PCWorld reports the Steam Deck has returned to market with nearly doubled pricing, featuring only OLED models at $789 for 512GB and $949 for 1TB versions. Valve discontinued cheaper LCD models and attributes price increases to rising memory and storage costs driven by AI industry demand affecting consumer hardware. This trend extends beyond Steam Deck to other gaming handhelds like Lenovo Legion Go, signaling broader affordability challenges in PC gaming hardware. The Steam Deck, harbinger of a portable PC gaming revolution, has been out of stock for three months. Now it's back at almost double the price of the original model. It'll cost you $789 USD to get the 512GB OLED version, $949 for the 1TB upgrade. The original LCD model, which debuted at $400, is resigned to the dustbin of history . Welcome to PC gaming in 2026, where the K-shaped economy has claimed the last remaining affordable option. The 512GB OLED model now costs $1,129 in Canada, 649 pounds in the UK, 779 euro in Europe, $1,199 in Australia, and 3,279 PLN in Poland.

Deep learning models for 12-lead electrocardiogram (ECG) analysis achieve high diagnostic performance but lack the intuitive interpretability required for clinical integration. Standard feature attribution methods are limited by the inherent difficulty in mapping abstract waveform fluctuations to physical anatomical pathologies. To resolve this, we propose a cross-modal method that projects feature attributions from high-performance 12-lead ECG models onto the CineECG 3D anatomical space. Our study reveals that while models trained directly on CineECG signals suffer from reduced accuracy and incoherent attributions, the proposed mapping mechanism effectively recovers clinically relevant feature rankings. Validated against a ground-truth dataset of 20 cases annotated by domain experts, the mapped explanations yield a Dice score of 0.56, significantly outperforming the 0.47 baseline of standard 12-lead attributions. These findings indicate that cross-modal averaging mapping effectively filters attribution instability and improves the localization of pathological features, combining the diagnostic expressiveness of standard ECG with the intuitive clarity of anatomical visualization.

What does the data tell us about immigration in Wales? Like many countries, Wales sees a steady flow of people arriving and leaving for other countries each year. The difference between those arriving and those leaving is known as net migration. Focusing on people moving from abroad, latest estimates say Wales' population - which was 3.2 million in June 2024 - had increased by about 23,000 over the previous year as a result of net international migration. A recent YouGov poll found a quarter of people surveyed in Wales believed that immigration, alongside the economy, should be among the issues prioritised by the Welsh government, even though immigration is controlled by the UK government.

Geographic context is often consider relevant to motor insurance risk, yet public actuarial datasets provide limited location identifiers, constraining how this information can be incorporated and evaluated in claim-frequency models. This study examines how geographic information from alternative data sources can be incorporated into actuarial models for Motor Third Party Liability (MTPL) claim prediction under such constraints. Using the BeMTPL97 dataset, we adopt a zone-level modeling framework and evaluate predictive performance on unseen postcodes. Geographic information is introduced through two channels: environmental indicators from OpenStreetMap and CORINE Land Cover, and orthoimagery released by the Belgian National Geographic Institute for academic use. We evaluate the predictive contribution of coordinates, environmental features, and image embeddings across three baseline models: generalized linear models (GLMs), regularized GLMs, and gradient-boosted trees, while raw imagery is modeled using convolutional neural networks. Our results show that augmenting actuarial variables with constructed geographic information improves accuracy. Across experiments, both linear and tree-based models benefit most from combining coordinates with environmental features extracted at 5 km scale, while smaller neighborhoods also improve baseline specifications. Generally, image embeddings do not improve performance when environmental features are available; however, when such features are absent, pretrained vision-transformer embeddings enhance accuracy and stability for regularized GLMs. Our results show that the predictive value of geographic information in zone-level MTPL frequency models depends less on model complexity than on how geography is represented, and illustrate that geographic context can be incorporated despite limited individual-level spatial information.

What would happen if Yellowstone's'supervolcano' erupted today? Say goodbye to Montana, Wyoming, and Idaho. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. This photo of a volcano in Iceland doesn't even begin to encapsulate the devastation that would happen if the Yellowstone volcano erupted. Breakthroughs, discoveries, and DIY tips sent six days a week.

Toyota's CUE7 robot sank a free throw at Toyota Arena Tokyo using AI-powered reinforcement learning instead of pre-programmed instructions, marking a shift in how robots are trained.

Booking.com confirmed hackers may have accessed customer names, emails, phone numbers and booking details, though financial data was not compromised in the breach.

Michael Dell and Susan Dell became the first donors to give more than $1 billion to the University of Texas at Austin, funding a massive AI-native hospital and research campus.

Amazon Alexa+ introduced voice-powered food ordering through Uber Eats and Grubhub, letting users build and modify delivery orders hands-free on Echo devices.