Goto

Collaborating Authors

 donnell


'Astonishingly lethal': BBC reports from site of Russian strike in Kyiv

BBC News

At least six people have been killed in a wave of Russia strikes on Kyiv, which the Ukrainian President Volodymyr Zelensky has condemned as a heinous attack. The BBC's James Landale visited the scene of one attack in eastern Kyiv where a drone rammed through a block of flats and left six people dead. Several other regions were also targeted. A drone attack on a market at Chornomorsk in the south of the country killed two people. Catherine Connolly has'never believed more' in the spirit of Ireland New Irish President Catherine Connolly says she has been given a powerful mandate to articulate a vision for a new republic.


Random Spiking Neural Networks are Stable and Spectrally Simple

Araya, Ernesto, Datres, Massimiliano, Kutyniok, Gitta

arXiv.org Machine Learning

Spiking neural networks (SNNs) are a promising paradigm for energy-efficient computation, yet their theoretical foundations-especially regarding stability and robustness-remain limited compared to artificial neural networks. In this work, we study discrete-time leaky integrate-and-fire (LIF) SNNs through the lens of Boolean function analysis. We focus on noise sensitivity and stability in classification tasks, quantifying how input perturbations affect outputs. Our main result shows that wide LIF-SNN classifiers are stable on average, a property explained by the concentration of their Fourier spectrum on low-frequency components. Motivated by this, we introduce the notion of spectral simplicity, which formalizes simplicity in terms of Fourier spectrum concentration and connects our analysis to the simplicity bias observed in deep networks. Within this framework, we show that random LIF-SNNs are biased toward simple functions. Experiments on trained networks confirm that these stability properties persist in practice. Together, these results provide new insights into the stability and robustness properties of SNNs.


Tornado hits Paris suburbs leaving one dead

BBC News

A tornado tore through Val-d'Oise, north of Paris, on Monday, toppling construction cranes, damaging properties and uprooting trees in its path. One person was killed and four others critically injured, authorities said. The town of Ermont, about 20 km (13 miles) northeast of Paris was hardest hit by the sudden twister, which caused damage in multiple districts. Interior Minister Laurent Nunez said on the X social media platform that it had been a storm of rare intensity. Drone footage shows blaze destroying the historic Bernaga Monastery in Italy.


BBC at scene of 'brazen' Louvre jewel theft

BBC News

BBC at scene of'brazen' Louvre jewel theft A manhunt is under way for a gang of thieves who carried out a broad daylight raid on Paris's Louvre Museum, and stole jewels described as priceless. The gang appear to have used a mechanical ladder to reach a first-floor window, before breaking into display cases and escaping on motorbikes. The BBC's Hugh Schofield is outside the museum where the extraordinary, daring and brazen robbery took place. Drone footage shows blaze destroying the historic Bernaga Monastery in Italy. Could a Corrie cameo be on the cards for Daniel O'Donnell?


Watch: Fire at historic Italian monastery

BBC News

Drone footage has emerged showing a blaze destroying the historic Bernaga Monastery in Italy. Founded in La Valletta Brianza in 1628, it is located about 30km (19 miles) east of Milan. More than 20 cloistered nuns were evacuated from the scene, according to Italian media reports. Could a Corrie cameo be on the cards for Daniel O'Donnell? Daniel O'Donnell said making a cameo on Coronation Street is on his bucket list.



3 Things James O'Donnell is into right now

MIT Technology Review

This is a podcast in which two very smart people (who happen to be young and hilarious professors of philosophy) draw unexpected philosophical connections between facets of modern life. Ellie Anderson and David Peña-Guzmán have done hour-long episodes on everything from mommy issues to animal justice, with particularly sharp segments on tech-adjacent issues like biohacking and the relationship between AI and art. Whenever I think society is dealing with a brand-new problem, these two unearth someone who was pondering it centuries ago. It's a treat to listen to. Over the summer I was eager to watch Mountainhead, a darkly funny film by Jesse Armstrong, the creator of Succession, that follows four unlikable tech founders as they watch the world collapse under political turmoil and violence caused by AI deepfakes.


Trump threatens to strip Rosie O'Donnell's U.S. citizenship as he says she's a 'threat to humanity'

FOX News

Fox News contributor Raymond Arroyo sounds off on Rosie The Pivoter ODonnell for her latest criticism of the Trump administration and the NEA teacher of the years admission that the job is deeply political. President Donald Trump has escalated his long-running feud with Rosie O'Donnell. On Saturday, Trump, 79, floated the idea of revoking the 63-year-old comedian and actress's U.S. citizenship following her move to Ireland earlier this year. "Because of the fact that Rosie O'Donnell is not in the best interests of our Great Country, I am giving serious consideration to taking away her Citizenship," Trump wrote in a post to his social media platform Truth Social. "She is a Threat to Humanity, and should remain in the wonderful Country of Ireland, if they want her. GOD BLESS AMERICA!" he added.


Microsoft's Copilot gamble is a bust. But AI PCs still feel inevitable

PCWorld

A year ago, Microsoft hyped Copilot PCs as the next big thing. Twelve months later, it's hard not to see them as one of the tech industry's more significant flops. The question is whether they'll stay that way. Many Copilot PCs began shipping on June 18, 2024, about a month after Microsoft announced the program at the company's headquarters a month earlier. Acer, Asus, Dell, HP, Lenovo, Samsung, and Microsoft's own Surface division committed to shipping Copilot PCs, whose centerpiece was a processor with an embedded Neural Processing Unit -- the engine of AI -- capable of 40 trillion operations per second, or TOPS.


DeepMultiConnectome: Deep Multi-Task Prediction of Structural Connectomes Directly from Diffusion MRI Tractography

Vroemen, Marcus J., Chen, Yuqian, Lo, Yui, Xue, Tengfei, Cai, Weidong, Zhang, Fan, Pluim, Josien P. W., O'Donnell, Lauren J.

arXiv.org Artificial Intelligence

Diffusion MRI (dMRI) tractography enables in vivo mapping of brain structural connections, but traditional connectome generation is time-consuming and requires gray matter parcellation, posing challenges for large-scale studies. We introduce DeepMultiConnectome, a deep-learning model that predicts structural connectomes directly from tractography, bypassing the need for gray matter parcellation while supporting multiple parcellation schemes. Using a point-cloud-based neural network with multi-task learning, the model classifies streamlines according to their connected regions across two parcellation schemes, sharing a learned representation. We train and validate DeepMultiConnectome on tractography from the Human Connectome Project Young Adult dataset ($n = 1000$), labeled with an 84 and 164 region gray matter parcellation scheme. DeepMultiConnectome predicts multiple structural connectomes from a whole-brain tractogram containing 3 million streamlines in approximately 40 seconds. DeepMultiConnectome is evaluated by comparing predicted connectomes with traditional connectomes generated using the conventional method of labeling streamlines using a gray matter parcellation. The predicted connectomes are highly correlated with traditionally generated connectomes ($r = 0.992$ for an 84-region scheme; $r = 0.986$ for a 164-region scheme) and largely preserve network properties. A test-retest analysis of DeepMultiConnectome demonstrates reproducibility comparable to traditionally generated connectomes. The predicted connectomes perform similarly to traditionally generated connectomes in predicting age and cognitive function. Overall, DeepMultiConnectome provides a scalable, fast model for generating subject-specific connectomes across multiple parcellation schemes.