Despite rapid progress in end-to-end AI music generation, AI-driven modeling of professional Digital Signal Processing (DSP) workflows remains challenging. In particular, while there is growing interest in neural black-box modeling of audio effect graphs (e.g. reverb, compression, equalization), AI-based approaches struggle to replicate the nuanced signal flow and parameter interactions used in professional workflows. Existing differentiable plugin approaches often diverge from real-world tools, exhibiting inferior performance relative to simplified neural controllers under equivalent computational constraints. We introduce WildFX, a pipeline containerized with Docker for generating multi-track audio mixing datasets with rich effect graphs, powered by a professional Digital Audio Workstation (DAW) backend. WildFX supports seamless integration of cross-platform commercial plugins or any plugins in the wild, in VST/VST3/LV2/CLAP formats, enabling structural complexity (e.g., sidechains, crossovers) and achieving efficient parallelized processing. A minimalist metadata interface simplifies project/plugin configuration. Experiments demonstrate the pipeline's validity through blind estimation of mixing graphs, plugin/gain parameters, and its ability to bridge AI research with practical DSP demands. The code is available on: https://github.com/IsaacYQH/WildFX.

Experience replay enables data-efficient learning from past experiences in online reinforcement learning agents. Traditionally, experiences were sampled uniformly from a replay buffer, regardless of differences in experience-specific learning potential. In an effort to sample more efficiently, researchers introduced Prioritized Experience Replay (PER). In this paper, we propose an extension to PER by introducing a novel measure of temporal difference error reliability. We theoretically show that the resulting transition selection algorithm, Reliability-adjusted Prioritized Experience Replay (ReaPER), enables more efficient learning than PER. We further present empirical results showing that ReaPER outperforms PER across various environment types, including the Atari-10 benchmark.

An AI-powered death clock promises to predict the exact day you'll die, right down to the second. The Death Clock app, available for download in Google and Apple stores, analyzes life choices users regularly make, their past habits, health conditions and family history of disease to'accurately' determine when they will die. Users are asked to put in a number of health markers like their cholesterol and blood-sugar levels, as well as their workout schedule, water intake, mental health and the current state of their romantic and plutonic relationships. The app is backed by data from 1,200 international life expectancy studies that looked at 53 million participants, including information from the Centers for Disease Control and Prevention. Although it seemed to be a morbid exercise, I took the test to see exactly how the results would play out.

This week, Blizzard released Diablo IV: Vessel of Hatred, an expansion to the wildly popular fantasy action-role-playing game that tasks players with slaughtering masses of screeching demons and collecting the randomized gear that they leave behind. Since coming out last year, Diablo IV has been a big success for Blizzard, earning more than 666 million (yes, really) in its first week. But before that release came years of fits and starts, including a predecessor that was perceived within Blizzard as an embarrassment and an iteration that was so drastically different, people began wondering if it was really still Diablo anymore. Today, Diablo is one of Blizzard's most important franchises. But to at least one Blizzard executive who was around in its early days, it wasn't even a "real game."

Kyiv, Ukraine – It looked like a deliberate manoeuvre by a skilled pilot that led to the first direct military clash between the United States and Russia since Moscow invaded Ukraine. Two Russian fighter jets approached a US drone flying in the cloudless, azure sky over international waters in the Black Sea on Tuesday morning. One of the Russian Su-27s released a stream of jet fuel on the MQ-9 Reaper drone, causing its cameras to shut off. Then the Su-27 hit the Reaper's propeller, causing it to tumble into the sea, the Pentagon said. It said the Reaper was a "reconnaissance drone" and carried no arms, although the unmanned aircraft with a wingspan of 26 metres (85 feet) was designed as a "hunter-killer" armed with laser-guided bombs and missiles.

Fox News correspondent Mike Tobin has the latest on tensions amid the Russia-Ukraine war on'Special Report.' The Russians planned the Black Sea drone attack carefully, probably for weeks. And watch out, China could try it next. As the admiral played by the late Sen. Fred D. Thompson said to Alec Baldwin's character in the classic movie "The Hunt for Red October," "The Russians don't do anything without a plan." Somebody on the Russian side thought this through.

You may have heard a lot of rumbling about a looming AI-generated "universe" where people can kick it in the Matrix, basically, with little more than just a pair of virtual reality headsets to guide them. But forget all that chatter, for something much better is now possible: An AI-driven software is now creating new videos for your favorite songs. As Classic Rock reports, it goes a little something like this: the software is programmed to generate visuals based on the text it's given to summarize. "cowbell," "instrumental bridge), and the software spits out completely new and totally modern images based on the data entered. Once you have the images, well hell--that's half the video!

Whether it's down to our own hubris, the disastrous effects of unbridled wealth accumulation and social division, war, the climate crisis, plague, a space rock or perhaps unfriendly aliens – we'll one day be dust caught in cosmic winds, lost to an indifferent universe. On our pale blue dot, the remnants of once-great civilisations and vanished peoples that we unearth already show us that advanced development is no guarantee of perpetuity. In sci-fi, humanity's naive yearning to fight on despite this realisation often proves a point of curiosity – and sometimes inspiration – for alien species. This is front and centre of the Mass Effect trilogy of video games, in which our imminent annihilation is given form in the tendrils of creatures called Reapers: ancient, building-sized, alien-robot hybrids that wipe out most life in the Milky Way every 50,000 years. Originally released between 2007 and 2012, the games were reissued this year as Mass Effect Legendary Edition, an updated complete trilogy, and there's a compelling case that they are among the best sci-fi ever made.

For years now, some of the best, wildest, most moving or revealing stories we've been telling ourselves have come not from books, movies or TV, but from video games. So we're running an occasional series, Reading The Game, in which we take a look at some of these games from a literary perspective. In the beginning, it was the Normandy that I fell for, not Mass Effect. If it hadn't been for the Normandy (gorgeous, sleek, the most advanced ship in the Alliance fleet and personal ride of Commander Shepard, star of the series), I might've just quit the newly remastered Legendary edition of the beloved trilogy after the first few hours. See, I did not like Mass Effect at all when I started playing.

The Pentagon's Joint Artificial Intelligence Center has awarded a $93.3 million contract to General Atomics Aeronautical Systems Inc (GA-ASI), makers of the MQ-9 Reaper, to equip the drone with new AI technology. The aim is for the Reaper to be able to carry out autonomous flight, decide where to direct its battery of sensors, and to recognize objects on the ground. The contract, announced at the end of last month, builds on a successful test earlier this year. In some ways this is not a major development, more of an incremental step using existing technology. What makes it significant is the drone that is being equipped, and what it will be able to do afterwards.