Probabilistic Ising machines (PIMs) are advanced and specialized computing systems that could tackle computationally hard problems, such as optimization or integer factorization tasks, more efficiently than classical systems. To solve problems, PIMs rely on interacting probabilistic bits (p-bits), networks of interacting units of digital information with values that randomly fluctuate between 0 and 1, but that can be biased to converge to yield desired solutions.Probabilistic Ising machines (PIMs) are advanced and specialized computing systems that could tackle computationally hard problems, such as optimization or integer factorization tasks, more efficiently than classical systems. To solve problems, PIMs rely on interacting probabilistic bits (p-bits), networks of interacting units of digital information with values that randomly fluctuate between 0 and 1, but that can be biased to converge to yield desired solutions.[#item_full_content]

Train delays can cascade into stalled commutes, economic losses, and vacation snags. Scheduling trains is computationally complex, though: It can take hours or days to solve large transportation networks on traditional computers, when disruptions like train breakdowns or traffic accidents demand much quicker solutions.Train delays can cascade into stalled commutes, economic losses, and vacation snags. Scheduling trains is computationally complex, though: It can take hours or days to solve large transportation networks on traditional computers, when disruptions like train breakdowns or traffic accidents demand much quicker solutions.[#item_full_content]

Artificial intelligence is getting smarter every day, but it still has its limits. One of the biggest challenges has been teaching advanced AI models to reason, which means solving problems step by step. But in a new paper published in the journal Nature, the team from DeepSeek AI, a Chinese artificial intelligence company, reports that they were able to teach their R1 model to reason on its own without human input.Artificial intelligence is getting smarter every day, but it still has its limits. One of the biggest challenges has been teaching advanced AI models to reason, which means solving problems step by step. But in a new paper published in the journal Nature, the team from DeepSeek AI, a Chinese artificial intelligence company, reports that they were able to teach their R1 model to reason on its own without human input.[#item_full_content]

Developments in autonomous robotics have the potential to revolutionize manufacturing processes, making them more flexible, customizable, and efficient. But coordinating fleets of autonomous, mobile robots in a shared space—and helping them work with each other and with human partners—is an extremely complicated task.Developments in autonomous robotics have the potential to revolutionize manufacturing processes, making them more flexible, customizable, and efficient. But coordinating fleets of autonomous, mobile robots in a shared space—and helping them work with each other and with human partners—is an extremely complicated task.[#item_full_content]

When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions about, for instance, the model architecture, optimizers, and training datasets before committing to a model.When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions about, for instance, the model architecture, optimizers, and training datasets before committing to a model.[#item_full_content]

Everyone hates traffic. Big cities in particular are plagued by an overabundance of vehicles, turning a simple crosstown jaunt into an odyssey during rush hour. Part of the problem is that traffic is incredibly complex, and a small change in one part of the system can have ripple effects that alter traffic patterns throughout a city. City planners attempting to improve local traffic grids can often struggle to foresee all the effects their changes could have.Everyone hates traffic. Big cities in particular are plagued by an overabundance of vehicles, turning a simple crosstown jaunt into an odyssey during rush hour. Part of the problem is that traffic is incredibly complex, and a small change in one part of the system can have ripple effects that alter traffic patterns throughout a city. City planners attempting to improve local traffic grids can often struggle to foresee all the effects their changes could have.[#item_full_content]

To train artificial intelligence (AI) models, researchers need good data and lots of it. However, most real-world data has already been used, leading scientists to generate synthetic data. While the generated data helps solve the issue of quantity, it may not always have good quality, and assessing its quality has been overlooked.To train artificial intelligence (AI) models, researchers need good data and lots of it. However, most real-world data has already been used, leading scientists to generate synthetic data. While the generated data helps solve the issue of quantity, it may not always have good quality, and assessing its quality has been overlooked.[#item_full_content]

Artificial intelligence is becoming increasingly versatile—from route planning to text translation, it has long become a standard tool. But it is not enough for AI to simply deliver useful results: it is becoming ever more important that it also complies with legal, ethical, and social norms. But how can such norms be taught to a machine?Artificial intelligence is becoming increasingly versatile—from route planning to text translation, it has long become a standard tool. But it is not enough for AI to simply deliver useful results: it is becoming ever more important that it also complies with legal, ethical, and social norms. But how can such norms be taught to a machine?[#item_full_content]

Growing up, we learn to push just hard enough to move a box and to avoid touching a hot pan with our bare hands. Now, a robot hand has been developed that also has these instincts.Growing up, we learn to push just hard enough to move a box and to avoid touching a hot pan with our bare hands. Now, a robot hand has been developed that also has these instincts.[#item_full_content]

By challenging AI chatbots to judge thousands of moral dilemmas posted in a popular Reddit forum, UC Berkeley researchers revealed that each platform appears to follow its own set of ethics.By challenging AI chatbots to judge thousands of moral dilemmas posted in a popular Reddit forum, UC Berkeley researchers revealed that each platform appears to follow its own set of ethics.[#item_full_content]