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'Kill the people': How men were left to starve in a South African gold mine

Al Jazeera

How men were left to starve in a South African gold mine. This image was created by Mohamed Hussein using the artificial intelligence (AI) tool Midjourney. Ayanda Ndabeni watched the faint glow from his headlamp fight the vast darkness 1,500 metres (4,920 feet) below ground. His miner's lamp had lasted for more than a week after he was lowered down into the shaft of the gold mine. But now the batteries were dying. He gently flipped the plastic switch of his lamp, turning it off, and the trapped men around him became shadows. In the stifling heat and humidity, their anxiety pressed in from all sides. Ayanda had descended into Shaft 10 of the Buffelsfontein mine in late September 2024, lowered by a team of nearly 20 men operating ropes and a pulley above ground. That day, he'd spotted police vehicles near the mine's entrance. The 36-year-old assumed it was just routine patrols around the mine system, which is 2km (1.2 miles) deep. But then the rope pulley, via which food, water, batteries and other items arrived, stopped moving. The shouting that usually indicated the rope operators were sending down a man or supplies also fell silent. When huge rocks came crashing down the shaft, they knew it was a warning. The men whispered of their growing fears that something was very wrong on the surface. Patrick Ntsokolo was also in Shaft 10. He was a few hundred metres higher up than Ayanda and had arrived in late July. Patrick was new to the mines. Tasked by the leaders of the artisanal miners with collecting the food, water and alcohol lowered down by the rope pulley, he hauled supplies along the slippery tunnels to small shops.




Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards

Neural Information Processing Systems

Project lead, main contributor, correspondence to alexandre.rame@isir.upmc.fr. Equal experimental contribution, order determined at random. Further information and resources related to this project can be found on this website.


d2b752ed4726286a4b488ae16e091d64-Supplemental-Conference.pdf

Neural Information Processing Systems

Table 3 presents comprehensive details of the TrojAI dataset. PICCOLO is a backdoor scanning tool aiming at detecting whether a language model is backdoored. It cannot reverse engineer exact triggers but optimizes a list of surrogate triggers that can induce ASR. The surrogate triggers by PICCOLO cannot be directly used. Table 4 documents the optimal prompts identified via fuzzing for each model.





Privacy utility trade offs for parameter estimation in degree heterogeneous higher order networks

Mandal, Bibhabasu, Nandy, Sagnik

arXiv.org Machine Learning

In sensitive applications involving relational datasets, protecting information about individual links from adversarial queries is of paramount importance. In many such settings, the available data are summarized solely through the degrees of the nodes in the network. We adopt the $β$ model, which is the prototypical statistical model adopted for this form of aggregated relational information, and study the problem of minimax-optimal parameter estimation under both local and central differential privacy constraints. We establish finite sample minimax lower bounds that characterize the precise dependence of the estimation risk on the network size and the privacy parameters, and we propose simple estimators that achieve these bounds up to constants and logarithmic factors under both local and central differential privacy frameworks. Our results provide the first comprehensive finite sample characterization of privacy utility trade offs for parameter estimation in $β$ models, addressing the classical graph case and extending the analysis to higher order hypergraph models. We further demonstrate the effectiveness of our methods through experiments on synthetic data and a real world communication network.


Jessie Buckley 'overwhelmed' to be starring in Oscar-tipped Hamnet

BBC News

Jessie Buckley'overwhelmed' to be starring in Oscar-tipped Hamnet The Oscar-tipped Hamnet, starring Jessie Buckley and Paul Mescal, is a film that shows the full range of human emotions, from elation to despair. It begins with a young William Shakespeare falling in love with Agnes (the other name by which the playwright's wife, historically referred to as Anne Hathaway, was known), and goes on to explore their immense grief after tragedy strikes their young family. But while it explores the sad origins of one of Shakespeare's greatest plays, Hamlet, it never portrays Agnes as just the playwright's wife - she is at the heart of the film. She was the full story of what I understand a woman to be, Buckley tells BBC News. And their capacity as women, and as mothers, and as lovers, and as people who have a language unto their own beside gigantic men of literature like Shakespeare.