Welcome to our latest roundup of what's going on in the indie game space. It's Gamescom week, so there have been tons of game announcements. We'll dig into several of those as well as a few new games you can jump into this weekend. You may recall a long-running saga about a guy who tried to gain access to a landfill site because he was convinced it contained a hard drive he accidentally threw away in 2013. The hard drive is said to house a private key for 8,000 Bitcoin, which is worth hundreds of millions of dollars.

Wed 26 Aug 2026 08.00 EDTLast modified on Wed 26 Aug 2026 16.37 EDT On a winding road tucked away behind forests in the Appalachian foothills of southern Ohio is where OpenAI, Nvidia and Japanese investors are set to spend $500bn on one of the largest artificial intelligence datacenters on the planet. Last March, the energy secretary, Chris Wright, the commerce secretary, Howard Lutnick and a host of Japanese and other dignitaries briefly descended on Piketon to enthusiastically break ground on a project to build 8GW worth of AI computing power. But locally, there's a different feeling: a mix of hope but also concern. "Personally, my emotions range between positive and skeptical," says Billy Spencer, who has been mayor of Piketon for the past 23 years, of the project. "There's not an organized opposition to it around here. There hasn't been that much talk. No one's come to council - I don't know that there's been one citizen who lives within the village of Piketon who has come and said: 'Mayor, what do you think about it?'"

How do garbage trucks work? Behind every trash day is a powerful, sophisticated machine. 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. Peek inside the powerful machines that collect, compact, and haul away your trash. Breakthroughs, discoveries, and DIY tips sent six days a week.

Reinforcement Learning from Human Feedback (RLHF) is essential for aligning large language models (LLMs) with human preferences and values. While recent research has primarily focused on algorithmic advancements--such as reducing computational overhead or strengthening reward models to mitigate reward hacking--the critical role of prompt-data construction and its scalability has received comparatively less attention. In this paper, we address this gap by systematically exploring data-driven bottlenecks that currently hinder RLHF performance scaling, focusing specifically on the challenges posed by reward hacking and decreasing response diversity. To mitigate reward hacking, we introduce a hybrid reward system combining reasoning task verifiers (RTV) and a generative reward model (GenRM). This approach enables accurate assessment of responses against clearly defined ground-truth solutions. Additionally, in order to ensure response diversity and enhance learning effectiveness, we propose a novel prompt-selection method named Pre-PPO, explicitly identifying training prompts that are inherently challenging and thus less prone to reward hacking.

Minamitorishima is nearly 1,250 miles east of Tokyo. The island is surrounded by a coral atoll and is only 0.6 miles wide. Breakthroughs, discoveries, and DIY tips sent six days a week. Nuclear power is on the rise around the world, but with it comes an extremely pressing question: where will all of the radioactive waste be stored? For Japan, one answer may lie in literally the most remote location at their disposal.

Rising costs, shifting beliefs, and environmental concerns are accelerating the decline of casket burials. Breakthroughs, discoveries, and DIY tips sent six days a week. The casket industry may soon require life support in the United States. According to analysis from the National Funeral Directors Association (NFDA), cremation is by far the more popular option compared to the traditional burial method. The NFDA estimates around 63 percent of all funerary requests were for cremation in 2025, compared to about 31 percent for casket burials.

Hundreds of illegal dumps are operating across England, including at least 11 so-called super sites containing tens of thousands of tonnes of rubbish, a BBC investigation has found. Drone footage showed one of the waste dumps in Over, Gloucestershire. Most sites are in countryside locations, often hidden, and on what should be agricultural land. Police say many are run by organised crime gangs, who are making cash by charging much less than legitimate operators to take and bury waste. How the great outdoors went from an escape from the nine to five to a full-time social media job.

The biodegradable design could help keep plastic from becoming fish food. Breakthroughs, discoveries, and DIY tips sent every weekday. Chances are sushi aficionados have left a restaurant take-out in tow and with a handful of adorable, but environmentally problematic, fish-shaped soy sauce packets. These single-use plastic " shoyu-tai " drip bottles are as iconic as they are convenient, but their small size and disposability mean they often end up sliding down sinks and into drains. Once in the big blue, they slowly break down into microplastics that are then eaten by fish .

Things to Do in L.A. Tap to enable a layout that focuses on the article. An attendee plays the Monster Hunter Wilds video game on the Sony PlayStation 5 Pro console during the Tokyo Game Show 2024 at Makuhari Messe in 2024 in Chiba, Japan. This is read by an automated voice. Please report any issues or inconsistencies here . With the start of the new year, Californians will pay a new fee every time they buy a product with a nonremovable battery -- whether it's a power tool, a PlayStation or even a singing greeting card.

Constrained decision-making is essential for designing safe policies in real-world control systems, yet simulated environments often fail to capture real-world adversities. We consider the problem of learning a policy that will maximize the cumulative reward while satisfying a constraint, even when there is a mismatch between the real model and an accessible simulator/nominal model. In particular, we consider the robust constrained Markov decision problem (RCMDP) where an agent needs to maximize the reward and satisfy the constraint against the worst possible stochastic model under the uncertainty set centered around an unknown nominal model. Primal-dual methods, effective for standard constrained MDP (CMDP), are not applicable here because of the lack of the strong duality property. Further, one cannot apply the standard robust value-iteration based approach on the composite value function either as the worst case models may be different for the reward value function and the constraint value function. We propose a novel technique that effectively minimizes the constraint value function--to satisfy the constraints; on the other hand, when all the constraints are satisfied, it can simply maximize the robust reward value function. We prove that such an algorithm finds a policy with at most $ε$ sub-optimality and feasible policy after $O(ε^{-2})$ iterations. In contrast to the state-of-the-art method, we do not need to employ a binary search, thus, we reduce the computation time by at least 4x for smaller value of discount factor ($γ$) and by at least 6x for larger value of $γ$.