reasons for creating the dataset and to promote transparency about funding interests. For what purpose was the dataset created? Was there a specific task in mind? Was there a specific gap that needed to be filled? The Dollar Street dataset is a supervised image dataset derived from Gapminder's Dollar Street project ( https://www.gapminder.org/dollar-street) that contains everyday household items from homes around the world. It was created with three goals in mind: 1. Make available a highly curated set of images with valuable metadata (e.g. Our evaluation results show that the Dollar Street dataset can add significant value to accuracy improvements when considering computer vision images that represent the geographic and socioeconomic diversity of the world. Concretely, this means that the dataset only contains CC-BY-licensed works.

This dataset includes images from homes with no internet access and incomes as low as $26.99 per

Peak is this summer's finest co-op game. The game, created in partnership with developers Aggro Crab and Landfall as part of a game jam, is currently in Steam's top five bestsellers. It sold over a million copies in its first week, and has now surpassed 8 million, according to Aggro Crab cofounder Nick Kamen. Now, as a result of its success, says Kamen, scammers are selling cheap, AI-made versions of it wherever they can. "We hate to see it," says Kamen.

Efforts to gut regulation across the US government using AI are well underway. On Wednesday, the Office of the Chief Information Officer at the Office of Management and Budget hosted a video call to discuss an AI tool being used to cut federal regulations, which the office called SweetREX Deregulation AI. The tool, which is still being developed, is built to identify sections of regulations that aren't required by statute, then expedite the process for adopting updated regulations. The development and rollout of what is being formally called the SweetREX Deregulation AI Plan Builder, or SweetREX DAIP, is meant to help achieve the goals laid out in President Donald Trump's "Unleashing Prosperity Through Deregulation" executive order, which aims to "promote prudent financial management and alleviate unnecessary regulatory burdens." Industrial-scale deregulation is a core aim laid out in Project 2025, the document that has served as a playbook for the second Trump administration.